Reza Abbasi-Asl

Principal Investigator

Reza is an Assistant Professor in the Department of Neurology and the Department of Bioengineering and Therapeutic Sciences at UCSF. He is a core faculty member at the UCSF Neuroscape Center, a Weill Neurohub Investigator, and the Director of Data Analytics and Visualization at the UCSF Weill Institute for Neuroscience.

Before joining UCSF, Reza was a scientist at the Allen Institute for Brain Science in Seattle. He completed his PhD and MSc in Electrical Engineering and Computer Sciences at UC Berkeley in 2018, where he worked with Bin Yu and Jack Gallant to develop interpretable machine learning tools with applications in computational neuroscience. Reza received his MSc in Biomedical Engineering from Sharif University of Technology in 2013 and BSc in Electrical Engineering from Amirkabir University of Technology (Tehran Polytechnic) in 2010. He is the recipient of the New Frontiers Research Award from the Sandler Program for Breakthrough Biomedical Research (PBBR) in 2021, and the Eli Jury Award from UC Berkeley, Department of Electrical Engineering and Computer Sciences in 2018. He received the May J. Koshland Fund in Memory of H.A. Jastro Award from UC Berkeley Graduate Division in 2016, the Excellence Award in Biomedical Engineering from Sharif University of Technology in 2013, and the Excellence Award in Electrical Engineering from Tehran Polytechnic in 2010. 

Roozbeh Farhoodi

Postdoctoral scholar

Roozbeh is a postdoctoral scholar at the Abbasi Lab working at the intersection of computational neuroscience and machine learning. His project is focused on understanding the relationships between neural structure and neural activities in the primary visual cortex. Before joining UCSF, he was a postdoc at the University of Pennsylvania under the supervision of Konrad Kording where he studied the theory of deep learning and how the morphologies of neurons contribute to the computation in the brain. Roozbeh received his Ph.D. in Mathematics from Sharif University in 2017 where he worked on the emergent patterns in neural networks.

Zhinoos Razavi

Postdoctoral scholar

Zhinoos is a Postdoctoral scholar at the Abbasi Lab working on brain mapping project.
Before joining UCSF, she was a Research fellow at Department of Medicine in
the University of Melbourne, Melbourne Australia. She has received her PhD from
Data analytic labs, School of Computer Science at Royal Melbourne Institute of
Technology (RMIT), Australia. Prior to joining RMIT, Zhinoos was a researcher at the data analytic group at IBM, Melbourne, Australia; a research scientist at University of Aveiro,
Portugal; and a research scientist at the Georgia Institute of Technology, Atlanta,
USA. She contributed to many machine learning projects and co-supervised master and PhD projects in the multidisciplinary field of seizure detection/prediction and machine learning. Her research areas include data science, machine learning, signal processing, and computational neuroscience

Gavin Cui

PhD Student, Bioengineering

Gavin is a PhD student in the UC Berkeley-UCSF joint Bioengineering program. Before coming to the program, Gavin was an undergraduate researcher at McGill University, where he generated MRI-based simulations of transcranial Direct Current Stimulation. Gavin’s background in Neuroscience and Medical Imaging prompts him to explore projects that apply machine learning methods for predicting neurological disorder prognosis. Currently, Gavin’s focus in the lab is to build models that can combine longitudinal MRI data and genomics data to improve Multiple sclerosis prognosis.

Neelroop Parikshak

Resident, Neurology

Neel is a physician-scientist who is completing clinical training in Neurology at UCSF. He has a background in both biology and mathematics which has him to pursue practical medical questions with rigorous, data-driven approaches. He has joined the lab to combine quantitative approaches with medicine and biology to improve diagnosis and prognosis of disorders and diseases and develop predictive models for disorders and diseases that lead to evidence-based interventions (related to the idea of “precision medicine”). Neel works on basic science questions with the Kriegstein lab.

Meera Mehta

Research Assistant

Meera is an undergraduate student at UC Berkeley studying Chemical Biology and Computer Science. At the Abbasi Lab, she is working on using machine learning methods to associate multi-omics and GWAS data to allow the interpretation of MS variants. Previously she has worked as a research apprentice at the Plant Gene Expression Center on a project utilizing CRISPR to study the role of miRNA’s on plant immunity.

Zeyu Yun

Research Assistant

Zeyu is an undergraduate student majoring in Computer Science and Math at UC Berkeley. At Abbasi Lab, he is working on designing a method to estimate the stability of patterns extracted using deep autoencoders. His project involves leveraging these stability-driven analyses to identify low-dimensional representations in spatial gene expression datasets.

Chirag Sharma

Research Assistant

Chirag is an undergraduate at UC Berkeley majoring in Computer Science and Physics. Chirag is currently working on a collaboration project with the UCSF Weill Institute for Neurosciences and Google Health to analyze time-series motion data of Parkinson’s patients from video data. This project seeks to develop few-shot machine-learned models that can predict symptom severity and extract meaningful clinical features for identifying the incidence of motion-related neurological disorders.

Gaurav Ghosal 

Research Assistant

Gaurav is an undergraduate Electrical Engineering and Computer Science major at UC Berkeley. Gaurav is currently working on designing an interpretable machine learning framework for multi-variable time-series classification. In the future, Gaurav will apply his framework to multi-modal bio-sensing datasets, as well as continue to develop interpretable machine learning methods. Prior to joining the lab, he worked on research in applying reinforcement learning for network scheduling.

Austin Jang

Research Assistant

Austin is an undergraduate student studying Electrical Engineering and Computer Science at UC Berkeley. At Abbasi Lab, he is interested in developing tools to interpret and train deep learning models to understand neurological responses to image stimuli. His project involves assessing biophysical models of the brain through state-of-the-art machine learning models.

Ahyeon Hwang

Research Assistant

Before joining the lab, Ahyeon was an undergraduate researcher at the Redwood Center for Theoretical Neuroscience, where she conducted work at the intersection of machine learning and neuroscience. After working briefly at the Computational Neurobiology Laboratory at the Salk Institute, she worked as a research associate at LBNL where she used statistical machine learning methods on medical record data to predict traumatic brain injury outcomes. Ahyeon is interested in developing more interpretable deep learning models to understand the mechanism of neurological disorders and improve clinical diagnoses through precision medicine tools. 

Undergraduate researchers

Rohan Divate, UC Berkeley

Austin Jang, UC Berkeley

Arbaaz Muslim, UC Berkeley

Kevin Chen, UC Berkeley

Shiladitya Dutta, UC Berkeley

Former members

Franklin Heng, Research Assistant

Oluwaseun Adegbite, Rotation PhD student

Anmol Parande, Undergraduate researcher

Join us!

We have several openings for post-docs, graduate and undergraduate students and software developers. Contact Reza directly at to learn more!