Computer Vision
Urban Computing Health/Wellness Analytics
Image Retrieval Image Segmentation
Scene Classification Big
Data Contextual Inference Machine
Learning Vision+Language
Random Field Photo Collection MultimediaVideo
Analytics
Human-Centered Media & Interaction
Mobile Media Location-based service Geo Tagging
Action Recognition
Heterogeneous Information Networks Social
Multimedia Data Mining
Crowdsourcing 360° User
Profiling
12/15/2020: Congratulations to Yipeng
Zhang, who is selected for Honorable
Mention for the Computing
Research
Association's
(CRA) Outstanding Undergraduate Researcher
Award for 2021.
12/12/2019: Congratulations to Zhengyuan
Yang for
winning the 2020 Twitch Research Fellowship
to support his PhD
research on video and language. Twitch is the No. 1 live
streaming video service for video games in the
US, operated
by Twitch Interactive, a subsidiary of Amazon. In
addition, it offers
music broadcasts,
creative content, and more recently, "in real life"
streams.
11/08/2019: Congrats to newly minted Dr. Haofu Liaowho will join Amazon (AWS)
10/08/2019: Congratulations to Haofu
Liao for being selected as a finalist for
MICCAI
2019Young
Scientist Award
based his work on Artifact Disentanglement Network
for Unsupervised Metal Artifact Reduction
09/13/2019: Congrats to newly minted Dr. Jianbo Yuan who will join Amazon (AWS)
08/08/2019:
Congratulations to Weijian Li
for being selected for a graduate student travel award on
the basis of the score
obtained during the review process.
Weijian will present papers at MICCAI 2019. Yipeng
Zhang also
receives
an undergraduate student travel award.
07/29/2019: Yipeng Zhang, a CS
sophomore and a Xerox undergraduate engineering fellow
in this summer, is featured
in an Instagram post by our new University President
Sarah C. Mangelsdorf. It includes a picture of Yipeng
with Sarah in front of Yipeng's poster on "A deep
learning approach to early childhood caries
prevention."
12/07/2018: Professor Luo is elevated
to Fellow of AAAI(Association
for Advancement of Artificial Intelligence) for
"significant contributions to the fields of computer vision and
data mining, and particularly pioneering work
on multimodal
understanding for sentiment analysis, computational social
science, and digital health"
11/01/2018: Professor Luo is elevated
toFellow of ACM(Association
for Computing Machinery) for "contributions to
multimedia content analysis and social multimedia informatics"
10/03/2018: The
University of Rochester has been selected as a Morris K.
Udall Center of Excellence in Parkinson's
Disease Research by the National Institute of
Neurological Disorders and Stroke (NINDS). The new
$9.2 million award brings together researchers from industry and
multiple academic institutions to focus
on the development of digital tools to enhance understanding of
the disease, engage broad
populations in research, and accelerate the development of new
treatments for Parkinson's disease.
Professor Luo will co-lead the Advanced Analytics Core that
brings together a team of experts in
biostatistics, computational science and mathematics from
multiple institutions.
09/15/2018: Professor Luo is the recipient of the 2018 IEEE
Region 1 Technological Innovation in Academic Award for "contributions in computer vision and data mining"
08/24/2018: Congratulations to Zhengyuan Yang
and
Yixuan Zhang for winning Best
Industrial Related Paper Award
at ICPR 2018 for their
paper on "End-to-end Multi-Modal Multi-Task Vehicle Control
for Self-Driving Cars
with Visual Perception"
08/13/2018: Congrats to newly minted Dr. Yu
Wang who has joined Apple
06/29/2018:
Congratulations to Haofu Liao
for being "pre-selected for a student travel award on the
basis of the score your paper has obtained during the review
process". Haofu will present
two papers (both with early acceptance) at MICCAI 2018.
12/25/2017: Professor Luo is interviewed by Sixthtone
in a feature
"Even
China's Backwater Cities Are Going Smart" which reveals
China's grand plans
for an artificial intelligence rollout of
smart cities.
02/24/2017:
Professor Luo's Data Mining course was considered "favorite class
taken at the University of Rochester"
in
the Data Science program (Featured Article: Data
science for a better planet)
02/11/2017: National
Science Foundation Research Experience for Undergraduates (NSF
REU) Computational
Methods for Understanding Music, Media, and Minds
Please
note that the projects are flexible and the current descriptions
are meant as examples.
11/07/2016: Professor Luo is a panelist on NPR Radio, WXXI Connections
hosted by Evan Dawson Monthly Science Roundtable
"Twitter, Social Media and The Election"
10/21/2016: Our work on fine-grained
recognition of East Asian faces is covered by Washington
Post
You
are welcome to take the Asian Face Challenge at http://www.vista-today.com/asianmyth
to
help benchmark human recognition performance (currently at 49%
with 400+ tests)
Another
story on NextShark
10/01/2016: Professor Luo speaks at the Huang Symposium @UIUC to
celebrate the 80th birthday and
extraordinary
career of Professor Thomas S.
Huang
06/26/2016: Yiheng Zhou and Numair Sani, our
undergraduate researchers, present their work on mining Instagram
for
illicit drug use patterns at SBP-BRiMS
2016, supported by student travel scholarship
06/09/2016: Our work on "Will
Sanders Supporters Jump Ship to Trump?" is covered by Pacific
Standard
05/10/2016: Our work on using AI to hunt drug dealers
on Instagram is covered by Daily Dot
05/04/2016: Our work on "Voting with Feet: Who are leaving Hilary Clinton and
Donald Trump" is covered
by AOL, Daily
Dot, LipTV,Pivot
America
04/21/2016: Zhishen Pan,
a Junior student in the Data Science program, won the Poster
Presentation Award at the
2nd
Annual
Rochester Global Health Symposium & UNYTE Scientific
Session: Innovative Solutions to
Combat
Global Health Disparities for the poster "Towards Understanding
How News Coverage Affects
Public Perception During Epidemic
Outbreak." Congratulations!
03/20/2016: Our work on using Twitter user avatar facial analysis to study
Trump and Clinton followers is covered by MIT Technology Review,Digital Trends,Market
Exclusive
03/17/2016: Our CVPR
2016 paper - "Image Captioning with Semantic Attention" -
describes the engine behind a
system
that has been sitting atop the Leader
Board for the Microsoft COCO
(Common Objects in Context)
Image
Captioning Challenge since November 2015, beating Google, Microsoft, Baidu/UCLA, Stanford,
UC
Berkeley, University of Toronto/Montreal, and other power
houses. Full
Story.
09/06/2011: I am looking for two self-motivated PhD students
to join my research group in Fall 2012 to work in the areas
of computer vision and social media data mining.
Applicants are expected to have strong skills in both
programming and mathematics. Related research publications
in ranked venues of computer
vision, machine
learning, or data
mining is a plus . To apply, check http://www.cs.rochester.edu/education/phd-program.
09/01/2011: Professor Luo joined the CS Department after a
prolific career of 15+ years at Kodak Research Labs.
Jiebo Luo
joined the University of Rochester in Fall 2011 after over fifteen
prolific years at Kodak
Research Laboratories, where he was a Senior Principal
Scientist leading research and advanced development. He has been
involved in numerous technical conferences, including serving as
the program co-chair of ACM
Multimedia 2010, IEEE
CVPR 2012 and IEEE ICIP 2017. He has
served on the editorial boards of the IEEE Transactions on Pattern
Analysis and Machine Intelligence, IEEE Transactions on
Multimedia, IEEE Transactions on Circuits and Systems for Video
Technology, ACM Transactions on Intelligent Systems and
Technology, Pattern Recognition, Machine Vision and Applications,
and Journal of Electronic Imaging. Dr. Luo is the
Editor-in-Chief of the IEEE Transactions on Multimedia for the
2020-2022 term. Dr. Luo is a Fellow of ACM,AAAI,
IEEE, IAPR,
and SPIE.
Cheng Peng, Haofu Liao, Gina Wong, Jiebo Luo, S. Kevin Zhou,
Rama Chellappa, "XraySyn: Realistic View Synthesis from a Single
Radiograph through CT Prior," The 35th AAAI Conference on
Artificial Intelligence (AAAI), February 2021.
Jin Chen, Xinxiao Wu, Yao Hu, Jiebo Luo, ''Spatial-temporal
Causal Inference for Partial Image-to-video Adaptation," The
35th AAAI Conference on Artificial Intelligence (AAAI),
February 2021.
Haitian Zheng, Lele Chen, Chenliang Xu, Jiebo Luo, "Pose Flow
Learning from Person Images for Posed Guided Synthesis," IEEE
Transactions on Image Processing, 30:1898-1909, 2021.
Zhengyuan Yang, Tushar Kumar, Tinalang Chen, Jinsong Su, Jiebo
Luo, ''Grounding-Tracking-Integration,'' IEEE Transactions
on Circuits and Systems for Video Technology, in press.
Xinxiao Wu, Ruiqi Wang, Jingyi Hou, Hanxi Lin, Jiebo Luo,
''Spatial-Temporal Relation Reasoning for Action Prediction in
Videos,'' International Journal of Computer Vision (IJCV),
in press.
Jie An, Tianlang Chen, Songyang Zhang, Jiebo Luo, "Global
Image Sentiment Transfer," International Conference on
Pattern Recognition (ICPR), Milan, Italy, December 2020.
Mingkun Yang, Haitian Zheng, Xiang Bai, Jiebo Luo,
"Cost-Effective Adversarial Attacks against Scene Text
Recognition," International Conference on Pattern
Recognition (ICPR), Milan, Italy, December 2020.
Gaoang Wang, Lin Chen, Mingwei He, Jiebo Luo, "DAIL:
Dataset-Aware and Invariant Learning for Face Recognition," International
Conference on Pattern Recognition (ICPR), Milan, Italy,
December 2020.
Weijian Li, Haofu Liao, Shun Miao, Le Lu, Jiebo Luo,
"Unsupervised Learning of Landmarks based on Inter-Intra Subject
Consistencies," International Conference on Pattern
Recognition (ICPR), Milan, Italy, December 2020.
Zhengyuan Yang, Yuncheng Li, Linjie Yang, Ning Zhang, Jiebo
Luo, "Weakly Supervised Body Part Segmentation with Pose based
Part Priors," International Conference on Pattern
Recognition (ICPR), Milan, Italy, December 2020.
Zhengyuan Yang, Amanda Kay, Yuncheng Li, Wendi Cross, Jiebo
Luo, "Pose-based Body Language Recognition for Emotion and
Psychiatric Symptom Interpretation," International
Conference on Pattern Recognition (ICPR), Milan, Italy,
December 2020.
Heliang Zheng, Jianlong Fu, Yanhong Zeng, Zheng-jun Zha, Jiebo
Luo, "Learning Semantic-aware Normalization for Generative
Adversarial Networks," Neural Information Processing Systems
(NeurlPS), December 2020. (spotlight presentation)
Yiming Xu, Lin Chen, Zhongwei Cheng, Lixin Duan, Jiebo Luo,
"Open-Ended Visual Question Answering by Multi-Modal Domain
Adaptation," The Conference on Empirical Methods in Natural
Language Processing (EMNLP), Findings of EMNLP,
November 2020.
Xiankai Lu, Wenguan Wang, Jianbing Shen, David Crandall, Jiebo
Luo, "Zero-Shot Video Object Segmentation with Co-Attention
Siamese Networks," IEEE Transactions on Pattern
Analysis and Machine Intelligence, in press.
Wenbin Li*, Wei Xiong*, Haofu Liao, Jing Huo, Yang Gao, Jiebo
Luo, "CariGAN: Caricature Generation through Weakly Paired
Adversarial Learning," Neural Networks, in press.
Tianlang Chen, Wei Xiong, Haitian Zheng, Jiebo Luo, "Image
Sentiment Transfer," Brave and New Ideas Track, ACM
Multimedia Conference, Seattle, WA, October 2020. (Oral
Presentation)
Jing Wang, Jinhui Tang, Jiebo Luo, "Multimodal Attention with
Image Text Spatial Relationship for OCR-Based Image Captioning,"
ACM Multimedia Conference, Seattle, WA, October 2020.
Mengshi Qi, Jie Qin, Xiantong Zhen, Di Huang, Yi Yang, Jiebo
Luo, "Few-Shot Ensemble Learning for Video Classification with
SlowFast Memory Networks," ACM Multimedia Conference,
Seattle, WA, October 2020.
Huan Lin, Fandong Meng, Jinsong Su, Yongjing Yin, Zhengyuan
Yang, Yubin Ge, Jie Zhou, Jiebo Luo, "Dynamic Context-guided
Capsule Network for Multimodal Machine Translation," ACM
Multimedia Conference, Seattle, WA, October 2020.
