Neurology

Sergio Baranzini, PhD

Professor in Residence
Neurology

Sergio E. Baranzini is Distinguished Professor of Neurology I at the University of California San
Francisco (UCSF). He is also a member of the Graduate Program in Bioinformatics, the Institute for
Human Genetics, the Bakar Computational Health Sciences Institute, ImmunoX, and the California
Institute for Quantitative Biology (QB3). He holds the Heidrich Friends and Family endowed chair in
Neurology. Dr. Baranzini earned his degrees in clinical biochemistry (1992) and PhD in human molecular

Miriam Gorostidi, PhD

Visiting Scholar
Neurology

Miriam is a Visiting Scholar from Donostia-San Sebastián, Spain. She earned her Bachelor’s Degree in Biomedical Engineering and a Master’s Degree in Biomedical Engineering with a specialization in Data Analysis from Tecnun, University of Navarre. Currently, Miriam is a Ph.D. student in the Neuroimmunology Department of Biogipuzkoa Health Research Institute, where she applies a computational approach to analyze the microbiome of Multiple Sclerosis patients.

Crystal Luong

Clinical Research Coordinator
Neurology

Crystal is a clinical research coordinator for the Baranzini laboratory. She was born and raised in San Francisco and earned her BS in Public Health from San José State University. You can often find her enjoying a bánh mì, dumplings or a Chipotle burrito bowl! Outside of food and work, she also enjoys strength training and traveling! 

Gabriel Cerono, MD

Postdoc Scholar - Employee
Neurology

Gabriel is an Argentinian Medical Doctor. He earned his medical degree from Universidad Nacional de La Plata. He is a self taught programmer, data scientist, and machine learning practitioner. He is currently involved in SPOKE development. His research interests lies in the integration of data science with clinical practice.

Karthik Soman, PhD

Specialist
Neurology

Karthik Soman currently works as a Specialist in Baranzini lab. His work mainly focuses on building knowledge network by data integration, graph data science (such as knowledge embedding), machine learning and applying them on clinical and biological data for disease prediction in an explainable fashion using network insights. To achieve this, he leverages a combination of graph data and big data analytics, employing High Performance Computing clusters to advance precision medicine.