David van Dijk, Ph.D.

Assistant professor of Medicine & Computer Science

David completed his PhD at the University of Amsterdam and the Weizmann Institute of Science (with Prof. Eran Segal) in Computer Science where he used machine learning to understand how gene regulation is encoded in DNA sequence. As a postdoctoral fellow at Yale Medical School and Dept. of Computer Science, he developed new machine learning and manifold learning methods for discovering hidden signatures in large biomedical data with an emphasis on single-cell data. David is currently an Assistant Professor in Medicine and in Computer Science at Yale, where he leads a research group in machine learning for biomedicine.

 

Postdoctoral Researchers

Cerise Tang, Ph.D.

Postdoctoral Associate

Cerise is a postdoctoral researcher in the van Dijk lab, focusing on applying large language models to genomic sequencing data for clinical response prediction. Prior to Yale, Cerise earned her PhD in Physiology, Biophysics and Systems Biology from Cornell University where her thesis focused on intratumoral heterogeneity in kidney cancer.

 

Josue Ortega Caro, Ph.D.

Postdoctoral Fellow

I am a Wu-Tsai Postdoctoral Fellow in the van Dijk and Cardin Laboratories, at Yale University. I graduated in biology from the Universidad Peruana Cayetano Heredia in Lima, Peru. I continued my graduate studies at Baylor College of Medicine, where I earned a PhD in Quantitative and Computational Biosciences with emphasis on Computational Neuroscience and Machine Learning. My current research interests revolve around applying Transformer-based models to multi-modal brain dynamics.

 

Daniel Levine, Ph.D.

Postdoctoral Associate

Daniel is a postdoctoral researcher at the Van Dijk Lab with a Ph.D. in mathematics from Penn State University, focusing on moduli spaces of vector bundles. His work centers on developing machine learning algorithms for biomedical data and uncovering theoretical insights into neural networks.

 

Graduate Students

Syed Asad Rizvi

Graduate Student

Syed is a Computer Science PhD student. Prior to joining the van Dijk Lab, he obtained his B.S. in Computer Science from the University of Houston and worked as an undergraduate research student at Houston Methodist Research Institute, where he focused on spatiotemporal modeling of time series data using Graph Neural Networks (GNNs). His current research interests are in applying GNNs and Large Language Models (LLMs) to single-cell data.

 

Sizhuang He

Graduate Student

Sizhuang is a Ph.D. student in Computer Science at Yale University. He earned his Bachelor's degree in Mathematics from the University of Michigan, Ann Arbor. His research interests lie in generative modeling—including diffusion and flow matching methods—over both continuous and discrete data domains, as well as in modeling spatiotemporal dynamics using operator learning frameworks.

 

Aakash Patel

Graduate Student

Aakash is a PhD student in Computer Science at Yale, specializing in machine learning for biomedicine. His research centers on developing foundation models tailored for biological systems, with particular emphasis on single-cell genomics, spatial transcriptomics, and neuroimaging data. Prior to coming to Yale, he earned a dual Master’s degree in Computer Science and Mathematics from the University of Michigan in Ann Arbor.

 

Yangtian Zhang

Graduate Student

Yangtian Zhang is a Ph.D. student in Computer Science at Yale University. His research interests include generative models, graph algorithms, and, more recently, multi-modal foundation models. He is currently focused on developing innovative solutions for real-world applications and scientific challenges.

 

Harry Zhang

Graduate student

Harry is an incoming Ph.D. student in Professor van Dijk’s lab at Yale University whose work lies at the intersection of large‑language models, deep learning, and intelligent agent systems. He earned his M.S. from Columbia University and holds a B.Sc. in Statistics from the University of British Columbia (Canada), with a strong foundation in data‑driven discovery. His research focuses on foundation models and AI agents to tackle complex biological challenges, and he looks forward to applying these approaches to biological data while collaborating across disciplines to push the boundaries of AI in biology.

 

Postgraduate Researchers and Collaborators

Sam Fenske

Graduate Student Collaborator

Sam is a PhD student in the computational biology and biomedical informatics (CBB) program at Yale. He received his BS in biomedical engineering from Washington University in St. Louis and after worked at the Northwestern Feinberg School of Medicine, analyzing single-cell lung immunology datasets and building predictive models for the ICU. He is currently interested in modeling cell state changes in cardiovascular and ovarian systems using machine learning models large scale genomics datasets with potential therapeutic and screening applications.

