Alejandro Buendia

Hello! I am a first-year PhD student in the Department of Biomedical Data Science at Stanford University. Previously I was a computational research lab manager in the Rabadan Lab at the Columbia University Irving Medical Center, a research engineer in the Clinical Machine Learning Group at MIT CSAIL, and a data scientist at Microsoft New England. I completed my bachelor's degree at Columbia University in mathematics and computer science in 2019, during which I was fortunate to be advised by Daniel Hsu.

I am currently interested in computational genomics and the development of large-scale foundation models for biological applications, particularly models pretrained on the genome and epigenome. I am excited about the application of biological foundation models to understanding disease mechanism and viral infection at single cell resolution.

I am passionate about diversity and inclusion in the tech, AI, and medical communities, both in regards to patient access to care and on the side of AI researchers and scientific development. At Microsoft New England, I co-founded and led a Diversity Recruiting Initiative with Ehi Nosakhare targeting the recruitment of underrepresented minorities for entry-level AI positions.

A foundation model of transcription across human cell types
Xi Fu*, Shentong Mo*, Alejandro Buendia*, Anouchka Laurent, Anqi Shao, Maria del Mar Alvarez-Torres, Tianji Yu, Jimin Tan, Jiayu Su, Romella Sagatelian, Adolfo A. Ferrando, Alberto Ciccia, Yanyan Lan, David M. Owens, Teresa Palomero, Eric P. Xing, Raul Rabadan
Nature (Jan. 2025)

Deeper evaluation of a single-cell foundation model
Rebecca Boiarsky, Nalini M. Singh, Alejandro Buendia, Ava P. Amini, Gad Getz, David Sontag
Nature Machine Intelligence (Dec. 2024)

A deep dive into single-cell RNA sequencing foundation models
Rebecca Boiarsky, Nalini Singh, Alejandro Buendia, Gad Getz, David Sontag
Machine Learning in Computational Biology (MLCB, Nov. 2023) | Oral Presentation, Top 15%

TabLLM: Few-shot classification of tabular data with large language models
Stefan Hegselmann, Alejandro Buendia, Hunter Lang, Monica Agrawal, Xiaoyi Jiang, David Sontag
26th International Conference on Artificial Intelligence and Statistics (AISTATS, Apr. 2023)

Examination and extension of strategies for improving personalized language modeling via interpolation
Liqun Shao, Sahitya Mantravadi, Tom Manzini, Alejandro Buendia, Manon Knoertzer, Soundar Srinivasan, Chris Quirk
First Workshop on Natural Language Interfaces (ACL, July 2020)

Random walk fundamental tensor and graph importance measures
Daniel Boley, Alejandro Buendia
International Workshop on Big Social Media Data Management and Analysis (IJCAI, Aug. 2019)

Optimized graph-based trust mechanisms using hitting times
Alejandro Buendia, Daniel Boley
International Workshop on Trust in Agent Societies (AAMAS, May 2017)