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Wannan (Winnie) Yang
Welcome to My Corner of the Web! 👋
I’m Winnie, a PhD candidate at New York University (NYU).
My work spans from biological brains (my works were recently published in Science and Nature) to autonomous LLM research agents (current research at Meta). I’ve spent years understanding biological learning machines and currently building artificial ones. The brain taught me how intelligence works. AI taught me how to build it.
Current Focus
My current interests include:
- Open-endedness: Evolving self-improving LLM Coding Agent using evolutionary algorithm (collaborating with Jenny Zhang)
- AI Research Scientist: In November 2025, I will join the AIRA Team at FAIR as a student researcher (manager: Yoram Bachrach), building toward a fully automated AI research scientist.
- LLM Interpretability and Alignemnt: During my internship at Meta, I have developed an effiicient agorithm to reduce hallucination in LLMs, leveraging interpretability insights (Preprint).
Past Research Highlight
In early 2024 I was beginning my transition from Neuroscience to AI. By then, progress in AI for several years had already exploded in a myriad of promise and hope. But what struck me in 2024 was that the rate of progress. In order for humanity to benefit from the plethora of benefits that AI brings, we must make sure the system is aligned, and we must build such safe systems now.
One area, for instance, that I have worked on is to monitor and characterize deception in LLMs (Preprint).
Within the broad goal of helping superalignment, I am interested in research revolving around building automated alignment research assistants.