Antonio Fonseca, M.Sc.

Graduate Student

Antonio is a doctoral candidate specializing in Neuroscience and Machine Learning at the Van Dijk Lab. Holding an eclectic educational background, he earned his Bachelor's degree in Robotics Engineering followed by a Master's in Microelectronics. Prior to diving into neuroscience, Antonio contributed to software development for mining robots and spearheaded research where he applied machine learning and signal processing techniques to explore behavioral development in animals.

At present, Antonio is passionate about advancing the field of brain research by employing Deep Learning algorithms to model dynamic brain activities. He is pioneering the development of machine learning methods specifically designed for spatiotemporal data. By applying these innovative methods to brain activity recordings, he aims to unravel intricate aspects of cognitive processes. His research serves as a bridge between artificial intelligence and neuroscience, shedding new light on the enigmatic functions of the brain.

Josue Ortega Caro

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.

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.

Sina Ghadermarzi

Postdoctoral associate

Sina is a postdoctoral associate at Center for Infection and Immunity, where he is co-mentored by Dr. David van Dijk and Dr. Akiko Iwasaki. His interest is mainly in applied machine learning, particularly, large language models, and causal inference, and their application to complex biological and biomedical problems. Currently, he is working on methods for analysis of multi-modal single-cell, and immune profiling data for understanding complex disease, such as long-covid and cancer. Before joining the lab, he obtained his PhD in computer science, where he worked on application of machine learning in protein bioinformatics.

Daniel Levine

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.

Sacha Lévy

Graduate Student

Sacha is a Computer Science Ph.D. student at Yale University, researching Machine Learning and Computational Biology under the supervision of Dr. David van Dijk. Prior to joining the Van Dijk Lab at Yale, he earned his Bachelor's in Computer Engineering from McGill University and worked with Professor Reihaneh Rabbany at Mila to quantify political polarization on social media and human trafficking on online escort platforms using active learning. His current research focuses on developing representation learning models to extract structural insights from biological data.

Zihe Zheng

Research Assistant

Zihe is a research assistant in the van Dijk Lab. She graduated from Yale University with a Master’s degree in Statistics. Prior to her time at Yale, she earned a Bachelor’s degree in Data Science from the University of Rochester. During her undergraduate research, Zihe focused on applying machine learning methods to address healthcare challenges. Her current research interests include the application of large language models to analyze single-cell RNA sequences.

Xingyu Chen

postgraduate associate

Xingyu is a postgraduate associate in van Dijk Lab. Before joining the van Dijk Lab, she obtained her bachelor’s degree in Computer Science and biology from McGill University and pursued her master’s degree in Bioinformatics at ETH Zurich. Xingyu is currently focusing on Large language models and their applications to single-cell data.

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.

Matteo Rosati

Medical Student collaborator

Matteo is currently a medical student at Yale School of Medicine and Artificial Intelligence MS student at University of Amsterdam. His research interests lie in applying generative models to neural data to uncover physiological and clinical insights, as well as in developing new neuromodulation techniques.