Yangchun Zhu, Zheng-Jun Zha, Tianzhu Zhang, Jiawei Liu, Jiebo
Luo, "A Structured Graph Attention Network for Vehicle
Re-Identification," ACM Multimedia Conference, Seattle,
WA, October 2020. (Oral Presentation)
Hao Wang, Zheng-Jun Zha, Xuejin Chen, Zhiwei Xiong, Jiebo Luo,
"Dual Path Interaction Network for Video Moment Localization," ACM
Multimedia Conference, Seattle, WA, October 2020.
Haitian Zheng, Lele Chen, Chenliang Xu, Jiebo Luo, "Pose Flow
Learning from Person Images for Posed Guided Synthesis," IEEE
Transactions on Image Processing, in press.
Fuchen Long, Ting Yao, Zhaofan Qiu, Xinmei Tian, Jiebo Luo,
Tao Mei, "Learning to Localize Actions from Moments," European
Conference on Computer Vision (ECCV), Glasgow, UK, August
2020. (oral presentation)
Jianxin Lin, Yingxue Pang, Yingce Xia, Zhibo Chen, Jiebo Luo,
"TuiGAN: Learning Versatile Image-to-Image Translation with Two
Unpaired Images," European Conference on Computer Vision
(ECCV), Glasgow, UK, August 2020. (spotlight presentation)
Zhengyuan Yang, Tianlang Chen, Liwei Wang, Jiebo Luo,
"Improving One-stage Visual Grounding by Recursive Sub-query
Construction," European Conference on Computer Vision
(ECCV), Glasgow, UK, August 2020.
Tianlang Chen, Jiajun Deng, Jiebo Luo, "Adaptive Offline
Quintuplet Loss for Image-text Matching," European
Conference on Computer Vision (ECCV), Glasgow, UK, August
2020.
Haitian Zheng, Haofu Liao, Lele Chen, Wei Xiong, Tianlang
Chen, Jiebo Luo, "Example-Guided Image Synthesis across
Arbitrary Scenes using Masked Spatial-Channel Attention and
Self-Supervision," European Conference on Computer Vision
(ECCV), Glasgow, UK, August 2020.
Weijian Li, Yuhang Lu, Kang Zheng, Haofu Liao, Chihung Lin,
Jiebo Luo, Chi-Tung Cheng, Jing Xiao, Le Lu, Chang-Fu Kuo, Shun
Miao, "Cross-domain Structured Landmark Detection via
Progressive Topology-Adapting Deep Graph Learning," European
Conference on Computer Vision (ECCV), Glasgow, UK, August
2020.
Mang Ye, Jianbing Shen, David J. Crandall, Ling Shao, Jiebo
Luo, "Dynamic Dual-Attentive Aggregation Learning for
Visible-Infrared Person Re-Identification," European
Conference on Computer Vision (ECCV), Glasgow, UK, August
2020.
Huafeng Li, Jiajia Xu, Zhengtao Yu, and Jiebo Luo, "Jointly
Learning Commonality and Specificity Dictionaries for Person
Re-Identification," IEEE Transactions on Image Processing,
in IEEE Xplore.
Xin Liu, Kai Liu, Jinsong Su, Yebin Ge, Xiang Li, Bin Wang,
Jiebo Luo, "An Iterative Multi-Source Mutual Knowledge Transfer
Framework for Machine Reading Comprehension," International
Joint Conference on Artificial Intelligence (IJCAI),
Yokohama, Japan, July 2020.
Yongjing Yin, Fandong Meng, Jinsong Su, Chunlun Zhou,
Zhengyuan Yang, Jie Zhou, Jiebo Luo, "A Novel Graph-based
Multi-modal Fusion Encoder for Neural Machine Translation," Annual
Meeting of the Association for Computational Linguistics
(ACL), Seattle, WA, July 2020.
Mengshi Qi, Yunhong Wang, Annan Li, Jiebo Luo, "STC-GAN:
Spatio-temporally coupled Generative Adversarial Networks for
Predictive Scene Parsing," IEEE Transactions on Image
Processing, 29: 5420-5430, 2020.
Jingyi Hou, Xinxiao Wu, Ruiqi Wang, Jiebo Luo, Yunde Jia,
"Confidence-Guided Self Refinement for Action Prediction in
Untrimmed Videos," IEEE Transactions on Image Processing,
in press.
Wei Xiong, Yutong He, Yixuan Zhang, Wenhan Luo, Lin Ma, Jiebo
Luo, "Fine-grained Image-to-Image Transformation towards Visual
Recognition," IEEE/CVF Conferences on Computer Vision and
Pattern Recognition (CVPR), Seattle, WA, June 2020.
Jie Chen, Zhiheng Li, Chenliang Xu, Jiebo Luo, "Learning a
Weakly-Supervised Video Actor-Action Segmentation Model with a
Wise Selection," IEEE/CVF Conferences on Computer Vision and
Pattern Recognition (CVPR), Seattle, WA, June 2020. (oral presentation)
Zhongjie Yu, Lin Chen, Zhongwei Cheng, Jiebo Luo, "TransMatch:
A Transfer-Learning Scheme for Semi-Supervised Few-Shot
Learning," IEEE/CVF Conferences on Computer Vision and
Pattern Recognition (CVPR), Seattle, WA, June 2020.
Zhaoyi Wang, Jielei Zhang, Liang Zhang, Cong Yao, Jiebo Luo,
"On Vocabulary Reliance in Scene Text Recognition," IEEE/CVF
Conferences on Computer Vision and Pattern Recognition
(CVPR), Seattle, WA, June 2020.
Jiamin Wu, Tianzhu Zhang, Zheng-Jun Zha, Jiebo Luo, Yongdong
Zhang, Feng Wu, "Self-supervised Domain-aware Generative Network
for Generalized Zero-shot Learning," IEEE/CVF Conferences on
Computer Vision and Pattern Recognition (CVPR), Seattle,
WA, June 2020.
Jie An, Haoyi Xiong, Jun Huan, Jiebo Luo, "Ultrafast
Photorealistic Style Transfer via Neural Architecture Search," The
34th AAAI Conference on Artificial Intelligence (AAAI),
New York, NY, February 2020. (oral presentation)
Tianlang Chen, Jiebo Luo, "Expressing Objects just like Words:
Recurrent Visual Embedding for Image-Text Matching," The
34th AAAI Conference on Artificial Intelligence (AAAI),
New York, NY, February 2020.
Songyang Zhang, Houwen Peng, Jianlong Fu, Jiebo Luo, "Learning
2D Temporal Adjacent Networks for Moment Localization with
Natural Language," The 34th AAAI Conference on Artificial
Intelligence (AAAI), New York, NY, February 2020.
Jinyi Hou, Xinxiao Wu, Yunde Jia, Jiebo Luo, "Joint
Commonsense and Relation Reasoning for Image and Video
Captioning," The 34th AAAI Conference on Artificial
Intelligence (AAAI), New York, NY, February 2020.
Jiali Zeng, Linfeng Song, Jinsong Su, Xie Jun, Wei Song, Jiebo
Luo, "Neural Simile Recognition with Cyclic Multitask Learning
and Local Attention," The 34th AAAI Conference on Artificial
Intelligence (AAAI), New York, NY, February 2020.
Yongjing Yin, Fandong Meng, Jinsong Su, Yubin Ge, Linfeng
Song, Jie Zhou, Jiebo Luo, "Enhancing Pointer Network for
Sentence Ordering with Pairwise Ordering Predictions," The
34th AAAI Conference on Artificial Intelligence (AAAI),
New York, NY, February 2020.
Heliang Zheng, Zheng-Jun Zha, Jiebo Luo, "Learning Rich Part
Hierarchies with Progressive Attention Networks for Fine-Grained
Image Recognition," IEEE Transactions on Image Processing,
29: 476-488, 2020.
Tianliang Liu, Quanzeng You, Yanzhang Wang, Xiaodong Dong,
Xiubin Dai, Jiebo Luo, "Sentiment Recognition for Short
Annotated GIFs Using Visual-Textual Fusion," IEEE
Transactions on Multimedia, 22(4): 1098-1110, 2020.
2019
Jianxin Lin, Yingce Xia, Sen Liu, Tao Qin, Zhibo Chen, Jiebo
Luo, "Exploring Explicit Domain Supervision for Latent Space
Disentanglement in Unpaired Image-to-Image Translation," IEEE
Transactions on Pattern Analysis and Machine Intelligence,
in press.
Heliang Zheng, Jianlong Fu, Zheng-Jun Zha, Jiebo Luo,
"Learning Deep Bilinear Transformation for Fine-grained Image
Representation," Neural Information Processing Systems
(NeurlPS), Vancouver, Canada, December 2019.
Jaili Zeng, Yang Liu, Jinsong Su, Yubing Ge, Yaojie Lu,
Yongjing Yin and Jiebo Luo, "Iterative Dual Domain Adaptation
for Neural Machine Translation," Conference on Empirical
Methods in Natural Language Processing (EMNLP), Hong Kong,
November 2019.
Biao Zhang, Deyi Xiong, Jinsong Su, and Jiebo Luo,
"Future-Aware Knowledge Distillation for Neural Machine
Translation," IEEE Transactions on Audio, Speech and
Language Processing, in press.
Fuchen Long, Ting Yao, Xinwei Tian, Tao Mei, Jiebo Luo,
"Coarse-to-Fine Localization of Temporal Action Proposals," IEEE
Transactions on Multimedia, in press.
Rongrong Ji, Ke Li, Feng Guo, Xiaoshuai Sun, Yan Wang, Feiyue
Huang, Jiebo Luo, Gary Huang, "Semi-Supervised Adversarial
Monocular Depth Estimation," IEEE Transactions on Pattern
Analysis and Machine Intelligence, in press.
Yang Cong, Baojie Fan, Dongdong Hou, Huijie Fan, Kaizhou Liu,
Jiebo Luo, "Novel Event Analysis for Human-Machine Collaborative
Underwater Exploration," Pattern Recognition, in press.
Zhengyuan Yang, Boqing Gong, Liwei Wang, Wenbing Huang, Dong
Yu, Jiebo Luo, "A Fast and Accurate One-Stage Approach to Visual
Grounding," International Conference on Computer Vision (ICCV),
Seoul, South Korea, October 2019. (oral presentation)
Tianlang Chen, Zhaowen Wang, Ning Xu, Hailin Jin, Jiebo Luo.
"Large-scale Tag-based Font Retrieval with Generative Feature
Learning," International Conference on Computer Vision
(ICCV), Seoul, South Korea, October 2019.
Jingyi Hou, Xinxiao Wu, Wentian Zhao, Jiebo Luo, "Joint Syntax
Representation Learning and Visual Cues Translation for Video
Captioning," International Conference on Computer Vision
(ICCV), Seoul, South Korea, October 2019.
Songyang Zhang, Jinsong Su, Jiebo Luo, "Exploiting Temporal
Relationships in Video Moment Localization with natural
Language," ACM Multimedia Conference, Nice, France,
October 2019.
Jialong Tang, Ziyao Lu, Jinsong Su, Yubin Ge, Linfeng Song, Le
Sun, and Jiebo Luo, "Progressive Self-Supervised Attention
Learning for Aspect-Level Sentiment Analysis," Annual Meeting
of the Association for Computational Linguistics (ACL), Florence,
Italy, July 2019.
Yongjing Yin, Linfeng Song, Jinsong Su, Jiali Zeng, Chulun
Zhou, and Jiebo Luo, "Graph-based Neural Sentence Ordering," International
Joint Conference on Artificial Intelligence (IJCAI),
Macau, July 2019.
Heliang Zheng, Zheng-Jun Zha, Jiebo Luo, "Learning Rich Part
Hierarchies with Progressive Attention Networks for Fine-Grained
Image Recognition," IEEE Transactions on Image Processing,
in press.
Yang Feng, Lin Ma, Wei Liu, Jiebo Luo, "Unsupervised Image
Captioning," IEEE Conference on Computer Vision and Pattern
Recognition (CVPR), Long Beach, CA, June 2019. [PDF] [Code]
Yang Feng, Lin Ma, Wei Liu, Jiebo Luo, "Spatio-temporal Video
Re-localization by Warp LSTM," IEEE Conference on Computer
Vision and Pattern Recognition (CVPR), Long Beach, CA,
June 2019. [PDF] [Code]
Wei Xiong, Jiahui Yu, Zhe Lin, Jimei Yang, Xin Lu, Connelly
Barnes, Jiebo Luo, "Foreground-aware Image Inpainting," IEEE
Conference on Computer Vision and Pattern Recognition (CVPR),
Long Beach, CA, June 2019. [Project Page]
Mengshi Qi*, Weijian Li*, Zhengyuan Yang, Yunhong Wang, Jiebo
Luo, "Attentive Relational Networks for Mapping Images to Scene
Graphs," IEEE Conference on Computer Vision and Pattern
Recognition (CVPR), Long Beach, CA, June 2019.
Heliang Zheng, Jianlong Fu, Zheng-Jun Zha, Jiebo Luo, "Looking
for the Devil in the Details: Learning Trilinear Attention
Sampling Network for Fine-grained Image Recognition," IEEE
Conference on Computer Vision and Pattern Recognition (CVPR),
Long Beach, CA, June 2019.
