Alyssa Unell

I'm Alyssa, a Computer Science PhD student at Stanford advised by Professor Sanmi Koyejo and Professor Nigam H Shah. My research generally focuses on trustworthy evaluations of AI for medical applications. I previously worked with Professor Serena Yeung on VLM generalization and biomedical dataset creation and with Professor Chis Ré on the capabilities of language models to perform acts of long context retrieval. Additionally, I have worked with Microsoft Research's Real World Evidence Group to evaluate calibration methods for model capabilities in data-sparse settings.

Prior to beginning my PhD at Stanford, I graduated from MIT with a degree in Computation and Cognition. I was extremely fortunate to receive amazing mentorship throughout my undergraduate experience. I worked with Professor Pawan Sinha, Dr. Kyle Keane, and Dr. Xavier Boix Boisch within the MIT Quest for Intelligence.

I worked with Professor Martin Jaggi and Dr. Annie Hartley in the Machine Learning Optimization Lab where we explored the implementation of federated learning architecture for secure medical information sharing.

I have also had the privilege to work with Professor Polina Golland on projects relating to the use of generative AI for improving MRI acquisitions. Additionally, I have worked as a Machine Learning Intern for Intel serving to improve their optimization software.

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