October 28, 2015: Introducing our newest CS faculty members

Steve Checkoway

Assistant Professor

Steve Checkoway is an Assistant Professor in the Department of Computer Science at the University of Illinois at Chicago. Prior to joining UIC, he was an Assistant Research Professor in the Johns Hopkins University Department of Computer Science. He received a Ph.D. in computer science at the University of California, San Diego in 2012.

Checkoway?s research focuses on computer security, broadly construed. His work on the security of cyber-physical systems includes the first comprehensive analysis of automobile computer systems which demonstrated exploitable weaknesses in safety-critical software. Checkoway also conducted the first independent analysis of the backscatter X-ray, full-body scanners formerly deployed in U.S. airports. This study found that physical limitations of computer-controlled X-rays enabled contraband such as guns, knives, and explosives to be transported undetected through the scanner. Checkoway's work on compiler defenses against software exploitation have been integrated into Clang and GCC, the two most common compilers for Mac OS X and Linux.

Doug Hogan


Doug Hogan grew up in Altoona, PA, and spent most of his younger life in Central PA, doing undergrad at Juniata College and a first graduate degree at Penn State, both nearby. He did his undergrad work in math and CS and the first masters in CS. Knowing he was passionate about teaching math, he did a second masters in math education at Boston University. He taught high school math in York, PA, for two years, and spent the last seven years as an instructor in the CS department at Penn State.

Doug's strongest interest is teaching discrete math and the theoretical side of data structures and algorithms, and he is especially interested in helping students make the transition from procedural mathematics to abstract mathematics and the kind of tools they need to reason rigorously in CS. He is also passionate about academic advising, particularly with the early stages of the college curriculum and transitioning from high school to college.

Cynthia Taylor

Clinical Assistant Professor

Cynthia Taylor specializes in Computer Science pedagogy, focusing on active learning and assessment of pedagogical techniques, especially concept inventories.?She received her PhD in 2012?from the University of California, San Diego, where she focused on distributed systems.?

She enjoys teaching systems classes, including Operating Systems, Systems Programming, and Networks. She is especially interested in how students learn systems topics, and previously worked on developing a concept inventory for Operating Systems.

Balajee Vamanan

Assistant Professor

Balajee Vamanan's research straddles networking, systems, and architecture. Specifically, he is interested in the emerging networking-paradigms such as software-defined networking (SDN) and network function virtualization (NFV), and network optimizations for online services such as Web search and key-value stores.

Balajee received his PhD from Purdue University in 2015. His thesis focused on performance and energy optimizations for Online, Data-Intensive (OLDI) applications and network packet classification. During his PhD, he has worked on transport protocols, load balancing, network hardware, and energy management. In addition, he has experience with architecture and hardware design. Before graduate school, he was a hardware designer at NVIDIA Corporation where he was the lead memory controller designer for the first unibody MacBook Air.

Xinhua Zhang

Assistant Professor

Xinhua Zhang obtained his PhD in computer science from the Australian National University (ANU) in 2010, with specialization in statistical machine learning.? From Apr 2010 to Sept 2012, he was a postdoc at the Alberta Innovates Centre for Machine Learning within the University of Alberta.?From Oct 2012 to Oct 2015, he was a researcher at the Machine Learning Group of National ICT Australia (NICTA), with an adjunct appointment at the ANU.? He will join CS @ UIC in Nov 2015, and his current homepage is at https://www.cs.uic.edu/~zhangx.

Xinhua Zhang is interested in the development and analysis of statistical machine learning methods.?He is recently focusing on convex models for learning predictive representation, which jointly infer latent representation and learn predictors for massive datasets by combining them into a single convex optimization problem. This also involves the design of efficient optimization algorithms that are scalable for big data. He is interested in teaching data analytics and general computer science courses.

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