Principal Investigator

Prof. Archana Venkataraman

Archana Venkataraman is a John C. Malone Assistant Professor in the Department of Electrical and Computer Engineering at JHU. She received her Bachelor’s, Master’s, and PhD in Electrical Engineering from MIT in 2006, 2007, and 2012, respectively. She was a postdoctoral associate at both MIT and Yale prior to arriving at JHU. Dr. Venkataraman is also affiliated with the Malone Center for Engineering in Healthcare at JHU, which aims to improve both the quality and efficacy of patient care. Curriculum Vitae

Graduate Students

Niharika Shimona D’Souza

Shimona is currently a third year PhD student in the ECE Department at JHU. Prior to this, she obtained her Bachelor’s degree (B. Tech, Hons.) from the Indian Institute of Technology, Kharagpur in Electrical Engineering, along with a minor in Electrical and Electronics Communication Engineering. Her research interests lie at the intersection of Machine Learning, Signal and Image Processing, and Medical Computer Vision. Currently, she is working on the applications of Numerical Optimization Techniques for multimodal integration of resting state fMRI, structural DTI, and behavioral assessment for characterizing neurological disorders.

Jeff Craley

Jeff is currently a PhD student in the ECE department at JHU. He received his M.S. from Boston University in 2015. He earned a B.S. and B.A. from Virginia Tech in aerospace engineering and English literature, respectively, in 2011. His research focuses on signal processing and machine learning for modeling time series medical signals.

Naresh Nandakumar

Naresh is a second year PhD student in the Electrical and Computer Engineering Department at JHU. He received his bachelor’s degree at Vanderbilt University. His technical focus is in applied machine learning and statistical modeling. His research current projects involve fMRI analysis of pathological cases and functional connectomics of the brain. He is the social and professional development chair of his department in the graduate student association. Naresh also enjoys playing chess, tutoring, and being outdoors. He is always eager to talk to prospective students or collaborators, please email him at: nnandak1@jhu.edu.

Sayan Ghosal

Sayan is a first year doctoral student in the Department of Electrical and Computer Engineering at JHU. His current research focuses on functional connectivity analysis of the latent brain networks of Schizophrenia patients using fMRI. Prior coming to JHU he graduated with First Class Honors from the Department of Electronics and Telecommunication Engineering at Jadavpur University. During his undergrad he was involved in a number of research projects at Jadavpur University, India and University of Alberta, Canada. Sayan is deeply passionate about machine learning, artificial intelligence, human computer interactions and its application in healthcare and different clinical applications. Learn More…

Ravi Shankar

Ravi is currently a PhD student in the ECE Department at JHU. Before joining JHU, he received his bachelors (B. Tech) from IIT Guwahati majoring in Electrical and Electronics Engineering. His undergraduate thesis was on keyword spotting and detection for low resource languages. His current research focuses on utilizing techniques tools from signal processing and machine learning to analyze and manipulate speech data. In particular, he is working on understanding what aspects of human speech affect its perception of emotion. Also, he is working on developing algorithms to morph speech between different emotions without changing its linguistic content. Ravi also enjoys playing tennis and soccer in his free time.

Rohan Nandkarni

Rohan Nadkarni is a Biomedical Engineering Master’s student at JHU. He graduated from UCLA with a B.S. in Bioengineering in 2017. For his Master’s thesis project, he is developing an algorithm that uses arterial blood pressure (ABP) and near-infrared spectroscopy (NIRS) measurements to estimate the ABP corresponding to the lower limit of cerebral autoregulation for individual patients undergoing cardiac surgery. Since ABP must remain above this critical value in order to prevent injuries from insufficient blood flow, computing this quantity on a personalized basis would help improve post-operative outcomes.