Fuchen Long, Ting Yao, Xinmei Tian, Jiebo Luo, Tao Mei,
"Gaussian Temporal Awareness Networks for Action Localization",
IEEE Conference on Computer Vision and Pattern Recognition
(CVPR), Long Beach, CA, June 2019. (oral presentation)
Wei-An Lin*, Haofu Liao*, Cheng Peng, Xiaohang Sun, Jingdan
Zhang, Jiebo Luo, Rama Chellappa, S. Kevin Zhou, "DuDoNet: Dual
Domain Network for CT Metal Artifact Reduction," IEEE
Conference on Computer Vision and Pattern Recognition (CVPR),
Long Beach, CA, June 2019.
Haofu Liao, Wei-An Lin, Jiarui Zhang, Jingdan Zhang, Jiebo
Luo, S. Kevin Zhou, "Multiview 2D/3D Rigid Registration via a
Point-Of-Interest Network for Tracking and Triangulation," IEEE
Conference on Computer Vision and Pattern Recognition (CVPR),
Long Beach, CA, June 2019.
Jingyuan Chen, Lin Ma, Wei Liu, Jiebo Luo, "Localizing Natural
Language in Videos," The 33rd AAAI Conference on Artificial
Intelligence (AAAI), Honolulu, HI, February 2019.
2018
Qing Li, Jianlong Fu, Dongfei Yu, Tao Mei, Jiebo Luo,
"Tell-and-Answer: Towards Explainable Visual Question Answering
using Attributes and Captions," Conference on Empirical
Methods in Natural Language Processing (EMNLP), Brussels,
Belgium, November 2018. (oral presentation)
Mingkun Yang, Yongchao Xu, Xiang Bai, Jiebo Luo, "Integrating
Scene Text and Visual Appearance for Fine-Grained Image
Classification," IEEE Access, in IEEE Xplore.
Zhengyuan Yang, Yuncheng Li, Jianchao Yang, and Jiebo Luo,
"Action Recognition with Spatio-Temporal Visual Attention on
Skeleton Image Sequences," IEEE Transactions on Circuits and
Systems for Video Technology, in IEEE Xplore.
Wenbin Li, Jing Huo, Yinghuan Shi, Yang Guo, Lei Wang, Jiebo
Luo, "A Joint Local and Global Deep Learning Method for
Caricature Recognition," Asian Conference on Computer Vision
(ACCV), Perth, Australia, December 2018.
Haofu Liao, Gareth Funka-Lea, Yefeng Zheng, Kevin Zhou, Jiebo
Luo, "Face Completion with Semantic Knowledge and Collaborative
Adversarial Learning," Asian Conference on Computer Vision
(ACCV), Perth, Australia, December 2018.
Tianlang Chen, Zhongping Zhang, Quanzeng You, Chen Fang,
Zhaowen Wang, Hailin Jin, Jiebo Luo, "Factual or Emotional:
Stylized Image Captioning with Adaptive Learning and Attention,"
European Conference on Computer Vision (ECCV), Munich,
Germany, September 2018.
Yang Feng, Lin Ma, Wei Liu, Tong Zhang, Jiebo Luo, "Video
Re-localization via Cross Gated Bilinear Matching," European
Conference on Computer Vision (ECCV), Munich, Germany,
September 2018. [PDF][Github]
Qing Li, Qingyi Tao, Shafiq Joty, Jianfei Cai, Jiebo Luo,
"VQA-E: Explaining, Elaborating, and Enhancing Your Answers for
Visual Questions," European Conference on Computer Vision
(ECCV), Munich, Germany, September 2018.
Mengshi Qi, Jie Qin, Annan Li, Yunhong Wang, Jiebo Luo, Luc
Van Gool, "stagNet: An Attentive Semantic RNN for Group Activity
Recognition," European Conference on Computer Vision (ECCV),
Munich, Germany, September 2018.
Fuchen Long, Ting Yao, Tao Mei, Jiebo Luo, "Deep Domain
Adaptation Hashing with Adversarial Learning," ACM SIGIR
Conference on Research and Development in Information
Retrieval (SIGIR), Ann Arbor, MI, July 2018. (Oral
presentation)
Xiaobai Liu, Qian Xu, Jingjie Yang, Jacob Thalman, Shuicheng
Yan, and Jiebo Luo, "Learning Multi-Instance Deep Ranking and
Regression Network for Visual House Appraisal," IEEE
Transactions on Knowledge and Data Engineering (TKDE)
30(8): 1496-1506, 2018.
Zhengyuan Yang, Yixuan Zhang, Jerry Yu, Junjie Cai, Jiebo Luo,
"End-to-end Multi-Modal Multi-Task Vehicle Control for
Self-Driving Cars with Visual Perception," IAPR/IEEE
International Conference on Pattern Recognition (ICPR),
Beijing, China, August 2018. (Best Industrial Related Paper)[PDF][Demo]
Zhengyuan Yang, Yuncheng Li, Jianchao Yang, Jiebo Luo, "Action
Recognition with Visual Attention on Skeleton Images," IAPR/IEEE
International Conference on Pattern Recognition (ICPR),
Beijing, China, August 2018. (Oral presentation)
Zhongping Zhang, Yixuan Zhang, Zheng Zhou, Jiebo Luo,
"Boundary-based Image Forgery Detection by Fast Shallow CNN," IAPR/IEEE
International Conference on Pattern Recognition (ICPR),
Beijing, China, August 2018.
Viet-Duy Nguyen, Minh Tran, Jiebo Luo, "Are French Really That
Different? Recognizing Europeans from Faces Using Data-Driven
Learning," IAPR/IEEE International Conference on Pattern
Recognition (ICPR), Beijing, China, August 2018.
Quanzeng You, Zhengyou Zhang, Jiebo Luo,
"End-to-end Convolutional Semantic Embeddings," IEEE
Conference on Computer Vision and Pattern Recognition (CVPR),
Salt Lake City, UT, June 2018.
Wei Xiong, Wenhan Luo, Lin Ma, Wei Liu,
Jiebo Luo, "Learning to Generate Time-Lapse Videos Using
Multi-Stage Dynamic Generative Adversarial Networks," IEEE
Conference on Computer Vision and Pattern Recognition (CVPR),
Salt Lake City, UT, June 2018.
Danna
Gurari, Qing Li, Abigale Stangl, Anhong Guo, Chi
Lin, Kristen Grauman, Jiebo Luo, Jeffery Bigham, "VizWiz Grand
Challenge: Answering Visual Questions from Blind People," IEEE
Conference on Computer Vision and Pattern Recognition (CVPR),
Salt Lake City, UT, June 2018. (spotlight presentation)
Gui-Song Xia, Xiang Bai,
Jian Ding, Serge Belongie, Jiebo Luo, Mihai Datcu, Marcello
Pelillo, Liangpei Zhang, "DOTA: A Large-scale Dataset for Object
Detection in Aerial Images," IEEE Conference on Computer
Vision and Pattern Recognition (CVPR), Salt Lake City, UT, June 2018.
Xinpeng
Chen, Jingyuan Chen, Lin Ma, Jian Yao, Wei Liu, Jiebo Luo and
Tong Zhang, "Fine-grained Video Attractiveness Prediction Using
Multimodal Deep Learning on a Large Real-world Dataset," The
Web Conference (WWW), Lyon, France, April 2018.
Yu Wang, Haofu Liao, Yang Feng, Xiangyang Xu, Jiebo Luo, "Do
They All Look the Same? Deciphering Chinese, Japanese and
Koreans by Fine-Grained Deep Learning," IEEE International
Conference on Multimedia Information Processing and Retrieval,
Miami, FL, April 2018.
Tianlang Chen, Chenliang Xu, Jiebo Luo, "Improving Text-based
Person Search by Spatial Matching and Adaptive Threshold," Winter
Conference on Computer Vision (WACV), Lake Tahoe, NV,
March 2018.
Xitong Yang, Jiebo Luo, "Towards Perceptual Image Dehazing by
Physics-based Disentanglement and Adversarial Training", The 32nd AAAI Conference on
Artificial Intelligence (AAAI), New Orleans, LA,
February 2018.
Jingyi Hou, Xinxiao Wu, Jiebo Luo, "Unsupervised Deep Learning
of Mid-Level Video Representation for Action Recognition," The 32nd AAAI Conference on
Artificial Intelligence (AAAI), New Orleans, LA,
February 2018.
Yu Wang, Haofu Liao, Yang Feng, Xiangyang Xu, Jiebo Luo, "Do
They All Look the Same? Deciphering Chinese, Japanese and
Koreans by Fine-Grained Deep Learning," IEEE International
Conference on Multimedia Information Processing and Retrieval,
Miami, FL, April 2018.
Yang Cong, Ji Liu, Jiebo Luo, "User Attribute Discovery with
Missing Labels," Pattern
Recognition 73: 33-46, 2018.
2017
Heliang Zheng, Jianlong Fu, Tao Mei, and Jiebo Luo, "Learning
Multi-Attention Convolutional Neural Network for Fine-Grained
Image Recognition," International
Conference on Computer Vision (ICCV), Venice, Italy,
October 2017. (oral presentation)
Xiangyang Xu, Yuncheng Li, Gangshan Wu and Jiebo Luo,
"Multi-modal Deep Feature Learning for RGB-D Object Detection,"
Pattern Recognition 72:
300-313, 2017.
Zhengyuan Yang, Wendi Cross, Jiebo Luo, "Personalized pose
estimation for body language understanding," International Conference on Image
Processing (ICIP), Beijing, China, September 2017.
(oral presentation)
Honglin Zheng, Tianlang Chen, Quanzeng You, Jiebo Luo, "When
Saliency Meets Sentiment: Understanding How Image Content
Invokes Emotion and Sentiment," International Conference on Image Processing
(ICIP), Beijing, China, September 2017. (oral presentation)
Lifang Wu, Shuang Liu, Meng Jian, Jiebo Luo, Xiuzhen Zhang,
Mingchao Qi, "Reducing Noisy Labels on Weakly Labeled Data for
Visual Sentiment Analysis," International
Conference on Image Processing (ICIP), Beijing, China,
September 2017.
Yuncheng Li, Liangliang Cao, Jiebo Luo, "Mining Fashion Outfit
Composition Using an End-to-End Deep Learning Approach on Set
Data," IEEE Trans. on
Multimedia, 19(8): 1946-1955(2017).
Yanhao Zhang, Lei Qin, Rongrong Ji, Qingming Huang, Jiebo Luo,
"Exploring Coherent Motion Patterns via Structured Trajectory
Learning for Crowd Mood Modeling," IEEE Transactions on Circuits and Systems for Video
Technology, 27(3): 635-648 (2017).
Fei Wu, Zhuhao Wang, Weiming Lu, Xi Li, Yi Yang, Jiebo Luo,
Yueting Zhuang, "Regularized Deep Belief Network for Image
Attribute Detection," IEEE
Transactions on Circuits and Systems for Video Technology,
27(7): 1464-1477, 2017.
Qing Li, Zhaofan Qiu, Ting Yao, Tao Mei, Yong Rui, Jiebo Luo,
"Learning hierarchical video representation for action
recognition," International
Journal of Multimedia Information Retrieval, 6(1):
85-98, 2017.
Quanzeng You, Liangliang Cao, Jiebo Luo, "Image Based
Appraisal of Real Estate Properties," IEEE Transactions on. Multimedia, in press.
Xitong Yang, Sriganesh Madhvanath, Edgar A. Bernal,
Palghat Ramesh, Radha Chitta, Jiebo Luo, "Deep Multimodal
Representation Learning from Temporal Data," IEEE Conference on Computer Vision
and Pattern Recognition (CVPR), Hawaii, July
2017.
Marko Stamenovic, Jiebo Luo, "Machine Identification of High
Impact Research through Text and Image Analysis," IEEE Big Multimedia Conference,
Laguna Hills, CA, April 2017.
Quanzeng You, Hailin Jin, Jiebo Luo, "Visual Sentiment
Analysis by Attending on Local Image Regions", The 31st AAAI Conference on
Artificial Intelligence (AAAI), San Francisco, CA,
February 2017.
Songhe Feng, Congyan Lang, Jiashi Feng and Jiebo Luo, "Human
Facial Age Estimation by Cost-Sensitive Label Ranking and Trace
Norm Regularization," IEEE
Trans. on Multimedia, 19(1): 136-148, 2017.
Yang Cong, Ji Liu, Gan Sun, Quanzheng You, Yuncheng Li and
Jiebo Luo, "Adaptive Greedy Dictionary Selection for Web Media
Summarization," IEEE Trans.
on Image Processing, 26(1): 185-195, 2017.
2016
Yang Feng, Yuncheng Li, Jiebo Luo, "Learning Effective Gait
Features Using LSTM", International
Conference on Pattern Recognition (ICPR), Cancun,
Mexico, December 2016.
