About me

I am a final-year computer science Ph.D. candidate at Northeastern University, affiliated with the Network Science Institute and advised by Professor Tina Eliassi-Rad. My research interests lie at the intersection of graph machine learning, algorithmic fairness, and the societal impact of AI. I am supported by the NSF GRFP.

In August 2025, I will begin as an Assistant Research Professor (postdoc) at Cornell mentored by Professors Moon Duchin and Jon Kleinberg.

My research aims to improve the trustworthiness of machine learning applied to complex systems. I focus on developing representation learning that is efficient, stable, and fair.

I have worked as a sociotechnical researcher at Taraaz, collaborating on projects on human-rights impact assessments and AI procurement.

I have interned at Meta Central Applied Science (CAS) and FAIR AI and was previously a software engineer at Bloomberg LP. I graduated from Princeton University with a concentration in Computer Science and a certificate in Statistics and Machine Learning.

News

• [Nov ‘24] I will give a talk at Brown University’s CNTR. My slides are available here.
• [May ‘24] New preprint on negative sampling.
• [Feb ‘24] I presented a talk titled “Toward Understanding Mechanisms of Unfairness and Moving Beyond Demographic Attributes” at the MSR New England ML Ideas Seminar. My slides are available here.
• [Feb ‘24] This summer I will be a PhD Research Scientist Intern on the Graph Science and Statistics Research team at Meta Central Applied Science (CAS) in Menlo Park.
• [Jan ‘24] This spring I am the Instructor of Record for Introduction to Machine Learning and Data Mining (DS 4400) at Northeastern.