Center for Mind, Brain, Computation and Technology

Maylin graduated from University of California, San Diego (UCSD) with a BS degree in Physiology and Neuroscience. At UCSD, she studied learning and memory focusing on circuit and neuromodulation using optogenetics in Dr. Stefan Leutgeb’s lab. She later joined the preclinical team in a start-up biotech company in South San Francisco examining neural cell therapy in vivo for neurological diseases. She is currently pursuing her Bioengineering PhD degree in Dr. Stanley Qi’s lab at Stanford.

Lauren graduated from MIT with a B.S. in Physics and Materials Science. Her fascination with droplets and interfaces led her to gain interest in applying physical principles to complex biological phenomena. Motivated by a passion for translating physical and engineering principles to unique biological contexts, she is currently interested in light-matter interactions for advancing technologies in neuroscience.

Olivia (she/her/hers) is a PhD student in the Mechanical Engineering department advised by Dr. Sean Follmer in the SHAPE Lab. Before coming to Stanford, Olivia earned her BS in Mechanical Engineering from Tufts University. At Tufts, she worked with Dr. Chris Rogers at the Center for Engineering Education and Outreach where she developed and tested an educational tool to help teach robotics and artificial intelligence concepts to young students.

Muhammad (he/him) is a PhD student in Electrical Engineering, with a BS in Mathematics from the University of Florida. He is currently working in the Brain Interfacing Laboratory with advisor Dr. Paul Nuyujukian. His primary interest is using mathematical techniques to understand how networks of neurons encode motor control with potential applications in stroke recovery. Previously, he pursued research on dynamical systems theory and models of neural activity at the Center for the Neural Basis of Cognition and the National Institute of Neurological Disorders and Stroke.

Mary Kate (she/her) graduated from Georgia Tech with a BS in Biomedical Engineering and a minor in Computer Science. She is now pursuing a PhD in Bioengineering in Professor Allison Okamura's CHARM lab, considering the complex neurological processes at play during motor learning in the context of teleoperated surgical robotics. Ultimately, she hopes to learn about how we learn to execute new, complicated motor tasks. Outside of lab, she enjoys reading, crossword puzzles, and hanging out with her cat, Grapes.

Favour (she/her) is a Ph.D. candidate in Electrical Engineering conducting research in the Computational Neuroscience Laboratory with Dr. Ehsan Adeli and Dr. Kilian Pohl. Previously, she obtained a B.S. in Computer Science with minors in Arabic and Global Engineering Leadership from the University of Maryland-College Park (Go Terps!). Her current research is focused on using data-driven methods to discover trackable, digital biomarkers for neurodegenerative diseases by identifying neural correlates between neuroimaging and recorded human, movement-linked disturbances.

Siavash (He/Him/His), a Chemical and Systems Biology Ph.D. student at Stanford, is co-advised by Carolyn Bertozzi from the Department of Chemistry/Sarafan ChEM-H and Longzi Tan from the Department of Neurobiology. Prior to Stanford, he graduated Summa cum laude from the University of California at San Diego with a B.Sc./M.Sc. in Biochemistry and Chemical Biology, achieving Highest Distinction and Departmental Honors. Deeply passionate about neurobiology, Siavash is dedicated to employing cutting-edge technology to understand the intricate cellular and molecular processes of the brain.

Yuxin Wu is a PhD student in Electrical Engineering, working with Professor Paul Nuyujukian in the Brain Interfacing Laboratory at Stanford University. She received her Bachelor’s degree in Electronic Information Science and Technology from Tsinghua University in 2022. Yuxin’s long-term research interests include combining Electrical Engineering with Medical Science to improve the design of medical devices and systems.

She/Her/Hers

I am an electrical engineering Ph.D. student and am interested in the dynamics of neural activity within and across brain regions as they relate to motor control, reinforcement learning, and brain-machine interfaces. My approach involves computational analyses of large-scale neural activity patterns, and I am especially interested in bidirectional approaches that take neural dynamics as inspiration for improving machine learning and robotics, as well as using methods from these engineering fields toward understanding the brain.

he/him

I graduated from Berkeley in 2019 with degrees in molecular & cell biology and cognitive science. After that I joined Stanford as a post-bac and in 2021 started my PhD. I'm interested in how we encode, represent, and decode information in cortex, and how those processes enable perception and decision making.