Iftekhar Naim, Abdullah Al Mamun, Young Chol Song, Jiebo Luo,
Henry Kautz, Daniel Gildea, "Aligning Movies with Scripts by
Exploiting Temporal Ordering Constraints", International Conference on
Pattern Recognition (ICPR), Cancun, Mexico, December
2016.
Quanzeng You, Liangliang Cao, Hailin Jin, Jiebo Luo, "Robust
Visual-Textual Sentiment Analysis: When Attention meets
Tree-structured Recursive Neural Networks", ACM Multimedia Conference,
Amsterdam, The Netherlands, October 2016.
Qing Li, Zhaofan Qiu, Ting Yao, Tao Mei, Yong Rui and Jiebo
Luo, "Action Recognition by Learning Deep Multi-Granular
Spatio-Temporal Video Representation," ACM/IAPR International Conference on Multimedia
Retrieval (ICMR), New York City, June 2016. (Long
paper, Best Paper Candidate)
Quanzeng You, Hailin Jin, Zhaowen Wang, Chen Fang, Jiebo Luo,
"Image Captioning with Semantic Attention," IEEE Conference on Computer Vision
and Pattern Recognition (CVPR), Las Vegas, NV, June
2016. (spotlight presentation)
Yuncheng Li, Yale Song, Liangliang Cao, Joel Tetreault,
Larry Goldberg, Jiebo Luo, "TGIF: A New Dataset and
Benchmark on Animated GIF Description," IEEE Conference on Computer Vision
and Pattern Recognition (CVPR), Las Vegas, NV, June
2016. (spotlight presentation)
Tianliang Liu, Xincheng Wang, Xiubin Dai, Jiebo Luo, "Deep
Recursive and Hierarchical Conditional Random Fields for Human
Action Recognition," IEEE
Winter Conference on Applications of Computer Vision
(WACV), Lake Placid, NY, March 2016.
Liang Lin, Keze Wang, Wangmeng Zuo, Meng Wang, Lei Zhang,
Jiebo Luo, "Deep Reconfigurable Models with Radius-Margin Bound
for 3D Human Activity Recognition," International Journal of Computer Vision,
available online.
Xinyang Cai, Wengang Zhou, Houqiang Li, Jiebo Luo, Lei Wu,
"Effective Kinetic Skeleton Representation for Low Latency Human
Action Recognition," IEEE
Trans. Multimedia, available online.
Quanzeng You, Hailin Jin, Jianchao Yang, Jiebo Luo,
"Cross-modality Consistent Regression for Joint Visual-Textual
Sentiment Analysis," ACM
International Conference on Web Search and Data Ming (WSDM),
San Francisco, CA, February 2016. [PrePrintPDF]
Quanzeng You, Hailin Jin, Jianchao Yang, Jiebo Luo, "Building
a Large Scale Dataset for Image Emotion Recognition: The Fine
Print and The Benchmark," The
30th AAAI Conference on Artificial Intelligence (AAAI),
Phoenix, AZ, January 2016. [PDF][Dataset Page]
2015
Yuncheng Li, Xitong Yang, Jiebo Luo, "Semantic Video Entity
Linking based on Visual Content and Metadata," International Conference on
Computer Vision (ICCV), Santiago, Chile, December 2015.
[PrePrintPDF]
Yuncheng Li, Jifei Huang, Jiebo Luo, "Using User Generated
Online Photos to Estimate and Monitor Air Pollution in Major
Cities," ACM International
Conference on Internet Multimedia Computing and Service
(ICIMCS), August 2015. (Best Paper) [PDF] [Project
Page]
Wu Liu, Tao Mei, Yongdong Zhang, Cherry Che and Jiebo Luo,
"Multi-Task Deep Visual-Semantic Embedding for Video Thumbnail
Selection," IEEE
International Conference on Computer Vision and Pattern
Recognition (CVPR), Boston, MA, June 2015.
Wanying Ding, Junhuan Zhu, Lifan Guo, Xiaohua Hu, Jiebo Luo,
Haohong Wang, "Jointly Image Topic and Emotion Detection using
Multi-Modal Hierarchical Latent Dirichlet Allocation," Journal of Multimedia Information
System, 2015.
Yang Cong, Ji Liu, Jiebo Luo, "Speeded up Low Rank Online
Metric Learning for Object Tracking," IEEE Transactions on Circuits and Systems for Video
Technology, 2015.
2010-2014
Young Chol Song, Henry Kautz, James Allen, Mary
Swift, Yuncheng Li, Jiebo Luo, "A Markov Logic Framework for
Recognizing Complex Events from Multimodal Data," ACM
International Conference on Multimodal Interaction (ICMI),
Sidney, Australia, December 2013.
Yao Zhou and Jiebo Luo, "A Practical Method for
Counting Arbitrary Target Objects in an Arbitrary Scene," IEEE
ICME, July 2013.
Congyan Lang, Jiashi Feng, Guangcan Liu, Jinghui Tang,
Shuicheng Yan and Jiebo Luo, "Improving Bottom-up Saliency
Detection by Looking into Neighbors," IEEE Transactions on
Circuits and Systems for Video Technology, 23(6):
1016-1028, June 2013.
Minwoo Park, Jiebo Luo, Andrew Gallagher, Majid Rabbani,
"Learning to Produce 3D Media from a Captured 2D Video," IEEE
Transactions on Multimedia, 15(7): 1569-1578, 2013.
Hua Wang, Dhiraj Joshi, Jiebo Luo, and Heng
Huang, "Simultaneous Image Annotation and Geo-Tag Prediction
via Correlation Guided Structured Multi-Task Learning," IEEE
Symposium on Multimedia (ISM), December 2012.
Jianchao Yang, Jiebo Luo, Jie Yu, Thomas. Huang, "Photo
Stream Alignment and Summarization for Collaborative Photo
Collection and Sharing," IEEE Transactions on Multimedia,
14(6): 1642-1651, December 2012.
Youjie Zhou, Jiebo Luo, " Geo-Location Inference on News
Articles via Multimodal pLSA," ACM Multimedia Conference,
Nara, Japan, October 2012.
Xiaobin Xu, Tao Mei, Wenjun Zeng, Nenghai Yu, Jiebo Luo,
"AMIGO: Accurate Mobile Image GeOtagging," ACM
International Conference on Internet Multimedia Computing and
Services, Wuhan, China, September 2012. (Best
Paper)
Lin Chen, Dong Xu, Ivor Tsang, and Jiebo Luo for the paper
entitled, "Tag-Based Image Retrieval Improved by Augmented
Features and Group-Based Refinement", IEEE Transactions on Multimedia, Volume 14,
Number 4, August 2012 (2014 IEEE Multimedia Prize Paper
Award).
Minwoo Park, Jiebo Luo, Andrew Gallagher, "Towards Assessing
and Improving the Quality of Stereo Images," Special Issue
on Emerging Techniques in 3D,IEEE Journal of
Selected Topics in Signal Processing, 6(5): 460 - 470,
2012.
Siyu Xia, Ming Shao, Jiebo Luo, and Yun Fu, "Understanding
Kin Relationships in a Photo," Special Issue on Learning
Semantics from Multimedia Web Resources, IEEE Transactions
on Multimedia, 14(4): 1046-1056, 2012.
Lin Chen, Dong Xu, Ivor W. Tsang, Jiebo Luo, "Tag-based Image
Retrieval Improved by SVM with Augmented Features and
Group-based Refinement," Special Issue on Learning
Semantics from Multimedia Web Resources, IEEE Transactions
on Multimedia, 14(4): 1057-1067, 2012.
Cong Yang, Junsong Yuan, Jiebo Luo, "Towards Scalable
Summarization of Consumer Videos via Sparse Dictionary
Selection," Special Issue on Object and Event
Classification in Large-Scale Video Collections, IEEE
Transactions on Multimedia, 14(1): 66-75, February 2012.
Dhiraj Joshi, Ritendra Datta, Elena Fedorovskaya, Jia Li,
James Z. Wang, Jiebo Luo, "Computational inference of
aesthetics, mood, and emotion in images," IEEE Signal
Processing Magazine, 28(5): 94-115, September 2011.
Yiming Liu, Dong Xu, Ivor Tsang, Jiebo Luo, "Textual query of
personal photos facilitated by large-scale web data," IEEE
Transactions on Pattern Analysis and Machine Intelligence,
33(5): 1022-1036, May 2011.
Minwoo Park, Jiebo Luo, Robert Collions, Yanxi Liu, "Beyond
GPS: Determining the viewing direction of a geotagged image," ACM
Multimedia Conference, Firenze, Italy, October 2010.
Xiaobai Liu, Shuicheng Yan, Jiebo Luo, Jinhui
Tang, ZhongYang Huang, Hai Jin, "Nonparametric Label-to-Region by Search,"
CVPR 2010.
Jingen Liu, Jiebo Luo, Mubarak Shah, "Recognizing Realistic
Actions from Videos in the Wild," IEEE Conference on
Computer Vision and Pattern Recognition, Miami, FL, June
2009. (Oral Presentation) [Project
Page]
machine learning
2021
Guo-Jun Qi, Jiebo Luo, "Small Data Challenges in Big Data Era:
A Survey of Recent Progress on Unsupervised and Semi-Supervised
Methods," IEEE Transactions on Pattern Analysis and Machine
Intelligence, in press.
Xiao Wang, Guo-Jun Qi, Jiebo Luo, "EnAET: A Self-Trained
Framework for Semi-Supervised and Supervised Learning with
Ensemble Transformation," IEEE Transactions on Image
Processing, 30: 1639-1647, 2021.
Wei Zhu, Wenbin Li, Haofu Liao, and Jiebo Luo, ''Temperature
Network for Few-shot Learning with Distribution-aware
Large-margin Metric,'' Pattern Recognition, in press.
2020
Mengshi Qi, Jie Qin, Xiantong Zhen, Di Huang, Yi Yang, Jiebo
Luo, "Few-Shot Ensemble Learning for Video Classification with
SlowFast Memory Networks," ACM Multimedia Conference,
Seattle, WA, October 2020.
Wenbin Li, Lei Wang, Jing Huo. Yinghuan Shi, Yang Gao, Jiebo
Luo, "Asymmetric Distribution Measure for Few-shot Learning," International
Joint Conference on Artificial Intelligence (IJCAI),
Yokohama, Japan, July 2020.
Zhongjie Yu, Lin Chen, Zhongwei Cheng, Jiebo Luo, "TransMatch:
A Transfer-Learning Scheme for Semi-Supervised Few-Shot
Learning," IEEE/CVF Conferences on Computer Vision and
Pattern Recognition (CVPR), Seattle, WA, June 2020.
2019
Yi Wang, Nan Xue, Xin Fan, Jiebo Luo, Risheng Liu, Haojie Li,
Bin Chen, Zhongxun Luo, "Novelty Detection and Online Learning
for Chunk Data Streams," IEEE Transactions on Pattern
Analysis and Machine Intelligence, in press.
Wenbin Li, Lei Wang, Jinglin Xu, Jing Huo, Yang Gao and Jiebo
Luo, "Revisiting Local Descriptor based Image-to-Class Measure
for Few-shot Learning," IEEE Conference on Computer Vision
and Pattern Recognition (CVPR), Long Beach, CA, June 2019.
[PDF][Github]
Wenbin Li, Jing Huo, Yinghuan Shi, Yang Guo, Lei Wang, Jiebo
Luo, "Distribution Consistency based Covariance Metric Networks
for Few Shot Learning," The 33rd AAAI Conference on
Artificial Intelligence (AAAI), Honolulu, HI, February
2019. (oral presentation) [PDF][Github]
Liheng Zhang, Guo-Jun Qi, Liqiang Wang, Jiebo Luo, "AET vs.
AED: Unsupervised Representation Learning by Auto-Encoding
Transformations rather than Data," IEEE Conference on
Computer Vision and Pattern Recognition (CVPR),
Long Beach, CA, June 2019. (oral presentation)
2018
Yi Wang, Nan Xue, Xin Fan, Jiebo Luo, Risheng Liu, Haojie Li,
Bin Chen, Zhongxun Luo, "Fast factorization-free Kernel Learning
for Unlabeled Chunk Data Streams," International Joint
Conference on Artificial Intelligence (IJCAI), Stockholm,
Sweden, July 2018.
Xiaotong Zhang, Xianchao Zhang, Han Liu, Jiebo Luo,
"Multi-Task Clustering with Model Relation Learning," International
Joint Conference on Artificial Intelligence (IJCAI),
Stockholm, Sweden, July 2018.
Yang Cong, Ji Liu, Jiebo Luo, "Sparse Low-rank Online
Similarity Learning," IEEE Transactions on Cybernetics,
73: 33-46, 2018.
Yang Cong, Ji Liu, Jiebo Luo, "Online Similarity Learning for
Big Data with Overfitting," IEEE Transactions on Big Data,
4(1): 78-89, 2018.
