Ten Ph.D. Students Receive Outstanding Graduate Assistant Award

Ten doctoral students have received the Outstanding Graduate Assistant Award for the 2025–2026 academic year. Joseph Carolan, Pierce Darragh, Eadom Dessalene, Hiba El Oirghi, Peyman Jabbarzade, Donghyeon Joo, Dayeon Ki, Sonal Kumar, Yonghan Lee and Renata Valieva were recognized by the University of Maryland Graduate School for their contributions as graduate assistants across research and instruction.

More than 4,000 graduate students serve the campus each year as research, teaching or administrative assistants. The Graduate School established the award to recognize the contributions graduate assistants provide to students, faculty, departments and the university as a whole. Recipients are recognized as being among the top 2% of graduate assistants in a given year.

The research focuses of the awardees are:

Joseph Carolan (Research Assistant): Carolan is a computer science Ph.D. student advised by Professor Andrew Childs. His research studies the theoretical foundations of quantum computing and its implications for cryptography, particularly post-quantum cryptography designed to remain secure in a future with quantum computers. 

“Once I understood that a computer instantiated with quantum particles would be capable of computing things no ordinary computer could, I became obsessed with understanding exactly what,” Carolan said.

Pierce Darragh (Teaching Assistant): Darragh is a computer science Ph.D. student advised by Associate Professor David Van Horn. His research examines the relationship among syntax, type systems and programming ergonomics. He has served as a recurring teaching assistant for CMSC 430, Introduction to Compilers, where students work with unfamiliar codebases and complex programming systems. 

“Serving as a recurring TA has been an incredible opportunity to exercise these interests while developing my own skills in educating and assisting students through a difficult upper-level course,” Darragh said.

Eadom Dessalene (Research Assistant): Dessalene is a computer science Ph.D. student advised by Professor John Aloimonos. Dessalene studies how machines interpret human actions from video by modeling interactions between hands and objects to better understand motion patterns and physical activity. 

“My research focuses on the understanding and organization of physical actions from video,” Dessalene said.

Hiba El Oirghi (Teaching Assistant): El Oirghi is a computer science Ph.D. student advised by Associate Professor Marine Carpuat. Her research focuses on machine translation for low-resource languages and the security of large language models. She has also served as a teaching assistant supporting course assignments and recitations. 

“I TA’d in my first semester at UMD where I enjoyed supporting students and guiding them in their learning journey,” El Oirghi said.

Peyman Jabbarzade (Teaching Assistant): Jabbarzade is a computer science Ph.D. student advised by Professor Mohammad Hajiaghayi. His research focuses on combinatorial optimization, particularly in network design and submodular optimization, examining algorithmic approaches to problems such as Steiner networks. 

“I have always been interested in understanding the limits of algorithms and how mathematical ideas lead to efficient solutions,” Jabbarzade said.

Donghyeon Joo (Research Assistant): Joo is a computer science Ph.D. student advised by Assistant Professor Bahar Asgari. His research studies hardware and software co-design for efficient machine learning systems, including how sparsity in large language models can be induced and exploited across representation, GPU kernels and computer architecture. 

“Witnessing this transformation motivated me to engage in research,” Joo said.

Dayeon Ki (Research Assistant): Ki is a computer science Ph.D. student advised by Associate Professor Marine Carpuat. Her research examines how artificial intelligence mediates communication across languages and cultures by combining methods from natural language processing, human-computer interaction and statistics to evaluate multilingual AI systems and their effects on human decision-making. 

“I learned to ground research questions in real-world challenges and to critically interrogate model behavior rather than passively accepting it,” Ki said.

Sonal Kumar (Research Assistant): Kumar is a computer science Ph.D. student advised by Professors Ramani Duraiswami and Distinguished University Professor Dinesh Manocha. His research focuses on audio-language models, multimodal learning and advanced reasoning in speech and audio processing.

Yonghan Lee (Teaching Assistant): Lee is a computer science Ph.D. student advised by Distinguished University Professor Dinesh Manocha. His research studies dynamic 3D scene reconstruction and motion tracking, with applications in augmented and extended reality and robotics. He has also served as a teaching assistant for CMSC 320, Introduction to Data Science. 

“Serving as a TA taught me a lot by giving me multiple opportunities to collaborate in different roles,” Lee said.

Renata Valieva (Research Assistant): Valieva is a Ph.D. student in the Department of Mathematics who received the award for her work as a research assistant, co-supervised by Distinguished University Professor of Computer Science Aravind Srinivasan. Her research focuses on probability theory and randomized algorithms, exploring how randomness can be used to design efficient computational methods. 

“I’ve always enjoyed challenging problems, and mathematics appealed to me because of its beauty and elegance,” Valieva said.

—Story by Samuel Malede Zewdu, CS Communications