Two ECE Ph.D. Students Receive Ann G. Wylie Dissertation Fellowships

Two Ph.D. students from the Department of Electrical and Computer Engineering (ECE) have been named recipients of the University of Maryland 2025-2026 Ann G. Wylie Dissertation Fellowship. Sponsored by the UMD Graduate School, the fellowship provides financial support to UMD doctoral candidates who are in the latter stages of writing their dissertations.

Sagnik Bhattacharya joined the ECE Department in 2019, after receiving a B.Tech degree in Electrical Engineering with minors in Physics and Computer Science from the Indian Institute of Technology Kanpur, India. As an undergraduate, he received the 2016 Academic Excellence award and the 2019 Best Undergraduate Project award in the Department of Electrical Engineering.

At UMD, he has been recognized with an ECE Outstanding Teaching Assistant Award in 2024, a 2019 Future Faculty Fellowship, and the 2019 Dean’s Fellowship. He is advised by Professor Prakash Narayan.

Bhattacharya’s research focuses on the intersection of randomized sampling in graphical models, network secret key agreement, data compression, correlated bandits, and quantum entanglement. His studies have benefited classical and quantum systems through the development of novel information-theoretic bounds that contribute to the full impact of compression and inference, as well as improving the upper bounds on multiterminal quantum entanglement. He has also discovered formulae for shared information in non-tree graphs which allow efficient estimation algorithms and sequential bandit algorithms in order to estimate shared information in trees.

During the summer of 2023, Bhattacharya was a research engineer intern for Kaleidoscope Blockchain, where he worked on location estimation problems for Internet security applications.

Faisal Hamman has recently completed his Ph.D. in electrical engineering from the ECE Department. He joined ECE in 2020, after earning a Bsc in Electrical and Electronics Engineering from Işık University in Istanbul, Turkey. He is advised by Professor Sanghamitra Dutta.

Through his years in ECE, he has served as a Graduate Student Representative on the General Academic Affairs Committee and as a board member of the ECE Graduate. He co-organized the AI Alignment Workshop with the Artificial Intelligence Interdisciplinary Institute at Maryland (AIM UMD), an event that focused on building safe and value-aligned AI systems and united experts from academic, industry, government, and non-profits. As an advocate for STEM education, he has worked with high school students through hands-on projects in explainable AI.

While at UMD, Hamman has received the ECE Ph.D. Distinguished Dissertation Fellowship Award, the George Corcoran Memorial Award for Excellence in Teaching, and multiple Outstanding Teaching Assistant Awards. He is a Teaching Assistant Training and Development Fellow for the ECE Department.

Hamman has successfully defended his Ph.D. Dissertation, titled Trustworthy and Explainable Machine Learning Using Information-Theoretic Methods. His research has focused on trustworthy and reliable machine learning, with an emphasis on uncertainty quantification, knowledge distillation, and long-context understanding in large language models (LLMs).

Through his research, Hamman seeks to improve the transparency and safe deployment of artificial intelligence systems and foster trust in critical applications. He has applied his research through industry internships at Capital One and J.P. Morgan AI Research, focusing on improving the reliability of large-scale AI systems in high stakes applications.

Published January 23, 2026