Saswat Das

Saswat Das

PhD Student in Computer Science

SEAS, University of Virginia

About Me

I am a PhD student at the Department of Computer Science of the University of Virginia (UVA), where I am fortunate to be advised by Dr. Ferdinando Fioretto as a member of the RAISE Lab. My research interests are broadly situated within the fascinating area of trustworthy/responsible AI; more precisely, these include differential privacy, contextual integrity, agentic AI alignment (including single- and multi-agent systems), algorithmic fairness, and adversarial robustness.

Prior to this, I pursued an Integrated M.Sc. (BS+MS) degree at the National Institute of Science Education and Research (NISER) with a major in Mathematics and a minor in Computer Science, and was a student researcher at the School of Computer Sciences at NISER (2021-2023). I also spent the summer and fall of 2025 interning at the Pacific Northwest National Laboratory.

I’m open to research internship opportunities and collaborations in AI safety, privacy, responsible AI, and agentic LLMs!

Interests
  • Differential Privacy
  • Privacy-Preserving and Fair Machine Learning
  • Trustworthy AI
  • Cryptography/Security
  • Agentic LLMs
Education
  • PhD (Computer Science), 2023 - Present

    SEAS, University of Virginia

  • Integrated M.Sc. (BS+MS) (Mathematics Major and Computer Science Minor), 2018 - 23

    National Institute of Science Education and Research, HBNI

Recent News

All news»

May 2026: Received the Gold Reviewer Award for my service at ICML-26! Thanks, ICML!

Feb 2026: New preprint on “Colosseum: Auditing Collusion in Cooperative Multi-Agent Systems” available on arXiv!

Jan 2026: New preprint on “NeuroFilter: Privacy Guardrails for Conversational LLM Agents” available on arXiv!

Sep 2025: Paper on “Beyond Jailbreaking: Auditing Contextual Privacy in LLM Agents” accepted to the Multi-Turn Interaction (MTI-LLM) Workshop at NeurIPS 2025!

May 2025: New preprint on “Beyond Jailbreaking: Auditing Contextual Privacy in LLM Agents” out on arXiv!

Experience

 
 
 
 
 
SEAS, University of Virginia
PhD Student
Aug 2023 – Present Charlottesville, VA, USA
 
 
 
 
 
Pacific Northwest National Laboratory
PhD Intern
Jul 2025 – Dec 2025 Charlottesville, VA, USA (Remote)
 
 
 
 
 
EECS, Syracuse University
Visiting Research Scholar/Collaborator
Jun 2022 – May 2023 Syracuse, NY, USA
 
 
 
 
 
SM Lab, NISER, HBNI
Student Researcher
Mar 2021 – May 2023 Odisha, IN
 
 
 
 
 
School of Computer Sciences, NISER, HBNI
Winter Intern
School of Computer Sciences, NISER, HBNI
Dec 2019 – Jan 2020 Odisha, IN
 
 
 
 
 
School of Computer Sciences, NISER, HBNI
Summer Intern
School of Computer Sciences, NISER, HBNI
May 2019 – Jul 2019 Odisha, IN

Articles, Book Chapters, and Publications

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(2026). Colosseum: Auditing Collusion in Cooperative Multi-Agent Systems. arXiv:2602.15198.

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(2026). NeuroFilter: Privacy Guardrails for Conversational LLM Agents. arXiv:2601.14660.

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(2025). Beyond Jailbreaking: Auditing Contextual Privacy in LLM Agents. MTI-LLM @ NeurIPS-25.

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(2024). Fairness Issues and Mitigations in (Differentially Private) Socio-demographic Data Processes. AAAI-25 (Oral).

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(2024). Low-rank finetuning for LLMs: A fairness perspective. CoLoRAI @ AAAI-25 (🏆 Best Paper).

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(2024). Disparate Impact on Group Accuracy of Linearization for Private Inference. ICML-24.

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(2023). Finding ε and δ of Statistical Disclosure Control Systems. AAAI-24.

PDF Cite Poster DOI

(2023). Advances in Differential Privacy and Differentially Private Machine Learning - A Survey. In Information Technology Security (Springer Nature).

DOI

(2022). Fair Context-Aware Privacy Threat Modelling. In WPTM 2022, USENIX.

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