Subhro Das  Subhro Das photo         

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Research Staff Member
MIT-IBM Watson AI Lab, IBM Research, Cambridge, MA, USA
  

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Professional Associations:  AAAI  |  ACM  |  IEEE  |  IEEE Signal Processing Society

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Subhro Das is a Research Staff Member and Manager at the MIT-IBM AI Lab, IBM Research, Cambridge MA. As a Principal Investigator (PI), he works on developing novel AI algorithms in collaboration with MIT. He is a Research Affiliate at MIT, co-leading IBM's engagement in the MIT Quest for Intelligence. He serves as the Chair of the AI Learning Professional Interest Community (PIC) at IBM Research.

His research interests are broadly in the areas of ML Optimization, Reinforcement Learning and Trustworthy ML. At the MIT-IBM AI Lab, he works on developing novel AI algorithms for robust, accelerated, online & distributed optimization; safe, unstable & multi-agent reinforcement learning; uncertainty quantification and human-centric AI systems. He leads the Future of Work initiative within IBM Research, studying the impact of AI on labor market and developing AI-driven recommendation frameworks for skills and talent management. Previously, at the IBM T.J. Watson Research Center in New York, he worked on developing signal processing and machine learning based predictive algorithms for a broad variety of biomedical and healthcare applications.

He received MS and PhD degrees in Electrical and Computer Engineering from Carnegie Mellon University in 2014 and 2016, respectively. His dissertation research was in distributed filtering and prediction of time-varying random fields and he was advised by Prof. José M. F. Moura. He completed his Bachelors (B.Tech.) degree in Electronics & Electrical Communication Engineering from Indian Institute of Technology Kharagpur in 2011. During the summers of 2009, 2010 and 2015, he interned at Ulm University (Germany), Gwangju Institute of Science & Technology (South Korea), and, Bosch Research (Palo Alto, CA), respectively.

 

Current MIT-IBM Research Grants

  • Human-Centric AI: Novel Algorithms for Shared Decision Making
    PI: David Sontag (MIT), Arvind Satyanarayan(MIT), Subhro Das (IBM), Dennis Wei (IBM), Prasanna Sattigeri (IBM)
  • Adaptive, Robust, and Collaborative Optimization
    PI: Ali Jadbabaie (MIT), Asu Ozdaglar(MIT), Subhro Das (IBM)
  • Safety Structures, Certification, and Training for AI in the Feedback Loop
    PI: Luca Daniel (MIT), Alexandre Mcgretski(MIT), Lam Nguyen(IBM), Subhro Das (IBM)
  • Principles and Methods for Exploiting Unlabeled Data in Supervised Learning
    PI: Greg Wornell (MIT), Prasanna Sattigeri (IBM), Subhro Das (IBM)
  • From “What is possible” to “What is economically attractive”: A Business Case Approach for where AI will be Deployed
    PI: Neil Thompson (MIT), Subhro Das (IBM), Brian Goehring (IBM)