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). I am fortunate to be advised by Dr. Ferdinando Fioretto as a member of the RAISE Group at UVA. My research interests are broadly situated within the fascinating area of trustworthy/responsible AI; more precisely, these include differential privacy, algorithmic fairness, adversarial robustness. I am also interested in cryptography and topics related to security.

Prior to this, I pursued an Integrated M.Sc. (BS+MS) degree at the National Institute of Science Education and Research (NISER), an off-campus centre of Homi Bhabha National Institute, India, with a major in Mathematics and a minor in Computer Science. I also was a student researcher at the School of Computer Sciences at NISER (2021-2023).

Reach out to me anytime for discussing ideas, regarding opportunities and to give talks on my research. I’m open to research internship opportunities and collaborations in general!

Interests
  • Differential Privacy
  • Privacy-Preserving and Fair Machine Learning
  • Trustworthy AI
  • Cryptography/Security
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 2024: Selected to participate in the AI-SCORE (Artificial Intelligence School for Computer Science and Operations Research Education) Summer School in DC.

May 2024: Paper accepted at ICML-24: “Disparate Impact on Group Accuracy of Linearization for Private Inference”

Jan 2024: New preprint on the “Disparate Impact on Group Accuracy of Linearization for Private Inference” out on ArXiV.

Dec 2023: Accepted to the AAAI-24 Student Scholarship Program and got offered a grant for attending AAAI-24. Thanks, AAAI!

Dec 2023: I will deliver a student talk at the NIST CRC Workshop on the privacy and fairness of Census data releases.

Experience

 
 
 
 
 
SEAS, University of Virginia
PhD Student
Aug 2023 – Present Charlottesville, VA, USA
 
 
 
 
 
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
 
 
 
 
 
Stanford University
Section Leader, CodeInPlace
Stanford University
Apr 2021 – May 2020
 
 
 
 
 
Technion - Israel Institute of Technology
Attendee, Summer School on Computer & Cyber Security
Technion - Israel Institute of Technology
Sep 2020 – Sep 2020
 
 
 
 
 
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

Quickly discover relevant content by filtering publications.
(2024). Disparate Impact on Group Accuracy of Linearization for Private Inference. ICML-24.

PDF Cite

(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.

PDF Cite

Contact