I am a fourth year PhD student advised by Dr. Martine De Cock and Dr. Anderson Nascimento in the School of Engineering and Technology at the University of Washington Tacoma. I am a Graduate Research Assistant in the Privacy-Preserving Machine learning group. I am broadly interested in Trustworthy Machine Learning. Currently, my research focuses on privacy-preserving machine learning and fairness in machine learning.

I earned my Masters in Computer Science & Systems from University of Washington Tacoma in 2020 with a thesis on privacy-preserving video classification that was nominated for the UW Distinguished Thesis award. I then briefly worked as a Research Intern at MILA under the supervision of Dr. Golnoosh Farnadi. I interned at JPMorgan Chase as an AI Research Associate in Summer 2023 and have been awarded 2023 JP Morgan Chase Fellowship to support PhD research on synthetic data generation. I will be interning at JPMorgan Chase in Summer 2024. Prior to starting at UW Tacoma, I spent a few years in the Nuclear Power Generation industry as an IT administrator after receiving my Bachelors from JawaharLal Nehru Technological University Anantapur in 2009.

• S. Pentyala, M. Pereira, & M. De Cock (2024). CaPS: Collaborative and Private Synthetic Data Generation from Distributed Sources, To appear in: Proceedings of the 41st International Conference on Machine Learning, 2024.
• S. Golob, S. Pentyala, R. Dowsley, B. David, M. Larangeira, M. De Cock, A. Nascimento A Decentralized Information Marketplace Preserving Input and Output Privacy , Proceedings of the 2nd Data Economy Workshop (DEC23) - SIGMOD 2023 workshop, 2023.
• J. Sun, S. Pentyala, M. De Cock, G. Farnadi Privacy-Preserving Fair Item Ranking , 45th European Conference on Information Retrieval 2023. (Paper )
• S. Pentyala, N. Neophytou, A. Nascimento, M. De Cock, G. Farnadi Privacy-Preserving Group Fairness in Cross-Device Federated Learning , In Proceedings of Algorithmic Fairness through the Lens of Causality and Privacy (AFCP2022) - NeurIPS 2022 workshop. (arXiv)
• S. Pentyala, R. Dowsley and M. De Cock Privacy-Preserving Video Classification with Convolutional Neural Networks, In Proceedings of the 38th International Conference on Machine Learning, PMLR 139, 2021. (HTML, Poster, Talk)
• F. Tabet and S. Pentyala, B. Patel, et al. OSMRunner: A System for Exploring and Fixing OSM Connectivity, 22nd IEEE International Conference on Mobile Data Management (MDM) 2021. (HTML, Talk)

• R.J.M. Maia, D. Ray, S. Pentyala, R. Dowsley, M. De Cock, A. Nascimento and R. Jacobi. ,An End-to-End Framework for Private DGA Detection as a Service, To appear in PLOS ONE 2024.
• J. Vos, S. Pentyala et al. Privacy-Preserving Membership Queries for Federated Anomaly Detection, To appear in: PoPETS 2024(3), 2024

• S. Golob, S. Pentyala, A. Maratkhan, M. De Cock High Epsilon Synthetic Data Vulnerabilities in MST and PrivBayes AAAI-24 Workshop on Privacy-Preserving Artificial Intelligence, 2024.
• S. Pentyala, S. Sharma, S. Kariyappa, F. Leuce and D. Magazzeni Privacy-Preserving Algorithmic Recourse, 3rd International Workshop on Explainable AI in Finance, ICAIF 2023.
• M. Pereira, S. Pentyala, A. Nascimento, R. T. de Sousa Jr., M. De Cock Secure Multiparty Computation for Synthetic Data Generation from Distributed Data , SyntheticData4ML Workshop, NeurIPS, 2022. (Poster, PDF,Talk)
• S. Pentyala, D. Melanson, M. De Cock, G. Farnadi PrivFair: a Library for Privacy-Preserving Fairness Auditing, AAAI-22 Workshop on Privacy-Preserving Artificial Intelligence, 2022. (arXiv, PDF, Talk)
• S. Pentyala, M. De Cock and R. Dowsley Privacy-Preserving Video Classification, Women in Computer Vision Workshop at CVPR, 2021. (Poster)

• S. Pentyala, D. Railsback, R. Maia, R. Dowsley, D. Melanson, A. Nascimento, M. De Cock Training Differentially Private Models with Secure Multiparty Computation (arXiv)

• S. Pentyala, N. Neophytou, A. Nascimento, M. De Cock, G. Farnadi PrivFairFL: Privacy-Preserving Group Fairness in Federated Learning, Montreal AI Symposium 2022 Poster
• S. Pentyala, N. Neophytou, A. Nascimento, M. De Cock, G. Farnadi Towards Private and Fair Federated Learning , Women in Machine Learning (WiML) workshop at NeurIPS2022

• 2023-2024 School of Engineering & Technology’s Outstanding Student Leadership Award
• Carwein-Andrews Endowment for Graduate Programs for the Spring quarter of 2024
• 2023 UPE Executive Council Award by UPE International Honor Society for the Computing and Information Disciplines
• Recipient of 2023 JP Morgan Chase Fellowship to support PhD research on synthetic data generation
• 2023 Andrew and Julie Fry Innovation Award, UW Tacoma
• 2022-2023 School of Engineering & Technology’s Student Justice Equity Diversity & Inclusion Award, UW Tacoma
• 2022-2023 School of Engineering & Technology’s Outstanding Graduate Research Award, UW Tacoma
• Our Team PPMLHuskies won 2nd award in the U.S-U.K. PETs Prize Challenges
• WiML travel award to present work on private and fair federated learning at WiML@NeurIPS 2022
• Carwein-Andrews Endowment award for 2022-2023
• 2021-2022 School of Engineering & Technology’s Outstanding Graduate Research Award, Univeristy of Washington Tacoma. (CERT)
• Winner of Track III of the iDASH2021 secure genome analysis competition. (HTML)
• Gold Medalist at Jawaharlal Nehru Technological University, Anantapur in the Branch of ECM, Class of 2009. (CERT)

• Spring 2023: Pre-doctoral Instructor for TCSS 143 (Fundamentals of Object-Oriented Programming)
• Winter 2023: Pre-doctoral Instructor for TCSS 143 (Fundamentals of Object-Oriented Programming)

• Sub-Reviewer for ECAI 2023
• Reviewer for SyntheticData4ML Workshop@NeurIPS 2023
• Invited talk on 2023 WiDS celebration at UW Tacoma
• Reviewer for International Journal of Information Management
• Reviewer for IEEE Transactions on Neural Networks and Learning Systems
• Reviewer for IEEE Transactions on Dependable and Secure Computing
• Roundtable Lead on Privacy at the Algorithmic Fairness through the Lens of Causality and Privacy (AFCP2022) Workshop, NeurIPS 2022
• Sub-Reviewer for NeurIPS 2022
• Reviewer for SyntheticData4ML Workshop@NeurIPS 2022