Postdoctoral Research Assoc.
Souptik Barua is currently a postdoctoral research scientist under Dr. Ashutosh Sabharwal in the Scalable Health Lab at Rice University. He obtained his M.S. and Ph.D. in Electrical Engineering with a specialization in data science at Rice University under Prof. Arvind Rao and Prof. Ashok Veeraraghavan. Before that, he got his undergraduate degree (dual Bachelors and Master in Technology) in Electrical Engineering from the Indian Institute of Technology, Kharagpur.
Souptik's research goal is to contribute to the emerging field of digital health using data science models that are clinically meaningful, scalable, and inclusive. He leverages his expertise in machine learning, signal processing, and statistical analysis to discover novel data-driven biomarkers for chronic diseases.
Data science and machine learning for health, computational medicine, biomedical signal processing, biomedical image analysis. Full list of publications on Google Scholar page.
2019 Rice University, Houston, TX Ph.D. in Electrical and Computer Engineering Specialization: Data Science and Machine Learning
2015 Rice University, Houston, TX Master of Science in Electrical Engineering Specialization: Signals and systems
2012 Indian Institute of Technology, Kharagpur Bachelor and Master of Technology (dual degree) in Electrical Engineering Specialization: Signal Processing
Honors & Awards
PATHS-UP Seed Award: Winner of the 2019 and 2021 Precise Advanced Technologies and Health Systems for Underserved Populations (PATHS-UP) Innovation seed grant to research the use of wearable sensors for diabetes management in an underserved Hispanic/Latin
Global Ph.D. Summit Fellow: Selected as one of 13 fellows of the inaugural global PhD summit hosted by EPFL, Lausanne, Switzerland in November, 2018. The theme of the conference was "Data-driven Research in the Life Sciences".
Rice Future Faculty Fellowship: Selected as one of 6 fellows for Rice's 2021 Future Faculty Fellows program. The program provides fellows with expert coaching and training for the faculty application process including preparing research and teaching state