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CRC & Assistant Professor, Cheriton School of Computer Science

is a Canada Research Chair in "Minimizing Human Error in Modern Networks" and an assistant computer science professor at the University of À¶Ý®ÊÓƵ. Her research focuses on programmable computer networks, specifically on designing and developing automated processes to program and reason about modern networks. In doing so, she brings in techniques from other computer science disciplines such as formal methods, programming languages, and hardware design. Prior to À¶Ý®ÊÓƵ, she was a presidential post-doctoral fellow at the computer science department of Cornell University, and received her Ph.D. from Princeton University, where she was advised by Jennifer Rexford. She has been named a Rising Star in Networking and Communications by N2Women in 2021 and her work has been recognized by the ACM SIGCOMM Doctoral Dissertation Award and Microsoft Research Dissertation Grant.

Assistant Professor, Cheriton School of Computer Science

Dr. is an assistant computer science professor at the University of À¶Ý®ÊÓƵ. His research area lies broadly in computer systems. In particular, his work identifies and mitigates side-channel vulnerabilities in computer systems and generative AI applications. Professor Liu also works on system designs that mitigate carbon emissions in AI and cloud systems. He received a PhD degree at the University of Virginia in 2022, where his PhD research was supported by a Google Fellowship award.Ìý

Assistant Professor & Director of the Active & Interactive Robotics Lab (AIRLab)

Dr.ÌýYue Hu is an assistant professor in the Department of Mechanical and Mechatronics Engineering at the University of À¶Ý®ÊÓƵ. She holds a PhD in computer science from Heidelberg University, with postdoctoral training at Heidelberg and the Italian Institute of Technology. Prior to joining À¶Ý®ÊÓƵ, she held academic and research positions in Japan, including as a JSPS fellow at AIST and assistant professor at Tokyo University of Agriculture and Technology. Her research bridges physical-social human-robot interaction, collaborative and humanoid robotics, and optimal control, with a recent interest in cybersecurity and privacy in robotic systems. She investigates how robots can interact safely and meaningfully with people while preserving users’ privacy and protecting against cyber threats. Recent work includes studying traffic analysis vulnerabilities in teleoperated robots and developing defenses to mitigate fingerprinting risks, and privacy in interactions with social robots. Professor Hu is also a co-lead of the CRAFT (Cybersecure Robotics and Future Talent) initiative, a multidisciplinary training program focused on offensive and defensive cybersecurity in robotic platforms.

Assistant Professor, University of À¶Ý®ÊÓƵ's Faculty of Engineering

Dr. is an assistant professor in the Department of Electrical and Computer Engineering at the University of À¶Ý®ÊÓƵ. His research lies at the intersection of computer architecture, computer systems, and theoretical computer science, with a focus on cybersecurity. Professor Zahedi received his Ph.D. in computer science from Duke University and his Bachelor of Science and Master of Science degrees in electrical and computer engineering from the University of Tehran.

Assistant Professor, University of À¶Ý®ÊÓƵ's Department of Economics

I am an economic theorist working at the intersection of economics and computer science. My research focuses on multi-agent learning to understand and shape the societal consequences of our transition to an algorithm-driven economy. I am particularly interested in the theoretical underpinnings that will ensure these systems are stable, fair, and beneficial to society.Ìý

Assistant Professor, University of À¶Ý®ÊÓƵ's Management Science and Engineering Department

, Ph.D., holds the Val O’Donovan Chair in Efficient, Safe, and Adaptive AI in the Faculty of Engineering and is an assistant professor in the Management Science and Engineering Department at the University of À¶Ý®ÊÓƵ, with cross-appointments in Systems Design Engineering and the David R. Cheriton School of Computer Science. As director of the Critical Machine Learning Lab, Dr. Rambhatla develops efficient and adaptive models that prioritize safety and reliability -- addressing the real-world demands of critical, data-scarce, and evolving environments in health care, manufacturing, aviation, and beyond. With over 50 publications and wide media coverage, her recognitions include the 2025 Outstanding Performance Award from the University of À¶Ý®ÊÓƵ, and the 2021 Merit Award for Excellence in Postdoctoral Research from the University of Southern California. She earned her Ph.D. and M.S. in electrical engineering from the University of Minnesota – Twin Cities, where she was awarded the E. Bruce Lee Memorial Fellowship.