Jan Christoph is an Assistant Professor at the University of California, San Francisco, and head of the Cardiac Vision Lab. He is a faculty member of the Cardiovascular Research Institute, with appointments in the Division of Cardiology, School of Medicine, and the Department of Bioengineering and Therapeutic Sciences. His research interests include cardiac electrophysiology and biomechanics, cardiac arrhythmia mechanisms, the physics of complex biological systems, artificial intelligence, numerical modeling and imaging. Previously, he worked as a researcher in Germany, where he developed novel optical and ultrasound-based imaging techniques for the visualization of life-threatening ventricular arrhythmias. Read more ...


Jan Lebert is a Postdoc and Computational Researcher at the Cardiac Vision Lab. Jan is interested in the physics of complex systems, computing, artificial intelligence and medical imaging. He obtained a PhD in biophysics and specializes in the prediction of cardiac dynamics using deep learning. Jan was a graduate student at the University of Göttingen in Germany and pursued his PhD over the past 2 years remotely at UCSF. He graduated recently with 'Summa Cum Laude'.


Shrey Chowdhary is a Computational Research Specialist at the Cardiac Vision Lab. Shrey obtained a BSc in Computer Science and Physics at the University of Illinois and he is generally interested in computational physics, high-performance and distributed computing and computer graphics. In our lab he is involved in numerical method development and performing computer simulations of the heart. Before joining our lab, he worked as a software engineer in San Francisco.


Lucas Pedersen is a Staff Research Associate at the Cardiac Vision Lab. Lucas studied Neuroscience at Purdue University and he is interested in artificial intelligence, computational modeling and arrhythmia mechanisms. He has experience with predicting sudden cardiac death using machine learning.


Tanish Baranwal is an undergraduate research assistant at the Cardiac Vision Lab. Tanish is a second-year undergraduate student at UC Berkeley studying Electrical Engineering and Computer Science, and his research interests include deep learning, computer vision, computational biology, and neuroscience. Previously, he worked as a student researcher at the Louis Lab, University of California, Santa Barbara in evolutionary neuroscience and is now excited to study 3D spiral waves and implementing deep learning models to push state of the art capabilities.


Shai Dickman is an undergraduate research assistant at the Cardiac Vision Lab. Shai is currently a second-year undergraduate student at UC Berkeley studying Electrical Engineering & Computer Science with a minor in Mathematics. His research interests include 3D imaging, computational mathematics, and procedural animation.


Luke Villarama is a Biophysics Ph.D.-student at UCSF and currently rotating at the Cardiac Vision Lab. He completed his undergraduate degree in physics and has past experience in molecular dynamics simulations and simulations of Brownian diffusion within bacterial cells. He is interested in continuing to do computational biophysics research, including simulations and deep learning.


Joy Barsoum is an undergraduate research assistant at the Cardiac Vision Lab and a second-year undergraduate student at UC Berkeley studying Electrical Engineering and Computer Science. Joy is interested in medical technology and imaging, she enjoys the natural sciences and math and is also interested in education.


Ali Momennasab is an undergraduate research assistant at the Cardiac Vision Lab. Ali studies Computer Science at the California State Polytechnic University in Pomona and is interested in machine learning and medical imaging.



We are looking for enthusiastic undergraduate students, Ph.D. students or Postdocs to join our lab. If you are interested in working in an exciting interdisciplinary field and would like to apply your computational skills in biological or medical research then please contact us! We are interested in people with diverse backgrounds such as physics, engineering / bioengineering, computer science, applied math, biology, physiology or medicine. Please submit your CV and a brief research statement to: [email protected] value a diverse and inclusive work environment.