About Me

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I am a researcher passionate about developing responsible AI systems that prioritize privacy, safety, fairness, and factual integrity. My work centers on identifying and mitigating risks in machine learning applications, particularly in critical domains like cybersecurity and healthcare.

I recently earned my PhD at New York University as a Global PhD Fellowship recipient, working with Dr. Christina Pöpper. My research has been recognized with various honors, including a Health Equity & Global Health Best Paper Award at ML4H 2023 and a runner-up for the Andreas Pfitzmann Best Paper Award at PETS 2024. Previously, I gained valuable experience with privacy-enhancing technologies at Spotify Tech Research and the Center for Cyber Security.

I’m always open to collaboration and discussions. So don’t hesitate to reach out if you would like to collaborate, or just talk about life.

Prospective PhD applicants, especially those from underrepresented backgrounds, are more than welcome to email me about questions related to the application process or PhD experience. :)

Recent News

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Aug ‘24: Defended my PhD dissertation, “Towards Responsible AI: Safeguarding Privacy, Integrity, and Fairness.” Grateful for the guidance of my exceptional thesis committee.

Jul ‘24: Received the runner-up award for the Andreas Pfitzmann Best Paper at PETS in Bristol.

May ‘24: Served as Color Guard for NYU Commencement Exercises.

Mar ‘24: Appointed Publication Chair for ACNS 2024 conference.

Dec ‘23: Our work was recognized with the Best Paper Award at Machine Learning for Health conference, co-located with NeurIPS.

Jun ‘23: Engaged with the UN Information Integrity team to address online hate speech risks.

May ‘23: Served in the Program Committee for SecWeb 2023.

Feb ‘23: Invited to speak at the Microsoft Research (MSR) Colloquium about my research on threat modeling of disinformation campaigns.

Select Publications

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CodexLeaks: Privacy Leaks from Code Generation Language Models in GitHub Copilot
USENIX Security Symposium, Anaheim, US, 2023.

Tactics, Threats & Targets: Modeling Disinformation and its Mitigation
Network and Distributed System Security, San Diego, US, 2023.

How Fair are Medical Imaging Foundation Models?
Machine Learning for Health (ML4H), New Orleans, US, 2023.

Unraveling a Decade of Privacy Discourse around the World.
Privacy Enhancing Technologies (PETS), Bristol, UK, 2024

Global-Liar: Factuality of LLMs over Time and Geographic Regions
In Submission, 2024

Detailed list of publications can be found at Google Scholar.

Previously

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I got a B.S. in Computer Science from NYU Abu Dhabi, where my capstone project was on Reimagining Privacy in Online Social Networks. During high school, I represented the national team in International Chemistry Olympiad.