Dr. Dass joined D2K Lab as Research Scientist in August 2022. His research broadly focuses on integrating ideas from machine learning, parallel and distributed computing, and hardware design to develop algorithms and architecture for large-scale distributed machine learning. In addition to his research, he oversees the finances and day-to-day activities at the D2K Lab while working with the Director of the D2K Lab in making executive decisions and hiring. Before joining D2K, Dr. Dass was a Postdoctoral Research Associate in the Dept. of Electrical & Computer Engineering at Rice University.
Research: Dr. Dass' research broadly focuses on integrating ideas from machine learning, parallel and distributed computing, and hardware design to develop algorithms and architecture for distributed edge, and federated machine learning. He has published papers in peer-reviewed venues such as ICML, ICDCS, IPDPS, HiPC, TPDS, TC, and FPGA. He is a recipient of the Best Poster Award for Ph.D. Thesis among 40 candidates representing 14 Southeastern Conference (SEC) member institutions at the Annual Computing Conference held at the University of Alabama.
Proposal/Grants: Dr. Dass has demonstrated experience in leading the ideation, proposal writing, and budget planning for various grants. During his postdoc at Rice, Dr. Dass led the proposal efforts in securing the following grants: NSF CISE Core Program (Medium, awarded $1.2M), META (Facebook) Network for AI (awarded $50,000), Rice Creative Ventures Fund (awarded $10K), and IEEE/ACM MICRO 2022 Tutorial (selected amongst top proposal).
Teaching: Dr. Dass is also passionate about teaching and mentoring which involves sharing knowledge and exchanging ideas with students. During his Ph.D., Dr. Dass had been actively involved with teaching. His teaching portfolio spans 7 years in various roles (3x Instructor-of-Record, 14x Graduate Assistant Teaching, 2x voluntary instructor) teaching 1000+ undergraduate students across various courses from programming (C++, JAVA, Python), machine learning, computer organization design, and senior capstone projects. He is a recipient of the prestigious TA Excellence Award (2018) and the competitive College of Engineering Graduate Teaching Fellowship (2020) for excellence in teaching at Texas A&M.
Leadership: Dr. Dass has demonstrated ability to recruit, motivate, and lead teams from diverse backgrounds in various roles of VP and Mentor at the Indian Graduate Students Association (IGSA) in TAMU. As a core member of the IGSA executive committee, he has designed, developed, and implemented strategic plans resulting in passing a proposal, leading advocacy efforts at Graduate Student Council, securing sponsorship deals, organizing numerous events, and in IGSA winning the Best Student Organization among 1000+ at TAMU for consecutive years (2014-2017).
Ph.D. in Computer Engineering, Texas A&M University
B.Tech in ECE with Minor in CSE, Indian Institute of Technology (IIT Guwahati)
Honors & Awards
Graduate Teaching Fellowship 2020, Texas A&M University
Best Poster Award, First Annual Computing@SEC, 2019
Teaching Assistant Excellence Award 2018, Texas A&M University