Sarah H. Cen
I am a final-year Ph.D. student (MIT EECS) advised by Prof. Aleksander Mądry and Prof. Devavrat Shah, and I am on the job market this Fall 2023. My research lies at the intersection of machine learning theory and AI accountability. Specifically, I am interested in the design and governance of data-driven algorithms. By "design," I mean how we can better devise algorithms that work well when interfacing with humans. I enjoy tackling this line of work using tools from statistics, causal inference, and game theory. By "governance," I mean how human-facing algorithms are regulated, how algorithmic governance should inform algorithm design, and how we can develop tools for governance (e.g., auditing).
Recently, I have written on the regulation and auditing of social media algorithms; the emergence of AI supply chains; the estimation of counterfactual potential outcomes under spillover effects; how competing for resources under uncertainty affects long-term outcomes; and individual-level rights of data-driven decision subjects. Previously, I worked in intelligent transportation, communication networks, reinforcement learning, and robotics. During my master's, I performed research on autonomous vehicles (a.k.a. self-driving cars) with Prof. Paul Newman at the Unversity of Oxford. As an undergraduate, I studied control & decision systems with Prof. Naomi Leonard at Princeton University.
Please find my C.V. here.
Recent updates:
- Working on auditing! Feel free to reach out if AI auditing, compliance assessments, or diligence testing interests you.
- Publishing blogs on AI policy here: aipolicy.substack.com.
- Speaking at INFORMS and CODE.