Team
Principal Investigator
Andrew H. Song, Ph.D.
Assistant Professor, Department of Translational Molecular Pathology, UT MD Anderson Cancer Center
Adjunct Professor, Department of Computer Science, Rice University
Andrew is an Assistant Professor in the Department of Translational Molecular Pathology and Division of Pathology and Laboratory Medicine at UT MD Anderson Cancer Center (MDA profile) and an affiliate member in the Institute for Data Science in Oncology. He is also an Adjunct Professor in the Department of Computer Science at Rice University. Previously, he was a postdoctoral research fellow in the Department of Pathology at Brigham and Women's Hospital, working with Professor Faisal Mahmood.
Further back, he received his Ph.D. from Massachusetts Institute of Technology (MIT) Electrical Engineering and Computer Science (EECS) in 2022, with a focus on neural signal processing, co-advised by Professors Emery N. Brown (MIT) and Demba Ba (Harvard). He has Bachelor's & M.Eng. degrees, all in EECS, from MIT. He also served in the Republic of Korea Army for two years, during which he was stationed at Tyre, Lebanon as a UN peacekeeping force in Lebanon (UNIFIL) for a year.
asong2 [at] mdanderson [dot] org
Lab members
Paul Acosta, Ph.D.
Data Scientist
Co-advised with Dr. Yinyin Yuan
Paul is a Data Scientist at the Institute for Data Science in Oncology at MD Anderson Cancer Center. He is interested in developing multimodal AI and foundation models for computational pathology and spatial biology, with a particular focus on integrating histology and spatial transcriptomics and leveraging large language models for cancer research. His broader interests include digital pathology, spatial omics, and agentic AI. Previously, he earned his Ph.D. from UT Southwestern Medical Center. Outside of research, he enjoys pickleball, gaming, and tinkering with 3D printing.
Huilin Tai
Ph.D. Student, Computer Science, Rice University
Joined July 2026
Huilin is a Ph.D. student in Computer Science at Rice University. Her research develops multimodal models for cancer: how tissue can be represented across imaging, molecular, and clinical modalities, what those joint representations encode, and how much of one modality can be recovered from another. She is also interested in how such models are evaluated and explained. Previously, she received her B.Sc. in Statistics and Computer Science from McGill University and completed a thesis-based M.S. in Computer Science at Columbia University with Professor Mohammed AlQuraishi, where she worked on long-context genome language models. Outside of research, she enjoys squash, sketching, and writing.
Kunpeng (Eric) Zhang
Ph.D. Student, Computer Science, Rice University
Joined August 2026
Kunpeng is a Ph.D. student in Computer Science at Rice University. He is interested in developing multimodal AI and foundation models for biomedical data analysis and clinical decision-making. Previously, he received his B.S. in Computer Science from the University of Washington, where he worked on computational pathology and LLM agents under Professor Sheng Wang. Outside of research, he enjoys badminton and traveling.
Cristina Almagro-Pérez
Ph.D. Student, Harvard-MIT Health Sciences and Technology
Co-advised with Dr. Faisal Mahmood
Cristina is a Ph.D. Candidate at Harvard-MIT Health Sciences and Technology. She is interested in developing AI tools for 3D pathology and spatial biology data to improve the characterization of the tumor microenvironment and aid in biomarker discovery. Before starting her PhD, she worked on 3D computational pathology applied to micro computed tomography and serial histology for lung and pancreatic cancer at ETH Zurich and Johns Hopkins University. Outside of research, she loves running by the Charles, playing clarinet, and discovering new restaurants.
Julio Orellena Montes
Research Assistant
Joined September 2026
Julio received his BSc in Biology from Universidad Peruana Cayetano Heredia in Lima, Peru. His research spans single-cell and spatial transcriptomics, having contributed to studies on immune dynamics and viral latency across labs at UCLA, Weill Cornell Medicine and Northwestern University. His long-term goal is to pursue a PhD in computational pathology.
Nihal Josyula
Undergraduate student, Computer Science, Carnegie Mellon University
Joined September 2026
Nihal is a second-year undergraduate in Computational Biology at Carnegie Mellon University. He is interested in multimodal foundation models and in interpreting and evaluating what they learn. Previously, he worked on deep learning for medical image reconstruction at the NIH National Cancer Institute. Outside of research, he hikes and skis.