Anshuman Suri

San Francisco, CA

I recently joined as a Member of Technical Staff at DatologyAI! Previously, I was a postdoctoral fellow at Northeastern University, supervised by Alina Oprea. I obtained my PhD from University of Virginia, where I was extremely fortunate to be advised by Professor David Evans.

During my time in academia, I studied the privacy and security challenges of machine learning models, both as targets of attacks and as amplifiers of risk; exploring how models can be exploited and how they transform the security landscape of systems that use them.

news

Jul 25, 2025	Awarded Lambda Research Grant to work on training-time poisoning defenses for LLMs. Thank you, Lambda!
Jan 24, 2025	Our blogpost talking about critical flaws in the evaluation of a recent EMNLP best-paper has been accepted to the ICLR blogpost track!
Nov 14, 2024	UVA Engineering covered a story on our work on evaluating Membership Inference Attacks on Large Language Models?.
Oct 30, 2024	My first patent was just issued! This is based on work that our team did during my internship at Oracle Research back in Fall 2021. Patents sure are slow!
Oct 08, 2024	Presented our work Do Membership Inference Attacks Work on Large Language Models? at COLM in Philadelphia .

latest posts

Jul 17, 2025	Advice for working on ML projects
Nov 26, 2024	Reassessing EMNLP 2024’s Best Paper: Does Divergence-Based Calibration for Membership Inference Attacks Hold Up?
Nov 12, 2024	My submission to the ETI Challenge

selected publications

Toward Principled LLM Safety Testing: Solving the Jailbreak Oracle Problem

Shuyi Lin, Anshuman Suri, Alina Oprea, and Cheng Tan

In Proceedings of Machine Learning and Systems (MLSys), 2026

Bib PDF

@inproceedings{lin2026toward,
  title = {Toward Principled LLM Safety Testing: Solving the Jailbreak Oracle Problem},
  author = {Lin, Shuyi and Suri, Anshuman and Oprea, Alina and Tan, Cheng},
  booktitle = {Proceedings of Machine Learning and Systems (MLSys)},
  year = {2026}
}

Exploiting Leaderboards for Large-Scale Distribution of Malicious Models

Anshuman Suri^*, Harsh Chaudhari^*, Yuefeng Peng^*, Ali Naseh^*, and 2 more authors

In IEEE Symposium on Security and Privacy (S&P), 2026

Bib PDF Code

@inproceedings{suri2026exploiting,
  title = {Exploiting Leaderboards for Large-Scale Distribution of Malicious Models},
  author = {Suri, Anshuman and Chaudhari, Harsh and Peng, Yuefeng and Naseh, Ali and Oprea, Alina and Houmansadr, Amir},
  booktitle = {IEEE Symposium on Security and Privacy (S&P)},
  year = {2026}
}

SAGA: A Security Architecture for Governing AI Agentic Systems

Georgios Syros, Anshuman Suri, Jacob Ginesin, Cristina Nita-Rotaru, and 1 more author

In Network and Distributed System Security (NDSS) Symposium, 2026

Bib PDF Code

@inproceedings{syros2026saga,
  title = {SAGA: A Security Architecture for Governing AI Agentic Systems},
  author = {Syros, Georgios and Suri, Anshuman and Ginesin, Jacob and Nita-Rotaru, Cristina and Oprea, Alina},
  booktitle = {Network and Distributed System Security (NDSS) Symposium},
  year = {2026}
}

Do Parameters Reveal More than Loss for Membership Inference?

Anshuman Suri, Xiao Zhang, and David Evans

Transactions on Machine Learning Research (TMLR), 2024

Bib PDF Code

@article{suri2024do,
  title = {Do Parameters Reveal More than Loss for Membership Inference?},
  author = {Suri, Anshuman and Zhang, Xiao and Evans, David},
  journal = {Transactions on Machine Learning Research (TMLR)},
  year = {2024},
  url = {https://arxiv.org/abs/2406.11544},
}