Tauhidur Rahman

Interests

Mobile and ubiquitous computing, human health and behavior modeling with statistical signal processing and machine learning, novel on-body and off-body sensor development with embedded systems and applied physics.

Research

Prof. Rahman aims to develop next-generation mobile health technologies that leverages naturally generated and backscattered acoustic and electromagnetic waves from the human body (e.g., heart, skin, lung) and its surrounding environment (e.g, air, food) to unobtrusively, continuously and passively extract information about high-level health and behavioral variables including eating behavior, sleep, alcohol addiction, spread of infectious diseases and food quality.

His research involves (1) low-level sensor development to capture observable low-level physical signals from our bodies and surrounding environments with high fidelity, (2) signal interpretation algorithm development to map these low-level physical signals to relevant biological and behavioral measurements, and (3) mobile computing to run these algorithms in low power and resource settings. His research is interdisciplinary and employs core concepts and theories from different domains including applied physics, embedded and mobile computing, signal processing, machine learning, health sciences and medicine. Professor Rahman's long-term research vision is to rethink the core physical mechanisms of existing health technologies and to impact the way we diagnose diseases, track and manage our health.

Biography

Ph.D., Information Science, Cornell University (2017), M.S., Electrical Engineering, University of Texas at Dallas (2012), B.S., Electrical and Electronic Engineering, Bangladesh University of Engineering and Technology (2009). During his graduate studies, he was a member of the People-Aware Computing (PAC) lab at Cornell University and Multimodal Signal Processing (MSP) lab at UT Dallas. He also completed a research internship at Microsoft Research Redmond. Professor Rahman joined the faculty of the College of Information and Computer Sciences in 2017 as an Assistant Professor and is also affiliated with UMass Amherst's Institute for Applied Life Sciences (IALS).

Activities & Awards

Professor Rahman was a recipient of the Google Ph.D. Fellowship in 2016 in mobile computing. He also received an Outstanding Teaching Award in 2015 from Cornell University. Some of his other notable accomplishments include finalist in Qualcomm innovation fellowship in 2015, one best paper award in ACM Digital Health 2016, one best paper honorable mention award in ACM Ubicomp 2015. He co-chaired the 1st workshop on Digital Biomarkers 2017 (collocated with MobiSys 2017) in Niagara Falls, NY. His research has received several press coverages including Wall Street Journal, NewScientist, MIT Technology Review.