4th Year Bioengineering PhD Student

Education:

• MS, Bioengineering (2022)
• Tufts University
• BS, Mechanical Engineering, Biomedical Engineering (2021)
• Tufts University

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.

1st Year Neurosciences PhD Student

Education:

• Bachelor of Arts, Neuroscience (2023)
• University of Virginia

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.

5th+ Year Neurosciences PhD Student

Education:

• BS, Neuroscience, biology, chemistry (2017)
• Brandeis University
• MS, Neuroscience (2017)
• Brandeis University

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

1st Year Bioengineering PhD Student

Education:

• Bachelor of Arts, Biomedical Engineering (2023)
• Harvard University

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.

1st Year Biophysics PhD Student

Education:

• Bachelor of Arts, Neuroscience (2021)
• Harvard University
• Master of Philosophy, (2023)
• University College London

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.

3rd Year Electrical Engineering PhD Student

Education:

• B.S., Electrical and Computer Engineering (2023)
• The University of Texas at Austin

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.

1st Year Bioengineering PhD Student

Education:

• Bachelor of Science, Brain and Cognitive Sciences (2021)
• Massachusetts Institute of Technology
• Master of Science, BIOE-MS (2022)
• Stanford University

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.

2nd Year Bioengineering PhD Student

Education:

• Bachelor of Chemistry, Chemistry, Mathematics (2021)
• University of San Francisco
• B.S., Chemistry, Mathematics (2021)
• University of San Francisco

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.

2nd Year Electrical Engineering PhD Student

Education:

• Ph.D., Electrical Engineering ()
• Stanford University
• M.S., Computer Engineering (2023)
• Villanova University
• B.S., Computer Engineering (2022)
• Villanova University

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.

4th Year Bioengineering PhD Student

Education:

• A.B., Neuroscience and Behavior (Departmental Honors) (2021)
• Columbia University

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.

2nd Year Bioengineering PhD Student

Education:

• BS, Computer Science (2024)
• Rice University
• BA, Neuroscience, Cognitive Science (2024)
• Rice University

Research Area:

Restorative neurotechnologies, systems neuroscience, brain-computer interfaces

Biography:

--------- engineer

1st Year Electrical Engineering PhD Student

Education:

• Sc.M., Mathematics (2020)
• Brown University
• B.A., Mathematics (2018)
• University of Wisconsin - Madison

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.

1st Year Computer Science PhD Student

Education:

• Master of Science, Computer Science (2025)
• Stanford University
• Bachelor of Science, Computer Science (2023)
• University of California, San Diego

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.