2017
Jianbo Yuan, Han Guo, Zhiwei Jin, and Jiebo Luo, "One-shot
Learning for Fine-grained Relation Extraction via Convolutional
Siamese Neural Network," IEEE Big Data Conference,
Boston, MA, December 2017.
Yuncheng Li, Jianchao Yang, Yale Song, Liangliang Cao, Jia Li
and Jiebo Luo, "Learning from Noisy Labels with Distillation," International Conference on
Computer Vision (ICCV), Venice, Italy, October 2017.
Guo-Jun Qi, Jiliang Tang, Jingdong Wang and Jiebo Luo,
"Mixture Factorized Ornstein-Uhlenbeck Processes for Time-Series
Forecasting," ACM SIGKDD
Conference on Knowledge Discovery and Data Mining (KDD),
Nova Scotia, Canada, August 2017.
Yuncheng Li, Yale Song, Jiebo Luo, "Improving Pairwise Ranking
for Multi-label Image Classification," IEEE Conference on Computer Vision and Pattern
Recognition (CVPR), Hawaii, July 2017.
Yi Wang, Xin Fan, Maomao Min, Jiebo Luo, "Fast Online
Incremental Learning on Mixture Streaming Data," The 31st AAAI Conference on
Artificial Intelligence (AAAI), San Francisco, CA,
February 2017.
2016
Xianchao Zhang, Haixing Li, Wenxin Liang, Jiebo Luo,
"Multi-Type Co-clustering of General Heterogeneous Information
Networks," IEEE International
Conference on Data Mining (ICDM), December 2016.
Young Chol Song, Iftekhar Naim, Abdullah Al Mamun, Kaustubh
Kulkarni, Parag Singla, Jiebo Luo, Daniel Gildea and Henry
Kautz, "Unsupervised Alignment of Actions in Video with Text
Descriptions," AAAI
International Joint Conference on Artificial Intelligence
(IJCAI), New York City, July 2016.
2015
Iftekhar Naim, Young Chol Song, Henry Kautz, Jiebo Luo,
Qiguang Liu, Daniel Gildea, and Liang Huang, "Discriminative
Unsupervised Alignment of Natural Language Instructions with
Corresponding Video Segments," North American Chapter of the Association for
Computational Linguistics (NAACL), 2015.
Quanzeng You, Jiebo Luo, Hailin Jin, and Jianchao Yang,
"Robust Image Sentiment Analysis using Progressively Trained and
Domain Transferred Deep Networks," The Twenty-Ninth AAAI Conference on Artificial
Intelligence (AAAI), Austin, TX, January 25-30, 2015. [PDF]
[Project
Page]
2010-2014
Iftekhar Naim, Young Song, Daniel Gildea, Qiguang Liu, Henry
Kautz and Jiebo Luo, "Unsupervised Alignment of Natural Language
Instructions with Video Segments," the Twenty-Eighth AAAI Conference on Artificial
Intelligence (AAAI), Quebec City, Canada, July 27-31,
2014.
Yang Cong, Ji Liu, Junsong Yuan, Jiebo Luo, "Self-Supervised
Online Metric Learning With Low Rank Constraint for Scene
Categorization." IEEE
Transactions on Image Processing, 22(8): 3179-3191,
2013.
Liangliang Cao, Xin
Jin, Zhijun Yin, Andrey Del Pozo,
Jiebo Luo,Jiawei
Han, Thomas S.
Huang, "RankCompete:
Simultaneous ranking and clustering of information networks,"
Neurocomputing, 95: 98-104, 2012.
Yahong Han, Fei Wu, Qi Tian, Yueting Zhuang, Jiebo Luo,
"Correlated Attribute Transfer with Multi-task Graph-Guided
Fusion," ACM Multimedia Conference, Nara, Japan,
October 2012. (Long paper)
Lixin Duan, Dong Xu, Ivor Tsang, Jiebo Luo, "Visual Event
Recognition in Videos by Learning from Web Data," IEEE
Conference on Computer Vision and Pattern Recognition,
San Francisco, CA, June 2010. (Best Student Paper)
(Project
Page)
web and social media data mining
2020
Li Sun*, Haoqi Zhang*, Songyang Zhang, and Jiebo Luo,
"Content-based Analysis of the Cultural Differences between
TikTok and Douyin," Special Session on Intelligent Data Mining,
IEEE International Conference on Big Data, Atlanta, GA,
December 2020.
Neil Yeung, Jonathan Lai, and Jiebo Luo, "Face Off: Polarized
Public Opinions on Personal Face Mask Usage during the COVID-19
Pandemic," Special Session on Intelligent Data Mining, IEEE
International Conference on Big Data, Atlanta, GA,
December 2020.
Wei Wu*, Jinlong Ruan*, and Jiebo Luo, "Stock Price Prediction
Under Anomalous Circumstances," Special Session on Intelligent
Data Mining, IEEE International Conference on Big Data,
Atlanta, GA, December 2020.
Shuaidong Pan*, Faner Lin*, and Jiebo Luo, "Do Sports and
Politics Mix? Cross-Analysis of Fan Bases of Major League Sports
and Presidential Candidates," IEEE/ACM International
Conference on Advances in Social Networks Analysis and Mining
(ASONAM), 2020.
Viet Duong, Phu Pham, Tongyu Yang, Yu Wang and Jiebo Luo, "The
Ivory Tower Lost: How College Students Respond Differently than
the General Public to the COVID-19 Pandemic," IEEE/ACM
International Conference on Advances in Social Networks
Analysis and Mining (ASONAM), 2020.
Luoying Yang, Zhou Xu, Jiebo Luo, "Measuring Female
Representation and Impact in Films over Time," ACM
Transactions on Data Science, in press.
Hanjia Lyu, Long Chen, Yu Wang, Jiebo Luo, "Sense and
Sensibility: Characterizing Social Media Users Regarding the Use
of Controversial Terms for COVID-19," IEEE Transactions on
Big Data, available online.
Xinyi Lu, Long Chen, Jianbo Yuan, Joyce Luo, Zidian Xie, Jiebo
Luo, Dongmei Li, "E-cigarette Flavors and Their Perceptions on
Social Media: Observational Study," Journal of Medical
Internet Research, Vol 22, No 6, 2020.
2019
Shuaidong Pan, Tianran Hu, Shujing Sun, Jianbo Yuan, and Jiebo
Luo, "Help Oneself in Helping the Others: The Ecology of Online
Support Groups," IEEE International Conference on Big Data,
Los Angeles, CA, December 2019.
Yingtong Dou, Weijian Li, Zhirong Liu, Zhenhua Dong, Jiebo Luo
and Philip Yu, "Uncovering Download Fraud Activities in Mobile
App Market," IEEE/ACM International Conference on Advances
in Social Networks Analysis and Mining (ASONAM),
Vancouver, Canada, August 2019.
Yuan Liu, Zhongwei Cheng, Jie Liu, Bourhan Yassin, Zhe Nan,
Jiebo Luo, "AI for Earth: Rainforest Conservation by Acoustic
Surveillance," Workshop on Data Mining and AI for Conservation,
ACM SIGKDD Conference on Knowledge Discovery and Data Mining
(KDD), Anchorage, AK, August 2019.
Tianran Hu, Yinglong Xia, Jiebo Luo, "To Return or to Explore:
Modelling Human Mobility and Dynamics in Cyberspace," The
Web Conference (formerly WWW), San Francisco, CA, May
2019.
2018
Zhongping Zhang, Tianlang Chen, Zheng Zhou, Jiaxin Li, and
Jiebo Luo, "How to Become Instagram Famous: Post Popularity
Prediction with Dual-Attention," IEEE International
Conference on Big Data, Seattle, WA, December 2018.
Tianlang Chen, Yuxiao Chen, Han Guo, and Jiebo Luo, "You Type
a Few Words and We Do the Rest: Image Recommendation for Social
Multimedia Posts," IEEE International Conference on Big Data,
Seattle, WA, 2018.
Benjamin Kane and Jiebo Luo, "Do the Communities We Choose
Shape our Political Beliefs? A Study of the Politicization of
Topics in Online Social Groups," International Workshop on Big
Social Media Data Management and Analysis, IEEE
International Conference on Big Data, Seattle, WA,
December 2018.
Yuxiao Chen*, Jianbo Yuan*, Quanzeng You, Jiebo Luo, "Twitter
Sentiment Analysis via Bi-sense Emoji Embedding and
Attention-based LSTM," ACM Multimedia Conference, Seoul,
Korea, October 2018.
Xuefeng Peng, Li-Kai Chi and Jiebo Luo, "The Effect of Pets on
Happiness: A Large-scale Multi-Factor Analysis using Social
Multimedia," ACM Transactions on Intelligent Systems and
Technology (TIST) 9(5), 2018.
Tianran Hu, Jiebo Luo and Wei Liu, "Life in the 'Matrix':
Human Mobility Patterns in the Cyber Space," AAAI
International Conference on Web and Social Media (ICWSM),
Stanford, CA, June 2018. (Full Paper Acceptance Rate 16%)
Weijian Li*, Yuxiao Chen*, Tianran Hu, and Jiebo Luo, "Mining
the Relationship between Emoji Usage Patterns and Personality,"
AAAI International Conference on Web and Social Media (ICWSM),
Stanford, CA, June 2018.
Tianlang Chen, Yuxiao Chen, Han Guo and Jiebo Luo, "When
E-commerce Meets Social Media: Identifying Business on WeChat
Moment Using Bilateral-Attention LSTM," The Web Conference
(WWW), Lyon, France, April 2018.
Peijun Zhao, Jia Jia, Lexing Xie, Yongsheng An and Jiebo Luo,
"Analyzing and Predicting Emoji Usages in Social Media," The
Web Conference (WWW), Lyon, France, April 2018.
2017
Yiming Pan, Xuefeng Peng, Tianran Hu, and Jiebo Luo,
"Understanding What affects Career Progression Using LinkedIn
and Twitter Data," Special Session on Intelligent Data Mining, IEEE
Big Data Conference, Boston, MA, December 2017.
Xuefeng Peng, Yiming Pan, and Jiebo Luo, "Predicting High Taxi
Demand Regions Using Social Media Check-ins," Special Session on
Intelligent Data Mining, IEEE Big Data Conference,
Boston, MA, December 2017.
Zhiwei Jin, Juan Cao, Han Guo, Yongdong Zhang, Yu Wang and
Jiebo Luo, "Multimodal Fusion with Recurrent Neural Networks for
Rumor Detection on Microblogs," ACM Multimedia Conference, Mountain View, CA,
October 2017.
Yu Wang, Jiebo Luo and Xiyang Zhang, "When Follow is Just One
Click Away: Understanding Twitter Follow Behavior in the 2016
U.S. Presidential Election," International
Conference on Social Informatics (SocInfo), Oxford,
England, Sept. 2017.
Yu Wang, Yang Feng and Jiebo Luo, "How Polarized Have We
Become? A Multimodal Classification of Trump Followers and
Clinton Followers," International
Conference on Social Informatics (SocInfo), Oxford,
England, Sept. 2017.
Zhiwei Jin, Juan Cao, Han Guo, Yongdong Zhang, Yu Wang and
Jiebo Luo, "Detection and Analysis of 2016 US Presidential
Election Related Rumors on Twitter," International Conference on Social Computing,
Behavioral-Cultural Modeling & Prediction and Behavior
Representation in Modeling and Simulation (SBP-BRiMS),
Washington, DC, July 2017.
Yu Wang and Jiebo Luo, "Inferring Follower Preferences with
Sparse Learning," International
Conference on Social Computing, Behavioral-Cultural Modeling
& Prediction and Behavior Representation in Modeling and
Simulation (SBP-BRiMS), Washington, DC, July 2017.
Yu Wang and Jiebo Luo, "Gender Politics in the 2016
Presidential Election: A Computer Vision Approach," International Conference on Social
Computing, Behavioral-Cultural Modeling & Prediction and
Behavior Representation in Modeling and Simulation
(SBP-BRiMS), July 2017.
Quanzeng You, Jungseock Joo, Dario Garcia Garcia, Jiebo Luo,
"Cultural Dynamics and Trends in Facebook Photographs," AAAI International Conference on
Web and Social Media (ICWSM), Montreal, Canada, May
2017.
Tianran Hu, Han Guo, Hao Sun, Thuy-vy Thi Nguyen, Jiebo Luo,
"Spice up Your Chat: The Intentions and Sentiment Effects of
Using Emojis," AAAI
International Conference on Web and Social Media (ICWSM),
Montreal, Canada, May 2017.
Tianran Hu, Ruihua Song, Xing Xie, Maya Abtahian, Philip Ding
and Jiebo Luo, "A World of Difference: Divergent Word
Interpretations among People," AAAI International Conference on Web and Social Media
(ICWSM), Montreal, Canada, May 2017.
