Five New Faculty Join URCS

Published
July 1, 2014

John Criswell is an assistant professor in the Department of Computer Science at the University of Rochester.  He earned both his B.S. in Computer Science (2003) and Ph.D. in Computer Science (2014) at the University of Illinois at Urbana-Champaign.

John’s research interests focus on computer security and novel applications of compiler and operating system technology.  John's primary research work is on the Secure Virtual Architecture (SVA).  SVA enforces security policies on commodity operating system and application code via compiler instrumentation, thereby providing strong protection against sophisticated attacks.  Using SVA, John built the first systems that provide strong automated memory safety protection and complete control-flow integrity enforcement to commodity operating system kernels such as Linux and FreeBSD.  More recently, John has used SVA to create the Virtual Ghost system that protects application data and control-flow from a compromised operating system kernel.

Prior to joining the University of Rochester, John was a research programmer and graduate student at the University of Illinois.  Before that, John worked at Argus Systems Group, Inc. John’s work at Argus Systems Group included enhancements to the AIX operating system kernel and writing utilities that utilized mandatory access controls to improve system security.

Philip Guo is an assistant professor of Computer Science at the University of Rochester. His main research interests are in human-computer interaction (HCI), especially building tools for informal learning and online education. He is the creator of Online Python Tutor (pythontutor.com), a Web-based computer science education tool that has been used by over 500,000 people in over 165 countries. He plans to teach classes related to Web programming, dynamic programming languages, human-computer interaction, and educational technology.

Philip received a Ph.D. in Computer Science from Stanford University in 2012 and S.B. and M.Eng. degrees in Electrical Engineering and Computer Science from MIT in 2006. His Ph.D. dissertation was one of the first to identify the unique software needs of data scientists and to develop five new tools to address those needs. One such tool from his dissertation, CDE, has been used by over 10,000 people.

In addition to research and teaching, Philip is an avid writer. In 2012, he wrote a popular free e-book called The Ph.D. Grind (phdgrind.com), which is the first known detailed account of an entire Ph.D. experience, with over 300,000 downloads so far. Philip also writes a monthly blog column for the Communications of the ACM, and his personal website (pgbovine.net) gets over 250,000 visitors per year.

M. Ehsan Hoque is an Assistant Professor of Computer Science at the University of Rochester where he leads the Rochester Human-Computer Interaction (ROC HCI) Group. Ehsan’s research focuses on developing new algorithms that can sense subtle human nonverbal behavior enabling new applications of emotion technology in high-impact social domains such as social skills training, public speaking, and assisting individuals who experience difficulties with social interactions.

Ehsan has received his PhD degree from MIT Media Lab in August of 2013.  His PhD thesis - "Computers to Help with Conversations: Affective Framework to Enhance Human Nonverbal Skills" - was the first of its kind to demonstrate that it is possible for people to learn and improve their social skills by interacting with an automated system. Ehsan has won a number of awards, including the IEEE Gold Humanitarian Fellowship, and Best Paper Award at Ubiquitous Computing (UbiComp 2013), Best Paper honorable mentions at Automated Face and Gesture Recognition (FG 2011), and Intelligent Virtual Agents (IVA 2006).

Ehsan’s PhD work was showcased at the MIT Museum as one of the most unconventional inventions at MIT, and  has been featured in forums for the general public such as Canadian National TV, NPR, PBS, Time, among many. Ehsan's work is currently being supported by DARPA, Google Faculty Research Award and Microsoft Azure Award.

Thomas M. Howard will join the faculty of the Department of Computer Science and the Department of Electrical and Computer Engineering as an Assistant Professor in January 2015. He will also be a member of the Institute for Data Science and hold a secondary appointment in the Department of Biomedical Engineering. Dr. Howard is currently a Research Scientist at the MITComputer Science and Artificial Intelligence Laboratory in the Robust Robotics Group. Previously he was a Research Technologist at JPL in the Mobility and Robotic Systems section and a Lecturer in Mechanical Engineering at Caltech. Dr. Howard earned a PhD in Robotics from The Robotics Institute at Carnegie Mellon University in 2009 in addition to BS degrees in Electrical and Computer Engineering and Mechanical Engineering from the University of Rochester in 2004.

Dr. Howard’s research interests span artificial intelligence, robotics, and human-robot interaction. His research focuses on improving the optimality, efficiency, and fidelity of models for decision making in complex and unstructured environments with applications to robot motion planning and natural language understanding. He has applied his research on numerous robots including planetary rovers, autonomous automobiles, mobile manipulators, robotic torsos, and unmanned aerial vehicles. Dr. Howard was a member of the flight software team for the Mars Science Laboratory, the motion planning lead for the JPL/CaltechDARPA Autonomous Robotic Manipulation team, and a member of Tartan Racing, winner of the DARPA Urban Challenge.

Ji Liu is an assistant professor of the Department of Computer Science at University of Rochester. He received his PH.D. degree in computer science from University of Wisconsin-Madison in 2014, his M.S. degree in computer science from Arizona State University in 2010, and his B.E. degree in automation from University of Science and Technology of China in 2005. His research interests include machine learning and optimization as well as their applications in big data analytics, data mining, computer vision, etc. He won the KDD best research paper award honorable mention in 2010.