Joyita Dutta

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Joyita Dutta

About Me

I am an Associate Professor in the Department of Biomedical Engineering at the University of Massachusetts Amherst. I direct the Biomedical Imaging and Data Science Lab (BIDSLab). My research focus is to develop signal processing and artificial intelligence based solutions to a range of biomedical inverse problems, including image processing and reconstruction, brain network analysis, and electrophysiological signal processing for healthcare applications. Several of my ongoing research projects are focused on the development of AI-based tools in the context of Alzheimer's disease.



Brief Bio

Education and Training

  • B.Tech. (Honors), 2004 - Electronics and Electrical Communication Engineering, Indian Institute of Technology Kharagpur
  • M.S., 2006 - Electrical Engineering, University of Southern California
  • Ph.D., 2011 - Electrical Engineering, University of Southern California
  • Postdoctoral Fellowship, 2011-2013 - Radiology, Massachusetts General Hospital and Harvard Medical School

Selected Awards and Fellowships

  • Dreem Jury’s Prize, 2019
  • Bruce Hasegawa Young Investigator Medical Imaging Science Award, 2016
  • Tracy Lynn Faber Memorial Award, 2016
  • NIH Mentored Career Development Award, 2015
  • SNMMI CaIC Young Investigator Award, 2013
  • Alfred E. Mann Innovation in Engineering Doctoral Fellowship, USC, 2009–2011
  • Academic Achievement Award, USC, 2010
  • Merit Scholarship from Women in Science and Engineering, USC, 2010
  • American Society of Engineers of Indian origin (ASEI) Scholarship Award, 2006

Selected Grants as PI

  • NIH R03, 2023-2025 (Early Alzheimer’s forecasting from multimodal data via deep transfer learning, evaluated on a large-scale prospective cohort study; MPIs: Fiterau/Dutta)
  • MassAITC Pilot, 2023-2024 (An academic-industrial partnership for AI-based sleep staging in the elderly using the Dreem headband and a smartwatch; PI: Dutta)
  • UMCCTS PPP, 2023-2024 (Super-resolved thalamic imaging biomarkers for neurodegeneration; MPIs: Dutta/Saranathan)
  • NIH R01, 2021-2026 (Longitudinal predictive modeling of tau in Alzheimer’s disease; PI: Dutta)
  • NIH R03, 2021-2023 (Super-resolution tau PET imaging for Alzheimer’s disease; PI: Dutta)
  • NIH R21, 2020-2024 (Sleep metrics from machine learning for Alzheimer's disease diagnostics; MPIs: Dutta/Saxena)
  • Dreem Jury's Prize, 2019-2023 (Dreem-derived EEG measures for noninvasive, scalable pre-AD and AD diagnosis; MPIs: Dutta/Saxena/Pantazis)
  • NIH K01, 2015-2021 (Tau quantitation in AD with high resolution MRI and PET; PI: Dutta)