Jon Kleen
Principal Investigator
Jon is originally from rural Minnesota. He earned a PhD studying neuroscience from Dartmouth College along with training in engineering and computer science, and his MD from Dartmouth Medical School. At UCSF, he completed a residency in neurology, clinical fellowship in epilepsy, and postdoctoral training in human neurophysiology research. He is both a physician and a scientist in the Department of Neurology, Division of Epilepsy, and UCSF Weill Institute for Neurosciences.
Da Zhang
Da is a postdoctoral scholar at UCSF who received her Ph.D. in electrical and computer engineering at the University of Miami under the mentorship of Professor Mansur R. Kabuka. During her Ph.D., she studied deep representation learning for biological networks and uncovered hidden patterns in sequential data. Her current research uses machine-learning and deep-learning-based methods to understand the semantic basis of neural signals.
David Caldwell
David is a neurosurgery resident at UCSF who received his BSE and MSE in biomedical engineering at the University of Michigan, and subsequently his MD and PhD in bioengineering at the University of Washington. His PhD work was focused on engineering direct electrical stimulation of human sensorimotor cortex, working with patients that were implanted with electrodes in their brains for clinical care of epilepsy and movement disorders such as Parkinson’s and Essential Tremor. He is broadly interested in neural engineering and intracranial electrophysiology.
Ebenezer Chinedu-Eneh
Ebenezer is a neurology resident at UT Southwestern who started in the Kleen Lab as a UCSF medical student. He grew up in Minnesota, earned his BS in Biology while minoring in German at the University of Minnesota, and is currently a medical student at UCSF. He is broadly interested in leveraging technology to improve healthcare, and previously worked in a consumer health start-up towards that aim. His current interests involve utilizing AI to aid in visualization of neural networks using intracranial ECoG data.
Raphaël Christin
Raphaël grew up in Québec, Canada. He earned his bachelor's degree in Cognitive Science (Neuroscience specialization) and Computer Science from McGill University, where he obtained research experience in consciousness using signal processing, as well as neurobiological research in mood and anxiety disorders. He is very interested in applying computational methods in research to help patients and push forward our understanding of neurological diseases. As a Junior Specialist in the lab, he works on building data pipelines and analyzing software for epilepsy and cognition research using Python and Matlab.
Devon Krish
Devon is a current undergraduate studying bioengineering, electrical, and computer engineering (EECS) at UC Berkeley. He is widely interested in using machine learning and signal processing algorithms to decode abnormal bursts of neural activity. On previous projects, he’s worked to understand the link between interictal spikes and memory/language impairments, and he is currently focused on optimizing intracranial biomarker detection for neuromodulation and other cutting-edge technologies. In his free time, he enjoys writing music for film.
Siddharth Marathe
Siddharth is a Bay Area native, who is double majoring in Bioengineering and Electrical Engineering and Computer Sciences (EECS) at UC Berkeley. He has past experience in the wet-lab and dry-lab spaces, such as investigating regulatory T-cell therapeutic functions in cancer and developing image analysis pipelines for annulus fibrosis cells to model spinal disk degeneration/herniation. Currently he is using advanced signal processing techniques to analyze intracranial recordings as well as single-neuron data (Neuropixels in collaboration with the Chang Lab) and collaborating with other lab members on memory and eye-tracking projects.
Natalia Sucher Munizaga
Natalia grew up in New York City, earned her BA in Ancient Greek and Latin at Swarthmore College, and now is back in school for her post-baccalaureate at UC Berkeley and City College of San Francisco studying computational neuroscience. Her focus is conducting epilepsy research, specifically writing algorithms in MATLAB and Python to integrate semiology and electrophysiology in order to localize and track the propagation of seizure activity in the brain.
Edwina Tran
Edwina is a neurosurgery resident at Cedars Sinai who started in the Kleen Lab as a UCSF medical student. She was born and raised in San Francisco. She double majored in Molecular and Cellular Biology—Infectious Diseases and Public Health at UC Berkeley. Previously, she worked on building a bioinformatics pipeline to modify mNGS and host transcriptome profiling protocols for the detection of TB meningitis in resource-poor settings. Her current research interests include understanding the neurophysiology of memory processing using intracranial ECoG data from patients with medication-resistant epilepsy and other emerging neurosurgical interventions, including neurostimulation, that may rescue cognitive function.
Akshat Kalra
Akshat is a Staff Research Associate who recently completed his Master’s in Computer Science and Engineering from Santa Clara University. Being largely interested in neuromodulation for psychiatric and neurological disorders, his graduate research was based around building a closed loop system between photobiomodulation and EEG, while he also got experience in designing low intensity focused ultrasound devices. Apart from writing software pipelines for enabling intracranial neurophysiological research in the Kleen Lab, he works on mapping the semantic memory circuitry of the human brain. When not in the lab, you can find him exploring the various ice cream shops and bakeries that SF has to offer.