NeuroTech Alumni

AJ graduated from New Mexico State University with BS degrees in Electrical Engineering and Computer Science and a minor in Mathematics. He is currently pursuing a PhD in Electrical Engineering at Stanford, advised by Professor E.J. Chichilnisky. His research goal is to use novel results from experimental neuroscience to engineer algorithms that facilitate cellular resolution control of bi-directional neural interfaces. As a contributor to the Stanford Artificial Retina Project, he hopes to use this work to help restore high-acuity vision to people blinded by retinal degeneration.

Yuya grew up in Japan and received his B.Eng. in Electrical Engineering, Electronics, and Information Engineering from Nagoya University, Japan in 2019. He is currently pursuing a Ph.D. in Electrical Engineering at Stanford, advised by Professor Zhenan Bao in Chemical Engineering. His research focuses on transforming stretchable electronics – presently in the materials development phase – into real neuroscience applications.

Ava is a Ph.D. student in the Stanford Biomechatronics Lab, where she works on lower limb exoskeletons to improve mobility. Her research interests center around human-robot co-adaptation: how people learn to walk with exoskeletons, and how exoskeletons can best adapt to human behavior. A deep proponent of interdisciplinary work, she studies at the intersection of neuroscience, biomechanics, robotics, and controls while drawing on the principles of user-centered design, psychology, and disability studies.

Emily is a PhD candidate in electrical engineering at Stanford University and is a member of Professor Craig Levin's Molecular Imaging Instrumentation Laboratory (MIIL). She is interested in applying deep learning techniques for attenuation correction of simultaneous positron emission tomography and magnetic resonance imaging (PET/MRI) to visualize and quantify the molecular pathways of neurological disorders, such as Alzheimer's disease. Prior to attending Stanford University, she received her BS in electrical engineering from the University of Wisconsin - Madison.

Gabriela graduated from the University of Chicago in 2019 with a BS in Chemical Engineering and a minor in Computational Neuroscience. She is currently pursuing a PhD in Chemical Engineering at Stanford, advised by Surya Ganguli in Applied Physics. Her research currently focuses on bridging work in the Applied Physics and Psychology departments to examine noise correlations and coding fidelity in resting state functional Magnetic Resonance Images (fMRI).

My research philosophy is to connected to totally different fields to create something simple but unexpected. With my optical microscopy background, I joined Mark Brongersma's lab to learn nanophotonics. My research dream is to develop Nanophotonic tools to contribute Neuroscience. Besides science, my passion falls into rock climbing.

Max Kanwal graduated from UC Berkeley with a double major in Electrical Engineering and Computer Science (EECS) and Mathematics.  Max's scientific research interests revolve around developing a common theoretical framework to understand both natural and artificial intelligence.  Ultimately, he seeks to leverage this understanding to advance brain-AI interfacing technologies, in particular to engineer a closed-loop neural control system.  In preparation for this, Max has worked internationally with AI researchers, experimental neuroscientists, complexity theorists, and biologi

Vasily graduated from Moscow State University in 2016 with a degree in Laser Physics and Nonlinear Optics. Currently, he is working on his PhD in Applied Physics in Mark Schnitzer’s group. Vasily’s research interests include adaptive optics for deep tissue multiphoton imaging, large-scale brain voltage waves and critical behavior of neural networks.  He enjoys kayaking, snowboarding and mushroom hunting in his free time.

Pumiao graduated from Cornell University in 2018 with a B.S. in Electrical and Computer Engineering. She previously worked on “Micro-scale RF-powered Magnetic Neural Stimulator”. Currently, she is pursuing a PhD in Electrical Engineering at Stanford. Her research focuses on designing ultra high bandwidth neural interfaces that allow single-cell resolution when communicating with the nervous system. Specifically in the context of retina, she studies how to compress neural signals to reduce hardware power and bandwidth requirements.

Erin is a PhD student in the Electrical Engineering department currently working in the Neural Prosthetics Translational Laboratory with Dr. Krishna Shenoy and Dr. Jamie Henderson, and co-advised by Dr. Scott Linderman. She is interested in utilizing novel machine learning and statistical modeling techniques to improve decoding algorithms for brain computer interfaces (BCIs) in assistive neural prosthetic devices, particularly for rapid, dexterous motor sequences such as speech and handwriting.