Alyssa Unell

I'm Alyssa, a second year PhD student at Stanford studying Computer Science. I am advised by Professor Sanmi Koyejo and Professor Nigam Shah. My general interests include the ability to improve robustness and reliability in machine learning with applications in healthcare and medical research. 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.

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 acquistions. Additionally, I have worked as a Machine Learning Intern for Intel serving to improve their optimization software.

aunell@stanford.edu  /  CV  /  LinkedIn  /  Github  /  Twitter

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Research
1. Why are Visually-Grounded Language Models Bad at Image Classification?
Yuhui Zhang, Alyssa Unell, Xiaohan Wang, Dhruba Ghosh, Yuchang Su, Ludwig Schmidt, Serena Yeung-Levy
Conference on Neural Information Processing Systems, 2024
2. µ-BENCH: VISION-LANGUAGE BENCHMARK FOR MICROSCOPY UNDERSTANDING
Alejandro Lozano, Jeffrey Nirschl, James Burgess, Sanket Rajan Gupte, Yuhui Zhang, Alyssa Unell, Serena Yeung-Levy
Conference on Neural Information Processing Systems Datasets and Benchmarks Track, 2024
3. Feasibility of Automatically Detecting Practice of Race-Based Medicine by Large Language Models
Akshay Swaminathan, Sid Salvi, Philip Chung, Alison Callahan, Suhana Bedi, Alyssa Unell, Mehr Kashyap, Roxana Daneshjou, Nigam Shah, Dev Dash
AAAI 2024 Spring Symposium on Clinical Foundation Models
4. From Clear to Noise: Investigating Neural Noise Progression in Visual System Robustness
Hojin Jang, Alyssa Unell, Suayb Arslan, Walt Dixon, Michael Fux, Matt Groth, Joydeep Munshi & Pawan Sinha
Vision Sciences Society Poster Session, 2024
5. Transformation Tolerance of Machine-based Face Recognition Systems
Ashika Verma, Kyle Keane, Alyssa Unell, Anna Musser & Pawan Sinha
Poster Presentation at the ICLR 2021 Generalization Beyond the Training Distribution in Brains and Machines Workshop
6. Influence of Visual Feedback Persistence on Visuo-Motor Skill Improvement
Alyssa Unell, Zachary M. Eisenstat, Ainsley Braun, Abhinav Gandhi, Sharon Gilad-Gutnick, Shlomit Ben-Ami & Pawan Sinha
Nature Scientific Reports, 2021
Open-Source Contributions
1. Distributed Collaborative Learning (DisCo)
Added security guarantees to the DisCo platform that allows clients to securely train models in a decentralized fashion.