Bioengineering
4th Year Bioengineering PhD Student
Education:
Research Area:
Multimodal electrophysiology, sleep neuroscience
Biography:
Akshita (she/her) is a Bioengineering PhD candidate in the Neural Interaction Lab at Stanford, where she studies how brain-body dynamics during human sleep contribute to key functional processes using multimodal electrophysiology and wearable sensing. She is broadly interested in neural and autonomic signal processing and developing quantitative methods to understand multi-timescale coordination in human physiology.
Computer Science
5th+ Year Computer Science PhD Student
Education:
Research Area:
Robust and generalizable intracortical brain-computer interfaces
Biography:
Alisa is a Computer Science Ph.D. student jointly in the Stanford Neural Prosthetics Translational Lab and Linderman Lab, advised by Frank Willett, Jaimie Henderson and Scott Linderman. Her research focuses on cross-brain transfer methods to reduce the data collection burden on new handwriting and speech intracortical BCI users. She is supported by the NSF Graduate Research Fellowship and the Stanford Interdisciplinary Graduate Fellowship. Prior to coming to Stanford, Alisa received her B.S. in Computer Science from Trinity College in 2021, where she conducted research on heart murmur detection and classification.
Electrical Engineering
4th Year Electrical Engineering PhD Student
Education:
Research Area:
flexible electronics; neuroscience, medical devices
Biography:
Alisa (she/her) is a 4th year Electrical Engineering PhD Candidate in the Neural Interaction Lab. She is currently interested in olfaction, the gut, and the brain. Previously, she earned a BS from MIT, where she conducted research on various medical electronics. Outside of her PhD, Alisa loves camping, reading, and playing piano.
Neurosciences
1st Year Neurosciences PhD Student
Education:
Research Area:
Multimodal neuroimaging, brain stimulation
Biography:
Alexander is a first-year Neuroscience PhD student investigating how multimodal neuroimaging and brain stimulation techniques can be integrated to better characterize and treat neurological disorders. Before Stanford, Alexander earned a BA in Neuroscience with highest distinction from the University of Virginia, along with a minor in Data Science. He previously worked as a Data Analyst in the Laboratory for Neuroimaging of Coma and Consciousness at Massachusetts General Hospital.
Neurosciences
5th+ Year Neurosciences PhD Student
Education:
Research Area:
Intracortical brain computer interfaces for novel medical devices and agency
Biography:
Neuroengineering and human neuroscience related to intracortical speech brain computer interfaces and motor planning of articulation
Bioengineering
1st Year Bioengineering PhD Student
Education:
Research Area:
Wearable bioelectronics for continuous health monitoring and therapeutics
Biography:
Chibuike Uwakwe is an MD-PhD student in the Medical Scientist Training Program (MSTP) at Stanford University. He is originally from Wilson, North Carolina, and he previously earned an A.B. in Biomedical Engineering from Harvard University, where he conducted materials science research in the Harvard Microrobotics Lab under Prof. Robert Wood. His work in the Bao Group at Stanford focuses on developing wearable bioelectronics for continuous health monitoring and therapeutics.
Bioengineering
1st Year Bioengineering PhD Student
Education:
Research Area:
Soft bioelectronics for multi-modal sensing and neural stimulation
Biography:
Evelyn is pursuing an MD-PhD in the Medical Scientist Training Program (MSTP), jointly advised by Dr. Longzhi Tan (Biophysics) and Dr. Zhenan Bao (Chemical Engineering). She graduated summa cum laude from Harvard University with a major in neuroscience and a minor in Spanish literature. Evelyn received the Herchel Smith Fellowship for her thesis project at the MIT McGovern Institute, working with Dr. Edward Boyden to develop a next-generation protein sequencing technology. As a Marshall Scholar, Evelyn earned an MPhil in the Neural Computation Lab at University College London, where she optimized existing all-optical interrogation techniques to investigate cortical brain function. Evelyn is a recipient of the Knight-Hennessy Scholarship (2023) and the Paul & Daisy Soros Fellowship for New Americans (2024), supporting her dual-degree training. Her current research focuses on developing flexible bioelectronics for multi-modal recording and neural stimulation, as well as 3D microphysiological systems for probing neural-tumor interactions.
Electrical Engineering
3rd Year Electrical Engineering PhD Student
Education:
Research Area:
Computational Neuroscience, Statistical Modeling for Neuroscience
Biography:
Hannah (she/her) is an electrical engineering PhD student, advised by Scott Linderman. She is currently interested in developing statistical approaches to modeling neural dynamics. Previously, she earned a BS in Electrical and Computer Engineering from the University of Texas at Austin, where she conducted research in stroke and skin cancer diagnostic methods and non-invasive brain-computer interfaces. Outside of research, Hannah is passionate about science outreach and loves reading, playing the piano, teaching, and mentoring.
