Laboratory for Deep Neurophenotyping: Anoopum Gupta, MD, PhD
Laboratory for Deep Neurophenotyping
100 Cambridge Street
Boston, MA 02114
Explore This Lab
We are a group of neurologists and computer scientists who share the passion for using technology to precisely understand how certain neurologic diseases impact human motor and cognitive function. We believe that capturing high-definition behavior at scale will lead to the discovery of fundamental characteristics of disease that will inform new approaches to therapy development, diagnosis, and management. Our initial focus is on cerebellar ataxia, Parkinson’s disease, and neurodegenerative disease in general.
We are deeply thankful to the patients and patient advocates who donate their time to our research program during their visit to Massachusetts General Hospital. Likewise, this work would not be possible without the generous support from the Ataxia-Telangiectasia Children’s Project (A-TCP) and the Mass General Department of Neurology.
We are currently seeking a Postdoctoral Fellow in Machine Learning. Learn more and apply at the main Partners job site.
We are always looking for individuals with a strong quantitative and algorithmic background as well as a passion for understanding the brain and neurologic disease to lead areas of interest within our group. Contact firstname.lastname@example.org for more information.
Anoopum Gupta, MD, PhD
Dr. Gupta received his undergraduate degree in Electrical Engineering from Georgia Tech, his medical degree from the University of Pittsburgh School of Medicine, and his PhD in Robotics and the Center for the Neural Basis of Cognition from Carnegie Mellon University’s School of Computer Science. He completed his residency in neurology at the Partners-Harvard Neurology Residency Program (Mass General and Brigham and Women’s Hospital). Dr. Gupta’s previous research utilized methods in machine learning and signal processing to understand how large populations of neurons in the hippocampus support learning, memory, and decision making.
Nergis Khan, Clinical Research Assistant
Nergis grew up in Cedar Grove, NJ and graduated with a Bachelor of Arts degree in Neuroscience and a minor in Global Health and Health Policy from Princeton University in 2019. She hopes to pursue a career in medicine that bridges her interest in patient care, health disparities, and the development of medical technology.
Karin Knudson, PhD, Post-Doctoral Fellow
Karin Knudson completed her PhD in mathematics with Jonathan Pillow and Rachel Ward at The University of Texas. Her research has involved bringing methods from machine learning, Bayesian statistics, and compressive sensing to neural data - particularly time series data. Broadly, she is interested in how probabilistic modeling and machine learning techniques can be used and made interpretable in ways that deepen our understanding of neural systems and benefit human health.
Winnie Ching, Clinical Research Assistant
- Zhuoqing (George) Chang, PhD student in Electrical and Computer Engineering, Duke University
- Krzysztof Gajos, PhD, Gordon McKay Professor of Computer Science at the Harvard Paulson School of Engineering and Applied Sciences, Harvard University
- Albert Hung, MD, PhD, Assistant Professor of Neurology, Massachusetts General Hospital and Harvard Medical School
- Maia Jacobs, PhD, Harvard Paulson School of Engineering and Applied Sciences, Harvard University
- Sunghoon Ivan Lee, PhD, Assistant Professor, College of Information and Computer Sciences, University of Massachusetts Amherst
- Guillermo Sapiro, PhD, Edmund T. Pratt, Jr. School Professor of Electrical and Computer Engineering, Duke University
- Jeremy Schmahmann, MD, Professor of Neurology, Massachusetts General Hospital and Harvard Medical School
- Pavan Vaswani, MD, PhD, Neurology Resident, Massachusetts General Hospital, Brigham and Women’s Hospital, and Harvard Medical School
Mary Donovan, Clinical Research Coordinator, currently a medical student at Georgetown University
Recent publications include:
Azami H, Arnold SE, Sanei S, Chang Z, Sapiro G, Escudero J, Gupta AS (2019): Multiscale Fluctuation-based Dispersion Entropy and its Applications to Neurological Diseases. IEEE Access. 2019; 7:68718-68733. doi:10.1109/ACCESS.2019.2918560.
Jacobs M, Gheihman G, Gajos KZ, Gupta AS (2019): “I think we know more than our doctors:” How online health communities help caregivers manage care teams with limited disease-related expertise. Proceedings of the ACM on Human-Computer Interaction 3, CSCW, Article 159 (November 2019), 22 pages. Summary published at Medium.
Gajos KZ, Reinecke K, Donovan M, Stephen CD, Hung AY, Schmahmann JD, Gupta AS (2019): Computer mouse use captures ataxia and parkinsonism, enabling accurate measurement and detection. Movement Disorders. doi:10.1002/mds.27915