Payel Bhattacharjee (She/Her)

Ph.D. Candidate

Electrical and Computer Engineering

The University of Arizona

I am a Ph.D. candidate in the Department of Electrical and Computer Engineering at the University of Arizona, advised by Dr. Ravi Tandon. My research focuses on trustworthy and efficient machine learning, with an emphasis on large language model alignment, reward modeling, differential privacy, causal inference, causal graph discovery, and privacy-preserving AI.

My work develops principled methods for building AI systems that are reliable, privacy-preserving, interpretable, and aligned with human preferences. I am particularly interested in the intersection of generative AI, trustworthy machine learning, and causal reasoning, with applications to natural language processing, healthcare AI, and high-stakes decision-making.

Prior to joining the University of Arizona, I worked as an Associate Software Engineer at Bosch Global Software Technologies. I received my B.Tech. in Electronics and Telecommunication Engineering from Kalinga Institute of Industrial Technology (KIIT University), Bhubaneswar, India.

Research Interests

Trustworthy AI; large language model alignment; reward modeling; differential privacy; causal machine learning; privacy-preserving machine learning; generative AI; natural language processing; healthcare AI.

Recent News

IEEE Access 2026: Our work Learning to Diagnose Privately: DP-Powered LLMs for Radiology Report Classification was accepted in IEEE Access.

EACL 2026: Our work STAMP: Selective Task-Aware Mechanism for Text Privacy was accepted to EACL 2026.

NeurIPS 2025 AI4NextG Workshop: Our work Conformal Sparsification for Bandwidth-Efficient Edge-Cloud Speculative Decoding was accepted to the AI4NextG workshop.

TMLR 2025: Our work PROPS: Progressively Private Self-alignment of Large Language Models was published in Transactions on Machine Learning Research.

ECE Graduate Poster Symposium 2024: Received the People's Choice Award for presenting CURATE: Scaling up Differentially Private Causal Graph Discovery.

Awards and Service

People's Choice Award, ECE Graduate Poster Symposium 2024, University of Arizona, for the research presentation CURATE: Scaling up Differentially Private Causal Graph Discovery.

Officer, University of Arizona ECE Graduate Student Association, 2024–Present.

KIIT Merit Scholarship, Kalinga Institute of Industrial Technology, for obtaining the highest CGPA (10.0/10.0) in the academic year 2017–2018.