Bioengineering
1st Year Bioengineering PhD Student
Education:
Research Area:
Motivational control of behavior, optogenetics, neuropsychiatric disoders
Biography:
I am a first-year PhD student in the Bioengineering Department. Before that, I did my undergraduate research in the DiCarlo Lab at MIT, studying the ventral visual stream, and also worked in the Computational Neuroscience Science Lab at Stanford, using neural networks to analyze clinical data, and the Hein Lab at Cornell, using optogenetics and light sheet microscopy to study motor behavior in zebrafish.
Bioengineering
2nd Year Bioengineering PhD Student
Education:
Research Area:
Characterization of brain waste clearance with motion-encoding MRI
Biography:
I am a Bioengineering PhD student in the Radiological Sciences Laboratory. My research interest is in advancing magnetic resonance imaging (MRI) techniques to understand brain physiology, enhance disease diagnosis, and improve patient care. Before joining Stanford Bioengineering in 2024, I investigated the impact of congenital heart defects on neurodevelopment as part of the Pediatric Heart and Brain Research Group at UCSF. I graduated from the University of San Francisco in 2021 with a BS in Chemistry and Mathematics.
Electrical Engineering
2nd Year Electrical Engineering PhD Student
Education:
Research Area:
brain-computer interface, electrophysiology, nanofabrication, retinal prosthesis
Biography:
Electrical Engineering PhD Student at Stanford University. Research in the areas of brain-computer interfaces, electrophysiology, and nanofabrication, towards the development of retinal implants for vision restoration.
Materials Science
1st Year Materials Science PhD Student
Education:
Research Area:
Metasurfaces, Bioimaging, Optoelectronic materials and devices
Biography:
MinJae Kim is a first-year PhD student and Kwanjeong Doctoral Study Abroad Fellow in Materials Science and Engineering at Stanford University. He received a BS in Materials Science and Engineering at KAIST. Before joining Stanford University, he was a National Presidential Science Scholar, KAIST Presidential Fellow, National University of Singapore (NUS) Young Fellow, and Young Future Energy Leader selected by Khalifa University. He has received many awards and honors, including the national delegation at the Lindau Nobel Laureate Meeting and Global Young Scientists Summit, an invitation to the Nobel Ceremony, and the membership in the Young Engineers’ Honor Society nominated by the National Academy of Engineering of Korea. With these achievements, he has received many recognitions from the Korean government, such as the Talent Award of Korea (Ministry of Education) and a cadetship as the Research Officer for National Defense (Ministry of Defense, Ministry of Science and ICT).
Bioengineering
4th Year Bioengineering PhD Student
Education:
Research Area:
Investigating Batten disease pathology and treatment via multi-omic approaches
Biography:
Nick Manfred is an NSF Graduate Fellow, SIGF Fellow, and Neurosciences PhD Candidate at Stanford University. He received his A.B. with departmental honors in Neuroscience and Behavior from Columbia University, where he conducted research on valence encoding in mouse models of anxiety disorders. Prior to Stanford, he was a connectome annotator for a collaboration between the Zuckerman Institute and the FlyEM Project of Janelia-HHMI, and a Fulbright Scholar at the Max Planck Institute of Biological Intelligence. He is interested in identifying therapeutic targets to treat aging and neurodegeneration by researching lysosomal function. At Stanford, he has participated in LeadX, the Arete Fellowship, ASES Breakthrough, Ignite, MBCT, GRIP. He also has mentored undergraduates through CCOP Bootcamp and completed a PhD minor in Bioengineering.
Bioengineering
2nd Year Bioengineering PhD Student
Education:
Research Area:
Restorative neurotechnologies, systems neuroscience, brain-computer interfaces
Biography:
--------- engineer
Electrical Engineering
1st Year Electrical Engineering PhD Student
Education:
Research Area:
EEG Signal Processing for Clinical Neuroscience
Biography:
I am a mathematician and engineer by training and am driven to use my analytical skills to better understand brain networks through physiologically informed signal processing, information theory, network theory, dynamical systems, and topological methods. I am particularly interested in alterations of brain networks due to drugs and pathologies such as anesthetics, cancer, chemotherapeutic drugs, neurodegenerative diseases, and radiation exposure.
Computer Science
1st Year Computer Science PhD Student
Education:
Research Area:
NeuroAI: develop neuroconnectionist models of the brain to understand behavior.
Biography:
I am a PhD student in the Department of Computer Science. I am interested in how the mammalian brain is functionally and spatially organized over the course of evolution, gestation, and development, and what mechanistic constraints, inductive biases, and environmental statistics shape that organization. To generate hypotheses about so, I use deep artificial neural networks to study how their optimization under different constraints map to their match, both functionally and spatially, to the corresponding biological system being modeled. Prior to starting his PhD, I earned a master's degree in computer science from Stanford University and a bachelor's degree in computer science from the University of California, San Diego. In my free time, I like to be outdoors, read and write, do art, and think about circles.
Research Interests:
My research interests lie in developing neuroconnectionist mechanistic models of the brain that deepen our understanding of neural computation and representations. I aim to explore how physiological and anatomical constraints shape cortical topography and, in turn, scaffold development. I am particularly intrigued by observing certain behaviors emerge from mechanistic models, even when the model was not optimized to do so.
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