Graduate Students – Johns Hopkins

Medha Ramaswamy

Medha Ramaswamy is a Master’s student in Biomedical Engineering with a focus on Computational Medicine at Johns Hopkins University. She earned her B.Tech in Biotechnology from Vellore Institute of Technology, India. With a strong foundation in biology and data science, Medha is passionate about advancing medicine through computational tools. Her current research focuses on identifying EEG-based biomarkers for clozapine-resistant schizophrenia using dynamic network modeling. She is particularly interested in translational research that bridges laboratory discoveries with real-world clinical applications to improve patient outcomes. Outside of academics, Medha is a trained singer and recording artist.

Ana Paola Garcia Alonzo

Ana Paola Garcia Alonzo is a PhD student in the Biomedical Engineering department at The Johns Hopkins University. She earned her undergraduate degree in BME from Tecnologico de Monterrey, Campus Guadalajara in Mexico. Her research interests include neural signal processing, reinforcement learning applications in neuroscience, and assistive technologies. Outside of the lab, she loves exploring Baltimore, finding the best ice cream, baking, and reading. Her email is agarc124@jh.edu.

Surya Pandiaraju

Surya Pandiaraju is a PhD student in the Biomedical Engineering department at The Johns Hopkins University. He earned his undergraduate degree in BME from the University of Waterloo and has experience with neural data analysis in both industry and academic contexts. Surya is interested in translational research leveraging methods in neural signal processing and machine learning to improve tools and treatments for clinicians and patients.

Clara Lemaitre

Clara Lemaitre is a PhD candidate in the Biomedical Engineering Department at the Johns Hopkins University with a BE in Computer Engineering and a BS in Computer Science from the University of Minnesota – Twin Cities. At Hopkins, she is investigating biomarkers for neuropsychiatric disorders and is jointly advised by Sridevi Sarma and Adam Charles. Her research interests include neural signal processing, machine learning, and computational psychiatry.

Sayyida Shazia

Sayyida Shazia completed her engineering degree in biotechnology at Birla Institute of Technology, Mesra, India. She also holds a Masters degree from University of Oxford in nanotechnology. Her PhD project is to study the stunted population of India, which is a prominent and persistent public health problem of India. We are taking a multifactorial approach to study stunting and build statistical models on the vast data collected from different ethnic and regional populations of India. This project is co-supervised with Dr. Parul Christian from the Bloomberg School of Public Health.

Autumn Williams

Autumn Williams is a PhD candidate in the Biomedical Engineering Department at the Johns Hopkins University with a BS+MEng in Operations Research from Cornell University and an MS in Biomedical Engineering. Prior to joining the graduate program at Hopkins, she worked as a Senior Analyst in Clinical Integration Services for MedStar Health. At Hopkins, she is investigating quantitative electrophysiological biomarkers of disorders of consciousness. Her research interests include neural signal processing, biostatistics, machine learning, and neuroethics.

Luis Sanchez

Amir Hossein Daraie

Amir Hossein Daraie is a PhD candidate in the Biomedical Engineering Department at The Johns Hopkins School of Medicine and an M.Eng. student at the Applied Mathematics and Statistics at Johns Hopkins University. He is working on epilepsy seizure prediction, brain stimulation, and seizure network analysis under Professor Sridevi Sarma, Dr. Adam Charles and Dr. Joon Yi-Kang, MD. He earned his dual bachelor’s degree in biomedical and electrical engineering at Tehran Polytechnic. He worked as a research intern at Donders Centre for Cognitive Neuroimaging,
Netherlands. At the Donders Sleep & Memory Lab he developed soft- and hardware solutions for home-based sleep recordings and sleep modulation using single-electrode EEG and deep and machine learning algorithms under the supervision of Prof. Martin Dresler. He has several years of experience as a software developer and embedded system designer in international robotics competitions, RoboCup.

Posts classified under: Graduate Students