New Tenure-Track Faculty to Join Department of Computer Science

The University of Maryland’s Department of Computer Science is set to welcome a new cohort of eight new tenure-track faculty. The faculty members, with research expertise spanning a wide range of cutting-edge areas, are expected to enhance the department’s academic and research capabilities. 

"We are excited to welcome our newest faculty members," said Department Chair Matthias Zwicker, who holds the Elizabeth Iribe Chair for Innovation and the Phillip H. and Catherine C. Horvitz Professorship. "Their perspectives will drive forward impactful research and raise our level of excellence for years to come. We are thrilled to support them in their work as they join our department!"

Ruohan Gao

Ruohan Gao’s research focuses on computer vision and machine learning, with an emphasis on multisensory learning involving sight, sound and touch. The overarching goal of Gao's work is to empower machines to emulate and enhance human capabilities in perceiving and engaging with the multisensory world. He received a Ph.D. in Computer Science from The University of Texas at Austin. Following this, Gao completed a postdoctoral fellowship at Stanford Vision and Learning Lab.

Gao will join the department as an assistant professor in January 2025. He will lead UMD's Multisensory Machine Intelligence Group.

Mohit Iyyer

Mohit Iyyer’s research interests lie broadly in natural language processing and machine learning. Iyyer is focused on improving the instruction-following abilities of large language models for long-form generation, designing methods to evaluate long-form and multilingual text, building collaborative human-LLM systems to assist human authors in creative writing tasks, and increasing the robustness of LLM-generated text detectors to attacks. Iyyer earned a Ph.D. in Computer Science from the University of Maryland College Park in 2017, where he was a member of the Computational Linguistics and Information Processing (CLIP) Lab. He was also a postdoctoral researcher at the Allen Institute for Artificial Intelligence and later a faculty member at the University of Massachusetts, Amherst.

Iyyer will join the department as an associate professor in January 2025.

Gabe Kaptchuk

Gabe Kaptchuk’s research specializes in cryptography and privacy. He was a part of the researcher faculty at Boston University Kaptchuk and earned a Ph.D. in Computer Science from Johns Hopkins University. 

Kaptchuk will join the department as an assistant professor in August 2024. He will also be affiliated with the Maryland Cybersecurity Center (MC2) and the University of Maryland Institute for Advanced Computer Studies (UMIACS).

Binghui Peng

Binghui Peng’s research interests include theoretical computer science and machine learning. His current research aims to understand learning and intelligence through the lens of computation. Peng received a Ph.D. in Computer Science from Columbia University and his bachelor's degree from Tsinghua University in the prestigious Yao Class.

Peng will join the department as an assistant professor in the summer of 2025.

Han Shao

Han Shao’s primary research centers on machine learning theory, with a specific focus on modeling human strategic and adversarial behaviors within the learning process. Shao aims to understand how these behaviors affect machine learning systems and develop methods to enhance accuracy and robustness. Additionally, Shao is interested in gaining a theoretical understanding of empirical observations concerning adversarial robustness. Shao earned a Ph.D. in Computer Science from the Toyota Technological Institute in Chicago.

Shao will join the department as an assistant professor in the summer of 2025.

Runzhou Tao

Runzhou Tao specializes in the intersection of programming languages, operating systems and quantum computing, with a focus on building trustworthy and efficient quantum computing system software. Tao earned a Ph.D. in Computer Science from Columbia University and completed a bachelor's degree from Tsinghua University, where he conducted research on theoretical computer science.

Tao will join the department as an assistant professor in August 2024.

Fumeng Yang

Fumeng Yang’s research explores data-driven computational models, focusing on how individuals and groups perceive, use and develop these models. Yang’s work spans probabilistic forecasts and AI techniques such as foundation models. She is a researcher in Human-Computer Interaction (HCI) and Visualization. Yang earned a Ph.D. in Computer Science from Brown University, an M.Sc. from Tufts University and a B.Eng. from Shandong University.

Yang will join the department as an assistant professor in August 2024.

Yaodong Yu

Yaodong Yu’s research interests are in the theoretical foundations and applications of trustworthy machine learning. Yu’s work includes interpretable white-box deep neural networks, differentially private foundation models, optimization and uncertainty quantification for collaborative learning and robustness under distribution shifts. Yu earned a Ph.D. in Computer Science from UC Berkeley. His academic background also includes a B.S. from Nanjing University and an M.S. from the University of Virginia.

Yu will join the department as an assistant professor in the summer of 2025. 

—Story by Samuel Malede Zewdu, CS Communications