Sikha Pentyala

Sikha Pentyala

Postdoctoral Researcher
UW eScience Institute  ·  University of Washington Tacoma

I am a postdoctoral researcher at the University of Washington eScience Institute and University of Washington Tacoma, focusing on privacy-preserving synthetic genomics data generation. My research interests are broadly in Responsible and Trustworthy AI.

I earned my Ph.D. in Computer Science in June 2025 with a thesis titled "Enhancing Privacy in AI: Differential Privacy in Multiparty Computation", advised by Dr. Martine De Cock and Dr. Anderson Nascimento in the School of Engineering and Technology at UW Tacoma. Prior to my PhD, I earned my M.S. in Computer Science & Systems from UW Tacoma (2020), with a thesis on privacy-preserving video classification.

I interned at Mila – Québec AI Institute as Research Intern (Fall 2021 - Winter 2022 and Summer 2022) under Dr. Golnoosh Farnadi. I also interned at JPMorgan Chase as an AI Research Associate (Summer 2023 and Summer 2024), and was awarded the 2023 JP Morgan Chase PhD Fellowship for my research on synthetic data generation. Before joining UW Tacoma, I spent 7 years in the Nuclear Power Corporation of India Ltd in the role of Scientific Officer, following my Bachelor's degree (Gold Medalist) from Jawaharlal Nehru Technological University Anantapur in 2009.

Privacy in AI Synthetic Data Generation Secure Multiparty Computation Responsible and Trustworthy AI AI in Healthcare

News

Feb 2026 Talk (Upcoming) Invited talk on "Illuminating Dark Data: Privacy-Preserving AI in Distributed Data Silos" at University of Central Florida, April 2026 .
Feb 2026 Talk (Upcoming) Invited talk on "Privacy-Preserving Genomics Data Sharing on the NAIRR" at National AI Research Resource, Annual Meeting, March 2026 .
Jul 2025 Poster Two papers on synthetic RNA-seq and scRNA data generation presented at ISMB/ECCB 2025.
Jul 2025 Position Started as UW Data Science Postdoctoral Fellow at the eScience Institute.
Jun 2025 Talk Invited talk on "Privacy-preserving Synthetic Data Generation for NF1" at Children's Tumor Foundation Data Workshop / NF Conference.

Research Directions

My research builds toward Responsible and Trustworthy AI — work spans four directions:

→ Overview on ongoing projects

Selected Publications

CaPS paper
ICML 2024  ·  28% acceptance
CaPS: Collaborative and Private Synthetic Data Generation from Distributed Sources
S. Pentyala, M. Pereira, M. De Cock
Synthetic Data Generation
Fairness paper
PMLR 2025  ·  16% acceptance
Privacy-Preserving Group Fairness in Cross-Device Federated Learning
S. Pentyala, N. Neophytou, A. Nascimento, M. De Cock, G. Farnadi
Fairness
ICML 2021 paper
ICML 2021  ·  21% acceptance
Privacy-Preserving Video Classification with Convolutional Neural Networks
S. Pentyala, R. Dowsley, M. De Cock
Privacy in AI

Full publication list → includes + 2 patents  ·  publications in SatML, ECIR, PoPETS, PLOS  ·  10+ workshops at NeurIPS, AAAI, ICAIF, ISMB  · 

Selected Awards

🥈
U.S.–U.K. PETs Prize Challenge
2nd Prize, Phase 2 Track A  ·  Announced at the White House  ·  2023
🎓
JP Morgan Chase PhD Fellowship
Research on synthetic data generation  ·  2023
🎖
UPE Executive Council Award
UPE International Honor Society for Computing  ·  2023
🎓
Carwein-Andrews Distinguished Fellowship
UW Tacoma  ·  2023–2024