Alejandro Buendia

Biomedical Data Science PhD student, Stanford University

About

Hello! I am a second-year PhD student in the Department of Biomedical Data Science at Stanford University, where I am fortunate to be advised by Anshul Kundaje and Scott Boyd. My research interests are in developing machine learning approaches to understand genomic regulation (in particular, by leveraging spatially-resolved data) and the adaptive immune response to viral pathogens.

Previously I was a computational research lab manager at Columbia University Irving Medical Center, a research engineer 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 passionate about diversity and inclusion in the medical, AI, and tech communities. 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.

Research

Selected Publications

For a full list of publications, please see my Google Scholar.

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 (January 2025)

Writing

Genomics x AI Blog

I am on the editorial board for the Genomics x AI blog, a cross-institution and open-source initiative to publish research findings and build software supporting the genomics and AI communities. I am a core developer of the alphagenome_ft and alphagenome-pytorch packages, which provide finetuning utilities and a PyTorch implementation of AlphaGenome (Avsec et al., 2026).

Teaching

Courses