Rijul Magu, Kshitij Joshi and Jiebo Luo, "Decoding the Hate
Code on Social Media," AAAI
International Conference on Web and Social Media (ICWSM),
Montreal, Canada, May 2017.
Yu Wang and Jiebo Luo, "Tactics and Tallies: A Study of the
2016 U.S. Presidential Campaign Using Twitter 'Likes'," AAAI International Conference on
Web and Social Media (ICWSM), Second International
Workshop on News and Public Opinion, Montreal, Canada, May 2017.
Kuan-Ting Chen and Jiebo Luo, "When Fashion Meets Big Data:
Discriminative Mining of Best Selling Clothing Features," World Wide Web Conference
(WWW), Perth, Australia, April 2017.
Tianlang Chen, Yuxiao Chen and Jiebo Luo, "A Selfie is Worth a
Thousand Words: Mining Personal Patterns behind User
Selfie-posting Behaviours," World
Wide Web Conference (WWW), Perth, Australia, April
2017.
Tianran Hu, Eric Biglow, Henry Kautz, and Jiebo Luo, "Tales of
Two Cities: Using Social Media to Understand Idiosyncratic
Lifestyles in Distinctive Metropolitan Areas," Special Issue on
Big Media Data: Understanding, Search, and Mining, IEEE Transactions on Big Data,
3(1): 55-66, 2017.
2016
Yiheng Zhou, Numair Sani, and Jiebo Luo, "Fine-grained Mining
of Illicit Drug Use Patterns Using Social Multimedia Data from
Instagram," Special Session on Intelligent Data Mining," IEEE International Conference on
Big Data (Big Data), Washington, DC, December 2016.
Jianbo Yuan, Walid Shalaby, Mohammed Korayem, David Lin,
Khalifeh AlJadda and Jiebo Luo, "Solving Cold Start Problem in
Large-scale Recommendation Engines: A Deep Learning Approach," IEEE International Conference on
Big Data (Big Data), 2016.
Yuchen Wu, Jianbo Yuan, Quanzeng You, and Jiebo Luo, "The
Effect of Pets on Happiness: A Data-Driven Approach via
Large-Scale Social Media," Special Session on Intelligent Data
Mining, IEEE
International Conference on Big Data (Big Data),
Washington, DC, December 2016.
Haofu Liao, Yuncheng Li, Tianran Hu, and Jiebo Luo, "Inferring
Restaurant Styles by Mining Crowd Sourced Photos from
User-Review Websites," IEEE
International Conference on Big Data (Big Data), Washington,
DC, December 2016.
Yu Wang, Yang Feng, Jiebo Luo, "Pricing the Woman Card: Gender
Politics in 2016 US Presidential Election", Workshop on Applications of Big
Data in Computational Social Science, IEEE International Conference on
Big Data (Big Data),
Washington, DC, December 2016.
Yu Wang, Yang Feng, Xiyang Zhang, and Jiebo Luo, "Inferring
Voter Preferences behind Brexit," Workshop on Application of Big Data for Computational
Social Science, IEEE
International Conference on Big Data (Big Data),
Washington, DC, December 2016.
Yang Feng, Jiebo Luo, "When Do Luxury Cars Hit Road? Findings
by A Big Data Approach", Workshop
on Applications of Big Data in Computational Social
Science, IEEE
International Conference on Big Data (Big Data),
Washington, DC, December 2016.
Yu Wang, Yang Feng, Jiebo Luo, Xiyang Zhang, "Voting with
Feet: Who are Leaving Hillary Clinton and Donald Trump?" IEEE International Symposium on
Multimedia, San Jose, CA, December 2016. (Invited
Paper)
Tianran Hu, Ruihua Song, Xing Xie, Jiebo Luo, "Mining Shopping
Patterns for Divergent Urban Regions by Incorporating Mobility
Data", ACM International
Conference on Information and Knowledge Management (CIKM),
Indianapolis, IN, October 2016.
Kelly He, Lee Murphy, and Jiebo Luo, "Using Social Media to
Promote STEM Education: Matching College Students with Role
Models", European Conference
on Machine Learning and Principles and Practice of Knowledge
Discovery (ECML/PKDD), Riva del Garda, Italy,
September 2016. [arXiv]
Zhishen Pan, Kevin Chi, Timothy Dye, Jiebo Luo, "Towards
Understanding How News Coverage Affect Public Perception During
Epidemic Outbreaks",
International Conference on Social Computing,
Behavioral-Cultural Modeling & Prediction and Behavior
Representation in Modeling and Simulation (SBP-BRiMS),
Washington DC, June 2016.
Yiheng Zhou, Numair Sani, Jiebo Luo, "Understanding Illicit
Drug Use Behaviors by Mining Instagram," International Conference on Social
Computing, Behavioral-Cultural Modeling & Prediction and
Behavior Representation in Modeling and Simulation (SBP-BRiMS),
Washington DC, June 2016. [arXiv]
Tianran Hu, Haoyuan Xiao, Jiebo Luo, Thuy-vy Thi Nguyen,
"What the Language You Tweet Says About Your Occupation," AAAI International Conference on
Weblogs and Social Media (ICWSM), Cologne, Germany, May
2016.
Yu Wang, Yuncheng Li, Jiebo Luo, "Deciphering the 2016 U.S.
Presidential Campaign in the Twitter Sphere: A Comparison of the
Trumpists and Clintonists," AAAI
International Conference on Weblogs and Social Media (ICWSM),
Cologne, Germany, May 2016. [arXiv]
Yu Wang, Jiebo Luo, Richard G. Niemi, Yuncheng Li, Tianran Hu,
"Catching Fire via 'Likes': Inferring Topic Preferences of Trump
Followers on Twitter," AAAI
International Conference on Weblogs and Social Media (ICWSM),
Cologne, Germany, May 2016. [arXiv]
Nabil Hossain, Tianran Hu, Roghayeh Feizi, Ann Marie White,
Jiebo Luo, Henry Kautz, "Inferring Fine-grained Details on User
Activities and Home Location from Social Media: Detecting
Drinking-While-Tweeting Patterns in Communities," AAAI International Conference on
Weblogs and Social Media (ICWSM), Cologne, Germany, May
2016. [arXiv]
Yu Wang, Yuncheng Li, Richard G. Niemi, Jiebo Luo, "To Follow
or Not to Follow: Analyzing the Growth Patterns of the Trumpists
on Twitter," AAAI
International Conference on Weblogs and Social Media (ICWSM),
Workshop on Social Media in the Newsroom, Cologne, Germany, May
2016.
Zhiwei Jin, Juan Cao, Yongdong Zhang, Jiebo Luo, "News
Verification by Exploiting Conflicting Social Viewpoints in
Microblogs," The 30th AAAI
Conference on Artificial Intelligence (AAAI), Phoenix,
AZ, January 2016. [PDF]
2015
Quanzeng You, Sumit Bhatia, Jiebo Luo, "A Picture Tells a
Thousand Words About You! User Interest Profiling from
User Generated Visual Content," Signal
Processing, Special Issues on Big Data Meets Multimedia
Analytics, December 2015. [PDF]
Quanzeng You, Liangliang Cao, Jiebo Luo, "A Multifaceted
Social Multimedia-based Approach to Prediction of Elections,", IEEE Transactions on
Multimedia, to appear, 2015. [PrePrintPDF]
Tianran Hu, Adam Sadilek, Henry Kautz, and Jiebo Luo, "Home
Location Inference from Sparse and Noisy Data: Models and
Applications," IEEE
International Conference on Data Mining (ICDM), Workshop on
Social Multimedia Data Mining, Atlantic City, December
2015.
Yu Wang, Jianbo Yuan, and Jiebo Luo, "To Love or to Loathe:
How is the World Reacting to China's Rise?" IEEE International Conference on
Data Mining (ICDM), Workshop on Big Media Data: Understanding,
Search, and Mining, Atlantic City, December 2015. [PrePrintPDF]
Ran Pang, Agustin Baretto, Henry Kautz, and Jiebo Luo,
"Monitoring Adolescent Alcohol Use via Multimodal Data Analysis
in Social Multimedia," Special Session on Intelligent Mining, IEEE Big Data Conference,
Santa Clara, CA, October 2015. [PrePrintPDF]
Yuncheng Li, Yang Cong, Tao Mei, and Jiebo Luo, "User-Curated
Image Collections: Modeling and Recommendation," IEEE Big Data Conference,
Santa Clara, CA, October 2015. [PrePrintPDF]
Yu Wang, Jianbo Yuan, and Jiebo Luo, "America Tweets China: A
Fine-Grained Analysis of the State and Individual
Characteristics Regarding Attitudes towards China," IEEE Big Data Conference,
Santa Clara, CA, October 2015. [PrePrintPDF]
Kuan-Ting Chen*, Kezhen Chen*, Peizhong Cong, Winston Hsu,
Jiebo Luo, "Who are the Devils Wearing Prada in New York City?"
ACM Multimedia Conference,
October 2015. [PrePrintPDF]
Xitong Yang, Yuncheng Li, Jiebo Luo, "Pinterest Board
Recommendation for Twitter Users," ACM Multimedia Conference, October 2015. [PrePrintPDF]
Danning Zheng, Tianran Hu, Quanzeng You, and Jiebo Luo,
"Towards Lifestyle Understanding: Predicting Home and Vacation
Locations from User's Online Photo Collections," AAAI International Conference on
Weblogs and Social Media (ICWSM), May 2015.
2010-2014
Quanzeng You, Sumit Bhatia, Jiebo Luo, "The eyes of the
beholder: Gender prediction using images posted in online social
networks," IEEE International
Conference on Data Mining (ICDM), Workshop on Social
Multimedia Data Mining, December 2014. [PDF]
Simon Weber, Jiebo Luo, "What Makes An Open Code Popular in
Github," IEEE International
Conference on Data Mining (ICDM), Workshop on Software Data
Mining, December 2014.
Andrew Nocka, Danning Zheng, Tianran Hu, Jiebo Luo, "Moneyball
for Academia: Towards Measuring and Maximizing Faculty
Performance and Impact," IEEE
International Conference on Data Mining (ICDM), Workshop on
Domain Dependent Data Mining, December 2014.
Danning Zheng, Tianran Hu, Quanzeng You, and Jiebo Luo,
"Inferring Home Location from User's Photo Collections based on
Visual Content and Mobility Patterns," ACM Multimedia Conference, Workshop on Geotagging in
Multimedia (GeoMM), November 2014.
Yuncheng Li, Jiebo Luo, Tao Mei, "Personalized Image
Recommendation for Web Search Engine Users", IEEE ICME, July 2014.
Junhuan Zhu, Quanzeng You, Jiebo Luo and John R. Smith,
"Towards Understanding the Effectiveness of Election Related
Images in Social Media," IEEE
International Conference on Data Mining (ICDM), Workshop on
Domain-driven Data Mining, December 2013. [PDF]
Jianbo Yuan, Quanzeng You, and Jiebo Luo, "Are There
Cultural Differences in Event Driven Information Propagation
Over Social Media?" ACM
Multimedia Conference, International Workshop on
Socially-Aware Multimedia (IWSAM), October 2013. [PDF]
Quanzeng You and Jiebo Luo, "Towards Social Imagematics:
Sentiment Analysis in Social Multimedia," ACM SIGKDD, Workshop on Multimedia
Data Mining, August 2013. [PDF]
Jianbo Yuan, Quanzeng You, Sean McDonough, and Jiebo
Luo, "Sentribute: Image Sentiment Analysis from a Mid-level
Perspective," ACM SIGKDD,
Workshop on Issues of Sentiment Discovery and Opinion
Mining (WISDOM), August 2013. [PDF]
Ge Ma and Jiebo Luo, "Is A Social Picture Worth 1000 Votes?
Analyzing the Sentiment of Election Related Photos," IEEE ICME, July 2013.
Xin Jin, Jie Yu, Jiawei Han, Jiebo Luo, "Reinforced retrieval
in image-rich information networks via integration of link and
content based similarities," IEEE Transactions on Knowledge
Discovery and Engineering, 25(2): pp 448-460, Feb. 2013.
Xin Jin, Cindy Lin, Jiebo Luo, Jiawei Han, "SocialSpamGuard:
A Data Mining-based Spam Detection System for Social Media
Networks," Demo Paper, International Conference on Very
Large Data Bases (VLDB), Seattle, WA, August 2011.
Xin Jin, Chi Wang, Jiebo Luo, Jiawei Han, "LikeMiner: A
System for Mining the Power of 'Like' in Social Media Networks,"
Demo Paper, International Conference on Knowledge Discovery
and Data Mining (KDD), San Diego, CA, August 2011.
Zhijun Yin, Liangliang Cao, Jiawei Han, Jiebo Luo, and Thomas
Huang, "Diversified Trajectory Pattern Ranking in Geo-tagged
Social Media," SIAM Conference on Data Mining (SDM),
Mesa, AZ, April 2011.
