Imperial College London
Analytics & Operations, Imperial College Business School
Computational Optimization Group, Department of Computing

Contact: a[dot][last name]19@imperial.ac.uk

Address: ICBS E3.02, SW7 2AZ, London, UK

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Welcome to my page!

I am a doctoral candidate at Imperial College Business School where I am fortunate to be advised by Wolfram Wiesemann as a member of the Analytics & Operations group. I am also affiliated with the Computational Optimization Group and the Data Science Institute of Imperial College London. I have recently completed a PhD placement at The Alan Turing Institute as a part of the Enrichment Scheme and a PhD AI Research Associate Internship at J.P. Morgan.

In Fall 2026, I will start as an Assistant Professor of Operations & Technology at the UCL School of Management. Prior to that, during the 2025-2026 academic year, I will be a Postdoctoral Research Associate at Princeton University ORFE, mentored by Bartolomeo Stellato!

My research interests are the theory of data-driven decision making under uncertainty and its applications in machine learning, privacy, and fairness. In my recent works, I have been working on designing optimal privacy mechanisms, developing efficient algorithms for robust machine learning, as well as approximating hard decision making problems via robust optimization.

News

  • Apr 2025An extended abstract of our working paper "Optimal and fair housing allocation via weakly coupled Markov decision processes" is accepted for presentation at the MSOM Conference 2025 (London).
  • Apr 2025I will present a new, near-optimal mechanism for differential privacy at the Euro OSS on OR & ML.
  • Apr 2025We updated our work "It's all in the mix: Wasserstein classification and regression with mixed features". We substantially generalized our previous results, including the absence of a regularization reformulation of Wasserstein DRO when discrete features are present.