Sikha Pentyala
I am an Assistant Professor (tenure-track) at the School of Engineering & Technology, University of Washington (UW) Tacoma. I am an affiliated member of the eScience Institute at UW Seattle and Responsible Health AI Lab (RHAIL) at UW Tacoma. I am also a member of Privacy Preserving Machine Learning (PPML) Lab at UW Tacoma.
My research focus is on responsible and trustworthy AI. Most of my past and current work is on privacy-preserving synthetic data generation, on auditing AI systems for privacy, and on applying both in healthcare and genomics.
I am currently appointed as Staff Research Scientist at the UW School of Nursing. From July 2025 to July 2026, I was a Postdoctoral Researcher at the UW eScience Institute and UW Tacoma. I completed my Ph.D. at UW Tacoma in 2025, advised by Martine De Cock and Anderson Nascimento. I had the oppurtunity to intern at Mila – Québec AI Institute as Research Intern (Fall 2021 - Winter 2022 and Summer 2022) under Dr. Golnoosh Farnadi and at JPMorgan Chase as an AI Research Associate (Summer 2023 and Summer 2024). I was awarded the 2023 JP Morgan Chase PhD Fellowship for my research on synthetic data generation. Before graduate school I spent seven years as a Scientific Officer at the Nuclear Power Corporation of India.
News
Research Directions
My research builds toward Responsible and Trustworthy AI. My work spans four directions:
- Synthetic Data & Digital Twins — generating privacy-preserving (tabular) synthetic datasets, longitudinal synthetic datasets, multimodal synthetic datasets, and constructing digital twins for simulation and analysis
- Auditing & Assurance and Safety — auditing AI systems across the pillars of trustworthiness (fairness, privacy, robustness, transparency and safety) and developing methods to achieve them
- Privacy & Context — grounding privacy and fairness guarantees in social and situational context; bridging formal methods with human norms, with growing emphasis on agentic AI systems where contextual boundaries are dynamic
- AI for Good — applying AI to high-impact domains including healthcare (clinical NLP, synthetic data, digital twins) and education (LLM-assisted learning and personalization)
Selected Publications
Full list on the publications page or Google Scholar.