Jie Yu, Xin Jin, Jiawei Han, Jiebo Luo, "Collection-based
sparse label propagation and its application to social group
suggestion from photos," ACM Transactions on Intelligent
Systems and Technology, 2(2): , February 2011.
Xin Jin, Andrew Gallagher, Jiawei Han, Jiebo Luo,
"Wisdom of Social Multimedia: Using Flickr for Prediction and
Forecast," ACM Multimedia Conference, Brave and New
Ideas Track, Firenze, Italy, October 2010. (Long Paper)
biomedical analytics and health informatics
2021
Cheng Peng, Haofu Liao, Gina Wong, Jiebo Luo, S. Kevin Zhou,
Rama Chellappa, "XraySyn: Realistic View Synthesis from a Single
Radiograph Through CT Prior," The 35th AAAI Conference on
Artificial Intelligence (AAAI), February 2021.
2020
Weijian Li, Wei Zhu, Ray Dorsey, Jiebo Luo, "Predicting
Parkinson's Disease with Multimodal Irregularly Collected
Longitudinal Smartphone Data," IEEE International Conference
on Data Mining (ICDM), November 2020.
Zhou Zhuang, Johnson V. John, Haofu Liao, Jiebo Luo, Paul
Rubery, Addisu Mesfin, Sunil Kumar Boda, Jingwei Xie and Xinping
Zhang, ''Electrospray-Enabled Peptide Coating of Structural Bone
Allografts for Enhanced Repair and Reconstruction of Femoral
Segmental Defects,'' ACS Biomaterials Science &
Engineering, in press.
Wei Zhu, Haofu Liao, Wenbin Li, Weijian Li, Jiebo Luo,
"Alleviating the Incompatibility between Cross Entropy Loss and
Episode Training for Few-shot Skin Disease Classification," International
Conference on Medical Image Computing and
Computer Assisted Interventions (MICCAI), Lima, Peru,
October 2020.
Yipeng Zhang, Haofu Liao, Jin Xiao, Nisreen Al Jallad, Jiebo
Luo, "A Smartphone-based System for Real-time Early Childhood
Caries Diagnosis," Workshop on Perinatal, Preterm and
Paediatric Image Analysis, International Conference on
Medical Image Computing and Computer Assisted Interventions
(MICCAI), October 2020.
Ray Dorsey, Larsson Omberg, Emma Waddell, Jamie L. Adams, Roy
Adams, Mohammad Rafayet Ali, Katherine Amodeo, Abigail Arky,
Erika F. Augustine, Karthik Dinesh, Mohammed Ehsan Hoque,
Alistair M. Glidden, Stella Jensen-Roberts, Zachary Kabelac,
Dina Katabi, Karl Kieburtz, Daniel R. Kinel, Max A. Little,
Karlo J. Lizarraga, Taylor Myers, Sara Riggare, Spencer Z.
Rosero, Suchi Saria, Giovanni Schifitto, Ruth B. Schneider,
Gaurav Sharma, Ira Shoulson, E. Anna Stevenson, Christopher G.
Tarolli, Jiebo Luo, Michael P. McDermott, "Deep Phenotyping of
Parkinson's Disease," Journal of Parkinson's Disease, in
press.
Long Chen, Xinyi Lu, Jianbo Yuan, Joyce Luo, Jiebo Luo, Zidian
Xie, and Dongmei Li, "A Social Media Study on Associations of
Flavored E-cigarette with Health Symptoms: Observational study,"
Journal of Medical Internet Research, Vol 22, No 6, 2020.
Haofu Liao, Wei-An Lin, S. Kevin Zhou, Jiebo Luo, "ADN:
Artifact Disentanglement Network for Unsupervised Metal Artifact
Reduction," IEEE Transactions on Medical Imaging (TMI),
Volume 39, Issue 3, 2020.
Jianbo Yuan, Zhiwei Jin, Han Guo, Hongxia Jin, Xianchao Zhang,
Tristram Smith, and Jiebo Luo. "Constructing biomedical
domain-specific knowledge graph with minimum supervision." Knowledge
and Information Systems 62(1): 1-20, 2020.
2019
Jianbo Yuan, Haofu Liao, Rui Luo, Jiebo Luo, "Automated
Radiology Report Generation via Multi-view Image Fusion and
Medical Concept Enrichment," International Conference
on Medical Image Computing and Computer Assisted
Interventions (MICCAI), Shenzhen, China, October 2019.
Haofu Liao, Wei-An Lin, Zhimin Huo, William Sehnert, Levon
Vogelsang, Kevin Zhou, Jiebo Luo, "Generative Mask Pyramid
Network for CT/CBCT Metal Artifact Reduction with Joint
Projection-Sinogram Correction," International
Conference on Medical Image Computing and
Computer Assisted Interventions (MICCAI), Shenzhen, China,
October 2019.
Haofu Liao, Wei-An Lin, Jianbo Yuan, S. Kevin Zhou, Jiebo Luo,
"Artifact Disentanglement Network for Unsupervised Metal
Artifact Reduction," International Conference on Medical
Image Computing and Computer Assisted Interventions (MICCAI),
Shenzhen, China, October 2019. (Young Scientist Honorable
Mention) [PDF][Project Page]
Weijian Li, Viet-Duy Nguyen, Haofu Liao, Matthew Wilder, Ke
Cheng, Jiebo Luo, "Patch Transformer for Multi-tagging Whole
Slide Histopathology Images," International Conference on
Medical Image Computing and Computer Assisted
Interventions (MICCAI), Shenzhen, China, October 2019.
Sen Zhang, Changzheng Zhang, Lanjun Wang, Cixing Li, Dandan
Tu, Rui Luo, Guo-Jun Qi, Jiebo Luo, "MSAFusionNet: Multiple
Subspace Attention Based Deep Multi-modal Fusion Network," Springer
LNCS Proceedings of the 10th International Workshop on
Machine Learning in Medical Imaging (MLMI), in
conjunction with MICCAI, Shenzhen, China, October 2019.
Dong Liu, Changzheng Zhang, Lanjun Wang, Yaoxin Li, Xiaoshi
Chen, Rui Luo, Shuanlong Che, Hehua Liang, Yinghua Li, Si Liu,
Dandan Tu, Guo-Jun Qi, Pifu Luo, Jiebo Luo, "DCCL: A Benchmark
for Cervical Cytology Analysis," Springer LNCS Proceedings
of the 10th International Workshop on Machine Learning in
Medical Imaging (MLMI), in conjunction with MICCAI,
Shenzhen, China, October 2019.
Zidian Xie, Olga Nikolayeva, Dongmei Li, Jiebo Luo, "Building
Risk Prediction Models for Type 2 Diabetes Using Machine
Learning Techniques," Preventing Chronic Disease, in
press.
Wei-An Lin*, Haofu Liao*, Cheng Peng, Xiaohang Sun, Jingdan
Zhang, Jiebo Luo, Rama Chellappa, S. Kevin Zhou, "DuDoNet: Dual
Domain Network for CT Metal Artifact Reduction," IEEE
Conference on Computer Vision and Pattern Recognition (CVPR),
Long Beach, CA, June 2019.
Haofu Liao, Wei-An Lin, Jiarui Zhang, Jingdan Zhang, Jiebo
Luo, S. Kevin Zhou, "Multiview 2D/3D Rigid Registration via a
Point-Of-Interest Network for Tracking and Triangulation," IEEE
Conference on Computer Vision and Pattern Recognition (CVPR),
Long Beach, CA, June 2019.
2018
S Weisenthal, C Quill, J Luo, H Kautz, S Farooq, M Zand, "A
machine learning pipeline to predict acute kidney injury (AKI)
in patients without AKI in their most recent hospitalization," Journal
of Clinical and Translational Science, 2018.
Haofu Liao, Zhimin Huo, James Sehnert, Kevin S, Zhou, Jiebo
Luo, "Adversarial Sparse-View CBCT Artifact Reduction," International
Conference on Medical Image Computing and Computer Assisted
Intervention (MICCA), Granada, Spain, September 2018. (oral
presentation)
Haofu Liao, Yucheng Tang, Gareth Funka-Lea, Jiebo Luo, Kevin
S. Zhou, "More Knowledge is Better: Cross-Modality Volume
Completion and 3D+2D Segmentation for Intracardiac
Echocardiography Contouring," International Conference on
Medical Image Computing and Computer Assisted Intervention
(MICCA), Granada, Spain, September 2018.
Haofu Liao, Addisu Mesfin, Jiebo Luo, "Joint Vertebrae
Identification and Localization in Spinal CT Images by Combining
Short- and Long-Range Contextual Information," IEEE
Transactions on Medical Imaging 37(5): 1266-1275,
2018.
2017
Xuefeng Peng, Jiebo Luo, Catherine Glenn, Li-Kai Chi, and
Jingyao Zhan, "Sleep-deprived Fatigue Pattern Analysis using
Large-Scale Selfies from Social Media," Special Session on
Intelligent Data Mining, IEEE Big Data Conference,
Boston, MA, December 2017.
Yiheng Zhou, Jingyao Zhan and Jiebo Luo, "Predicting Multiple
Risky Behaviors via Multimedia Content," International Conference on Social
Informatics (SocInfo), Oxford, England, September
2017.
Xitong Yang, Jiebo Luo, "Tracking Illicit Drug Dealing and
Abuse on Instagram using Multimodal Analysis," ACM Transactions on Intelligent
Systems and Technology, 8(4): 58:1-58:15, August 2017.
Xuefeng Peng and Jiebo Luo, "Large-Scale Sleep Condition
Analysis Using Selfies from Social Media," International Conference on Social
Computing, Behavioral-Cultural Modeling & Prediction and
Behavior Representation in Modeling and Simulation (SBP-BRiMS),
Washington, DC, July 2017.
Jianbo Yuan, Chester Holtz, Tristram H Smith, Jiebo Luo,
"Autism Spectrum Disorder Detection from Semi-Structured and
Unstructured Medical Data," EURASIP
Journal on Bioinformatics and Systems Biology, 2017:3,
February 2017.
Yiheng Zhou, Catherine Glenn, Jiebo Luo, "Understanding and
Predicting Multiple Risky Behaviors from Social Media," AAAI 2017 Joint Workshop on Health
Intelligence, San Francisco, CA, February 2017.
Haofu Liao, Jiebo Luo, "A Deep Multitask Learning Approach to
Skin Lesion Classification," AAAI
2017 Joint Workshop on Health Intelligence, San
Francisco, CA, February 2017.
2016
Haofu Liao, Yuncheng Li, Jiebo Luo, "Skin Disease
Classification versus Skin Lesion Characterization: Achieving
Robust Diagnosis using Multi-label Deep Neural Networks", International Conference on
Pattern Recognition (ICPR), Cancun, Mexico, December
2016.
Kuan Wang, Jiebo Luo, "Detecting Visually Observable Disease
Symptoms from Faces", 1ST
International Workshop on Biomedical Informatic with
Optimization and Machine Learning (BOOM), in
conjunction with IJCAI 2016, New York City, New York, July
2016. (Best Paper Runner-Up)
Chunlan Huang, Vincent P. Ness, Xiaochuan Yang, Hongli Chen,
Jiebo Luo, Edward B Brown and Xinping Zhang, "Spatiotemporal
Analyses of Osteogenesis and Angiogenesis via Intravital Imaging
in Cranial Bone Defect Repair," Journal of Bone and Mineral Research,
available in
PubMed.
2015
Dawei Zhou, Jiebo Luo, Vincent Silenzio, Yun Zhou, Glenn
Currier, and Henry Kautz, "Tackling Mental Health by Integrating
Unobtrusive Multimodal sensing," the Twenty-Ninth AAAI Conference on Artificial
Intelligence (AAAI), Austin, TX, January 25-30, 2015. [PDF]
Junhuan Zhu, Jiebo Luo, Yousuf Khalifar, "Computerized Grading
of Cataract Surgery from Videos," Machine Vision and Applications, 26(1):
115-125, 2015.
Yang Cong, Ji Liu, Jiebo Luo, "Deep Sparse Feature Selection
for Computer Aided Endoscopy Diagnosis," Pattern Recognition, 48(3):
907-917, 2015.
Pre-2015
Tianli Yu, Jiebo Luo, Narendra Ahuja, "Search strategies for
shape regularized active contour," Computer Vision and
Image Understanding, 113(10): 1053-1063, 2009.
Hui Luo, Jiebo Luo, "Robust online orientation correction for
radiographs in PACS environments," IEEE Transactions on
Medical Imaging, 25(10): 1370-1379, 2006.
human computer interaction
Tianran Hu, Anbang Xu, Jiebo Luo. "Touch Your Heart: A
Tone-aware Chatbot for Customer Care on Social Media," The
ACM CHI Conference on Human Factors in Computing Systems (CHI),
Montreal, Canada, April 2018.
Quanzeng You, Jianbo Yuan, Jiaqi Wang, Philip Guo, Jiebo Luo.
