Interdisciplinary Graduate Fellows Alumni

Yi is a Ph.D. candidate in Ada Poon’s group in the Department of Electrical Engineering. She is currently studying the mechanisms of extracellular electrical stimulation and analyzing the effects of different current waveforms applied at the electrode. In the future, she plans to electrically stimulate the mouse hippocampus for memory recovery as a potential treatment for early-stage Alzheimer’s disease. Before joining Stanford, Yi received her B.S. degree in physics at Peking University in China.

I am a PhD student in the department of Bioengineering, co-advised by Jennifer Raymond (Stanford Neurobiology) and Mark Goldman (UC Davis Neuroscience). I am interested in the principles by which learning and memory operate, and in my research I am studying mathematical models of learning in the control of eye movement reflexes, which are mediated by neural circuits in the cerebellum.

Tamara is broadly interested in the role of microglia in the brain. She is currently working with Dr. Marius Wernig at the Institute for Stem Cell Biology and Regenerative Medicine to create human stem cell-derived models of the brain to learn more about how cells interact on a cellular and molecular level. She is particularly interested in how microglia cooperate with each other to establish very strict spatial organization, called tiling, and how this contributes to homeostasis.

Isabel is a PhD candidate in the Stanford Neurosciences Program. She works in the Giocomo Lab studying how our internal state—like whether we are alert or tired—affects the way our brains work. Prior to Stanford, Isabel received a BA from Bowdoin College and worked as a research technician at Harvard Medical School. In addition to her graduate work, Isabel is Co-President of NeuWrite West (neuwritewest.org), where she works to promote communication between neuroscientists and non-scientists so as to make neuroscience accessible to anyone curious about the brain.

Kyrstyn is a PhD candidate in the department of Materials Science and Engineering. She is working with her advisor Dr. Stephen Baccus (Neurobiology) as well as Dr. Evan Reed (Material Science) and Dr. Merritt Maduke (Molecular and Cellular Physiology) to determine the molecular effect of ultrasound neuromodulation through simulations and in vitro animal experiments. Prior to Stanford, she received a BS in Engineering from Swarthmore College.

Khaled was born in Pittsburgh, Pennsylvania and grew up in Beirut, Lebanon. He received his B.S. in Computer Engineering from Georgia Institute of Technology in 2017 and is currently pursuing his PhD in Electrical Engineering at Stanford University. 

His research interests are in using tools from control theory, stochastic optimization, and machine learning to build reliable and interpretable models for medical applications. Specifically, he is currently working on using multiple sensing modalities to improve detection and localization of seizures.

Kathryn is an MD-PhD student in Stanford's Neurosciences Interdisciplinary Program. She is fascinated by Schwann cells, which are glial cells that sort axons by size and selectively myelinate large-caliber axons during peripheral nervous system development. Kathryn is currently working with Dr. Brad Zuchero and Dr. Wah Chiu to uncover what mechanisms Schwann cells use to execute the dynamic movements necessary to sort and myelinate axons. Prior to Stanford, Kathryn studied Biology at Swarthmore College and conducted amyotrophic lateral sclerosis research in the laboratories of Dr.

Born in Nanjing, China, Yixiu Zhao is a PhD student in the Applied Physics department working in the Linderman Lab on computational neuroscience and machine learning with Dr. Scott Linderman. Yixiu has a wide variety of research interests, including building structured models for statistical inference, making neuroscientific inquiries with machine learning, and better understanding the high-level principles of human and artificial intelligence. His current project involves combining Bayesian inference and deep neural networks for behavioral studies of mice.