 

Shawn Wahi

Postgraduate Researcher

Shawn is a Postgraduate Researcher at the van Dijk Lab at Yale School of Medicine. He earned his B.S. and M.S. in Computer Science from Georgia Tech, specializing in machine learning, embedded systems, and human-computer interaction. Before joining the van Dijk Lab, he conducted research on safety and control algorithms for autonomous vehicles, contributing to uncertainty-aware prediction models and multi-robot SLAM systems. His interests lie in the medical domains of cardiology and oncology, with research focused on multimodal foundation models, large language models (LLMs), AI agents, and machine learning approaches for clinical risk prediction and health outcomes modeling. He aspires to pursue an MD-PhD, aiming to bridge Computer Science and Medicine to help shape the future of healthcare.

 

Marlene Li

Masters student

Marlene is a first-year Master’s student at Yale studying Computational Biology and Bioinformatics. She has experience in single-cell and spatial transcriptomic data analysis, particularly in cancer research. Her interests lie in applying AI methods to single-cell data to uncover biological insights.

 

Ivan Vrkic

Postgraduate researcher

I am currently a postgraduate researcher at the Van Dijk Lab, focusing on machine learning for biomedicine. Previously, I did my master’s studies at EPFL and TU Wien, where I was supervised by Prof. Pascal Fua. My research interests center on computational geometric methods for machine learning, with applications spanning computer vision, pattern recognition, geometry processing, and biomedical domains.

 

Olin Geimer

Postgraduate Fellow

I’m currently a Postgraduate Fellow at the van Dijk Lab, where I mostly build behavioral foundation models to simulate and predict human opinion and behavior. I earned my BSc in Computer Science at ETH Zurich, completing a thesis with Prof. Dr. Roger Wattenhofer where I introduced a genetic algorithm for uncovering formulaic alphas in stock‑market data. I’m now wrapping up my MSc at ETH; during this time I co‑authored an ICLR‑spotlight paper on neural‑network pruning and parallel training with Prof. Thomas Hofmann’s Institute for Machine Learning and managed a €1.5 M student investment fund by designing quantitative trading strategies. I am currently most interested in leveraging LLMs to understand and further the field of behavioral science and biomedicine.

 

Undergraduate Students

David Zhang

Undergraduate Student

David is a third-year undergraduate at Yale studying Statistics and Computer Science. His primary research interests involve methods and applications of machine learning for high dimensional omics data, particularly single cell. He is also interested in AI-driven applications in drug discovery and precision medicine.

 

David Jeong

Undergraduate student

David is a junior undergraduate at Yale University studying Computer Science and Statistics. His research interests involve mechanistic interpretability of large language models to understand how internal representations relate to model behavior, as well as their applications to high-dimensional biomedical data.

 

Lawrence Zhao

UNDERgraduate student

Lawrence is a junior undergraduate at Yale studying computer science and math. He is interested in methods and applications of machine learning for biological and chemical data.

 

Zhikai (Zaki) Wu

Visiting student

Zhikai Wu (Zaki): Zhikai is a third-year undergraduate student at Yuanpei College, Peking University. His research interests lie in scientific machine learning, with a particular focus on applications in physics. He is also interested in relativistic quantum field theory and the interpretation of quantum mechanics. As a visiting student at vanDijk lab, he is currently working on learning operator with large language models (LOLL).

 

Zhuoyang (Robinson) Lyu

Visiting student

Zhuoyang (Robinson) is an undergraduate at Brown University pursuing a double major in Computer Science and Applied Mathematics. He is interested in developing and applying machine learning methods in biomedical context, particularly single-cell genomics. His research experience focused on graph deep learning and foundation models.

 

Alumni

Graduate Students

Antonio Fonseca

Postdoctoral Associates

Nazreen Pallikkavaliyaveetil

Sina Ghadermarzi

Neal Ravindra

Emmanuele Zappala

Research Assistants and Undergraduates

Sacha Lévy

Xingyu Chen

Daphne Raskin

Matteo Rosati