Snap n' Shop: Visual Search-Based Mobile Shopping Made a Breeze
by Machine and Crowd Intelligence, IEEE International Conference on Semantic Computing
(ICSC), February 2015. [PDF]
Vivek K. Singh, Jiebo Luo, Dhiraj Joshi, Phoury Lei,
Madirakshi Das, Peter Stubler, "Reliving on demand: a total
viewer experience," ACM international conference on
Multimedia, November 2011.
Dhruv Batra, Adarsh Kowdle, Devi
Parikh, Jiebo Luo, and Tsuhan Chen, "iCoSeg: Interactive Co-segmentation of Objects in Image
Collections," IEEE Conference on Computer
Vision and Pattern Recognition (CVPR), San Francisco, CA,
June 2010.
mobile and pervasive computing
Yipeng Zhang, Haofu Liao, Jin Xiao,
Nisreen Al Jallad, Jiebo Luo, "A Smartphone-based System for
Real-time Early Childhood Caries Diagnosis,"Workshop on Perinatal, Preterm and Paediatric Image
Analysis,International Conference on Medical Image Computing
and Computer Assisted Interventions(MICCAI),
October 2020.
Young
Chol Song, Henry Kautz, James Allen, Mary Swift, Yuncheng Li,
Jiebo Luo, "A Markov Logic Framework for Recognizing Complex
Events from Multimodal Data," ACM International Conference on Multimodal
Interaction, Sidney, Australia, December 2013.
Heng
Liu, Tao Mei, Jiebo Luo, Houqiang Li, Shipeng Li, "Finding
Perfect Rendezvous On the Go: Accurate Mobile Visual
Localization and Its Applications to Routing," ACM
Multimedia Conference, Nara, Japan, October 2012.
(Long paper, Best Paper Candidate)
Learning
with Unpaired Data
Many learning tasks can be summarized as learning a mapping
from a structured input to a structured output, such as
machine translation, image style transfer, image captioning,
and image dehazing. Such mappings are usually learned on
paired training data, where an input sample and its
corresponding output are both provided. Collecting paired
training data often involves expensive human annotation, and
the scale of paired training data is therefore often limited.
As a result, the generalization ability of models trained on
paired data is also limited. One way to mitigate this issue is
learning with unpaired data, which is far less expensive to
collect. Taking machine translation as an example, the
unpaired training data can be collected separately from
newspapers in the source language and target language without
any annotation. The challenge of unpaired learning turns into
how to align the unpaired data. With carefully designed
objectives, unpaired learning has achieved remarkable progress
on several tasks. This talk will cover the data collection and
training methods of several unpaired learning tasks to
illustrate the power of learning with unpaired data.
Jointly Understanding User
and Content from Multimodal Social Media Data
Social media has become prevalent in our lives as the main
venue for sharing information, recording moments, as well as
expressing feelings and creativity. Two of the most
important signals in social media data are user profiles and
user sentiments, both of which can be inferred from
multimodal social media content that users choose to share
or respond to. We have been employing a joint modeling and
understanding approach to building interpretable user
profiles and characterizing nuanced user sentiments for a
wide variety of applications including Instagram, Tiktok,
Facebook, Pinterest, Youtube, Twitter, and Wechat. In this
talk, we will present the framework along with a few case
studies to illustrate the power of our approach, as well as
its utilities in content creation, promotion, and
recommendation.
Computer Vision ++: The Next
Step towards Big AI
With the huge successes of deep learning in computer vision,
many vision problems are seemingly being solved. Where do we
go from here? We will discuss a few directions where
computer vision can be either further pushed to deal with
data scarcity and data noise, or synergistically integrated
with other disciplines such as NLP and data mining, to
continue to advance the frontiers of artificial
intelligence.
Harvesting the Healing Power of AI
and Big Data
With the recent rapid advances in artificial intelligence,
machine learning and data science, a promising domain is
healthcare and wellness management. In this talk, we discuss
two directions: first, leveraging electronic medical data
including unstructured forms and videos to build robust
algorithms for disease diagnosis and medical training, and
second and more interestingly, utilizing social media data to
detect and alter user unhealthy behaviors such as drinking,
smoking, drug-use, and eating disorder. It is also intriguing
how these two directions can be combined synergistically, and
further to implement effective and innovative intervention.
Spear
and Shield: War of Misinformation and Disinformation Social media,
including Twitter and Chinese Weibo, has become an important
news and public opinion channel of in recent years. For
example, during the 2016 U.S. presidential election,
candidates and their supporters were actively engaged on
Twitter to run campaigns and express their opinions. The
convenience and openness of social media have also fostered
various misinformation,
rumors, and fake news, which have
become a serious public concern. To increase the credibility
of information on social media and prevent the spreading of
fake contents, it is crucial to detect misinformation and
disinformation automatically. We introduce our work in this
area and also provide analyses of the impacts in major
political events such as the U.S. presidential election.
When
Computer Vision meets E-Commerce Two of the top 10 largest
companies bymarket cap in the world, namely Amazon and Alibaba, are e-commerce
companies that are enjoying huge success. At the same time,
computer vision and artificial intelligence are making
strides in both technologies and applications. What power
can be unleashed when computer vision meets e-commerce. We
will present a few recent advances in user profiling,
behavior analytics, product recommendation, as well as deep
sales data mining.
Video and Language Video has become ubiquitous on
the Internet, TV, as well as personal devices. Recognition of
video content has been a fundamental challenge in computer
vision for decades, where previous research predominantly
focused on recognizing videos using a predefined yet limited
vocabulary. Thanks to the recent development of deep learning
techniques, researchers in multiple communities are now
striving to bridge videos with natural language in order to
move beyond classification to interpretation, which should be
regarded as the ultimate goal of video understanding. We will
present recent advances in exploring the synergy of video
understanding and language processing techniques, including
video-language alignment, video captioning, and video emotion
analysis.
Computational Inference of
Emotion in Images
With the recent successes in using deep learning techniques to
solve computer vision problems, the performances of the state of
the art algorithms in many areas, especially object recognition,
have been dramatically improved. Researchers are now inspired to
address yet more challenging problems, such as associating
pictures with aesthetics, and have also reported progress. One
remaining final frontier in extracting meaning from images is
related to the recognition of emotions that images arouse in
humans. The key challenges are the loose and highly abstract
nature of semantics associated with emotions. We will discuss
how to effectively employ a data-intensive approach to emotion
recognition in images, as well as multimedia that include both
image and text information.
You Are What You Post:
Personal Analytics from Big Social Media Data
From the abundance of personal records, public data, and
user-generated social multimedia contents, rich information
can be inferred regarding user profile, user interests, user
sentiment, user behaviors, user mobility, user lifestyles, as
well as user physical and mental health. We will present a few
recent advances in this important arena.
2016 Presidential Election: Donald
Trump De-mystified
With social media being increasingly utilized to boost
political campaigns, Donald Trump looms large in the 2016 US
Presidential Election. With the ability to track the Twitter
followers of the major candidates in the running, we conduct a
series of in-depth, fine-grained, data-driven analyses,
including 1) Will Sanders Supporters Jump Ship for Trump?
Fine-grained Analysis of Twitter Followers?, 2) Pricing the
Woman Card: Gender Politics between Hillary Clinton and Donald
Trump, and 3) Voting with Feet: Who are Leaving Hillary
Clinton and Donald Trump? These studies represent a new
paradigm for studying political campaigns and provide valuable
insight at unprecedented
scales and in
real-time.
Big Data Better Life We live in the age of big data.
The biggest big data is big visual data, which includes images
and other associated information. The biggest challenge is to
develop effective computational methods for making sense of
such massive visual data. Unlike text which is clean,
segmented, compact, one dimensional and indexable, visual
content is noisy, unsegmented, high entropy and
multidimensional. In this talk, we present a few recent
advances towards the ultimate goal of using big data, in
particular large-scale and rich multi-modality data, to
achieve robust intelligence in order to understand and improve
life in terms of healthcare, well-being, politics, business,
infotainment, and so on.
Vision with A Billion Eyes
A recent trend in computer vision is driven by images and video
generated by heterogeneous and multi-perspective visual sensing
networks. We present a few examples of research along this
line. First, we will present an interesting framework for
event recognition. With GPS information, we obtain satellite
images corresponding to picture locations and investigate their
novel use to recognize the picture-taking environment. We then
combine this inference with classical vision-based event
detection methods and demonstrate the synergistic fusion of the
two approaches. Second, to determine the viewing direction for
geotagged photos, we utilize both Google StreetView and Google
Earth satellite images. Third, we explore using phone-captured
images for localization as it contains more context information
than the embedded sensory GPS coordinates. We then build
applications to enable people to enjoy ubiquitous location-based
services (LBS) using their phones. Fourth, we leverage
crowd-sourced photos to remove unwanted bystanders from tourist
photos taken at popular attractions and measure air pollution in
major cities in China. Furthermore, given a new source of
visual data from public webcams deployed in urban environments,
we will present some ongoing work on crowd analytics using such
data.
Social Multimedia as Sensors
Social multimedia can be exploited as a powerful new way of
sensing social behaviors and activities from user-generated
social multimedia contents, including building user profiles
from a user's personal photo collection, inferring user
personality traits from social media language usage, producing
popular and diverse tourism routes from crowd-sourced geo-tagged
photos, extracting user sentiment from both textual and visual
information in social media, monitoring risky behaviors such as
teenage drinking and drug abuse, and forecasting election
outcome based on image sharing activities and user demographics
extracted using computer vision techniques. Finally, we will
share thoughts on current challenges and future directions.
CS/DS Program: Long Chen, Xinyi Lu,
Shuaidong Pan, Faner Lin, Zhifan Nan, Gao Fan, Tolga
Atkas, Viet Duy Nuygen, Viet Duong, Phu Pham, Yutong He,
Benjamin King, Peijun Xu, Yiming Pan, David Anuta, Josh
Churchin, Numair Sani, Ryan Berger, Kelly
He (Ernst & Young), Trevor Whitestone, Chester
Holtz (UCSD), Yiheng Zhou (CMU), Yuntao
Zhou (CMU), Honglin Zheng (UCLA), Xuefeng Peng (Harvard),
Kevin Chi, Zhishen Pan, Jiagen Zheng (UCSD), Jingyao Zhan
(UCSD), Zoe Tiet, Raina Langevin, Jake Schechner, Caesar De
Hoyos, Kuan Wang (PhD@U Penn), Lee Murphy, Jacob Niebloom,
Kezhen Chen (PhD@Northwestern), Chunpai Wang (PhD@Albany),
Andrew Nocka (Charles Schwab), Simon Weber (Hacker School)
Math/Stats/Applied Math Program: Danning Zheng (Bloomberg)
Economy Program: Alex Feiszli
Prospective
PhD Students
I'm
always looking for self-motivated students and usually recruit two
new PhD students per year. Applicants are expected to have
strong skills in both programming
and mathematics, as
well as research experience
in closely related areas. Grades alone won't cut it. "I worked
on a gazillion of projects" (but have no evidence) is a no-no.
Research publications in ranked venues of computer
vision,
machine
learning, or data
mining
is a plus (and the only reason you need to contact me directly).
Sorry but generic spams will be ignored.
I normally have two to three self-funded visiting student
positions per year. I do not provide any paid visiting or postdoc
positions, and I do not consider any visits shorter than 3 months.
It is expected that you have some minimum prior research
experience. A recommendation letter via email directly from your
research advisor is needed, if you have not personally met me.
Current UR
Students
Current UR students (undergraduate or MS) interested in working
with me are welcome to stop by my office during my office hours
(see the posting outside my office). It is desirable that you have
taken a course with me prior to starting any research in my lab. A
resume through email in advance is recommended as opposed to a
cold knock on the door. Reference
Letter Seekers
You
must have your advisor/mentor vouch for you, if you have not
personally worked with me. If you intend to work in my lab,
producing meaningful or publishable results is the essence for
the reference letter as a generic letter stating that you
worked in my lab would not help your graduate school
application.
Internship
Seekers
In
general, we do not host
summer internsunless
there is a preexisting arrangement, or you have prior research
product(s) to validate your seriousness.
Why URCS?
The University of Rochester is a private institution that was
founded in 1850. It is one of the smallest and most collegiate
schools among the nation's top research universities. According to
US News and World Report 2019, the University of Rochester's
ranking in the Best National Universities is 29th. It is also one
of only 25 schools named a "New Ivy" in the 2007 Kaplan/Newsweek
"How to Get into College Guide".
The Department of Computer Science at the University of Rochester
is a research-oriented department with a distinguished history of
contributions in systems, theory, artificial intelligence, and
HCI. Historically, a third of its PhD graduates have received
tenure-track faculty positions, and its alumni include prominent
leaders at major research laboratories such as Google, Microsoft,
and IBM.
Research is
a Journey not for the Faint-hearted
Do you have what it takes to be a successful PhD student? The
initial threshold is 4 out of 7 and I hope you have all 7 at
graduation.