Thomas Campbell Arnold
Ph.D Student
Peter Galer
Ph.D Student
Nina Ghosn
Ph.D Student
epilepsy. Specifically, I am interested in the application of computational methods to model
optimal stimulation parameters based on electrophysiological biomarkers and changes in
patient behavior. I am also interested in better understanding the behavioral, psychological,
and physiological drivers of seizure risk, and how these triggers can be integrated into a closed-
loop system for the treatment of epilepsy.
Georgios Mentzelopoulos
Ph.D Student
Georgios (George) Mentzelopoulos is a Ph.D student in the Department of Bioengineering. He completed his undergraduate studies at the University of Michigan, Ann Arbor, earning his Bachelor’s degrees in Biomedical Engineering and Electrical Engineering in April 2020.
He is interested in improving neural interfaces with both the peripheral and the central nervous systems. He is currently assisting the development of dry, super-nyquist density EEG arrays to investigate the prospect of phase-guided neuromodulation using transcranial magnetic stimulation. He is also assisting the development of EMG arrays to improve the neural interface of upper and lower limb prostheses.
In his free time, George enjoys tasting local brews, playing volleyball, and reading.
Akash Pattnaik
Ph.D Student
The unpredictability of seizure occurrence remains one of the largest sources of disease burden on persons with epilepsy. Using a rich dataset of intracranial electroencephalogram (iEEG) recordings from epilepsy patients, we seek to understand what factors may increase one’s susceptibility for seizures, and what patterns of brain signals may indicate an oncoming seizure. We use network neuroscience methods and Hidden Markov models to model seizure risk and ultimately seek to develop a warning system that gives epilepsy patients control over their seizures in normal, daily-life
settings
Sneha Shankar
Ph.D Student
Placid Unegbu
Ph.D Student
My primary research interest is centered around closed-loop neuromodulation devices that use biomolecules as a biomarker.
Kevin Xie
Ph.D Student
I am interested in the intersection of computer science and healthcare, specifically the use of machine learning to improve medical therapy and diagnostics. Currently, I am applying Natural Language Processing (NLP) methods to teach machines to read, understand, and extract clinical information from physician progress and discharge notes, with Epilepsy as an experimental lever. I plan to develop algorithms to support clinical decision-making, conduct clinical trials, and replicate critical works.
Yuzhang Chen
Ph.D Student
I'm interested in using novel electrode technologies to study the cellular mechanisms of seizure initiation, propagation, and termination in vivo and ex vivo. Through performing multimodal analysis, I hope to uncover new biomarkers for seizures and then optimize electrical stimulation patterns to acutely terminate seizures. I also hope to uncover the cellular identity of neurons responsible for early seizure termination in vivo.
Royce Dong
M.D/Ph.D Student
I grew up in St. Louis and graduated from Washington University in St. Louis in 2020 with a B.A. in Physics and Chemistry. I plan to get my MD/Ph.D. in Bioengineering at Penn. My research interests include developing novel materials and technologies for neural interfaces.
Jal Panchal
Master's Student
I am a 2nd year ROBO MSE student pursuing my Master’s thesis at the Litt Lab. I specialize in making non-invasive wearable devices and biomedical signal processing. My focus during the thesis will be on identification of physiological biomarkers using wearable devices for the detection of different brain states and seizure activity.
Jakob Michiels
Master's Student
Carlos Aguilla
PhD Student
Analyzing interictal spikes to rigorously locate and predict the SOZ in patients with drug-resistant epilepsy
Andre Revell
M.D/Ph.D Student
Eli Cornblath
M.D/Ph.D Student