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Tauhidur Rahman

Assistant Professor

Professor 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.

Current Research

Professor Rahman's 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.

Learn more at www.tauhidurrahman.com/

Academic Background

  • Ph.D., Information Science, Cornell University, 2017
  • M.S., Electrical Engineering, University of Texas at Dallas, 2012
  • Bangladesh University of Engineering and Technology, 2009
Tauhidur Rahman, Alexander Adams, Perry Schein, Aadhar Jain, David Erickson, Tanzeem Choudhury, “Nutrilyzer: A Mobile System for Characterizing Liquid Food with Photoacoustic Effect”, The 14th ACM Conference on Embedded Networked Sensor Systems (SenSys 2016), Stanford, California, USA.
Tauhidur Rahman, Mary Czerwinski, Ran Gilad-Bachrach, Paul Johns, "Predicting “About-to-Eat” Moments for Just-in-Time Eating Intervention", Digital Health 2016. Best Paper Award
Tauhidur Rahman, Alexander Adams, Ruth Vinisha Ravichandran, Mi Zhang, Shwetak Patel, Julie Kientz, Tanzeem Choudhury, "DoppleSleep: A Contactless Unobtrusive Sleep Sensing System using Short-Range Doppler Radar", The 2015 ACM International Joint Conference on Pervasive and Ubiquitous Computing (UbiComp 2015), Osaka, Japan. Honorable Mention Award
Tauhidur Rahman, Alexander Adams, Mi Zhang, Erin Cherry, Tanzeem Choudhury, "BodyBeat: Eavesdropping on our Body Using a Wearable Microphone", GetMobile: Mobile Computing and Communications 2015.
Tauhidur Rahman, Alexander Adams, Erin Carroll, Bobby Zhou, Huaishu Peng, Mi Zhang, Tanzeem Choudhury, "BodyBeat: A Mobile System for Sensing Non-Speech Body Sounds", International Conference on Mobile Systems, Applications and Services (MobiSys 2014), New Hampshire, USA, June.
Tauhidur Rahman, Mi Zhang, Stephen Voida, and Tanzeem Choudhury, "Towards Accurate Non-Intrusive Recollection of Stress Levels Using Mobile Sensing and Contextual Recall'', International Conference on Pervasive Computing Technologies for Healthcare (PervasiveHealth), Oldenburg, Germany, May, 2014.
Phil Adams, Mashfiqui Rabbi, Tauhidur Rahman, Mark Matthews, Amy Voida, Geri Gay, Tanzeem Choudhury, Stephen Voida, "Towards Personal Stress Informatics: Comparing Minimally Invasive Techniques for Measuring Daily Stress in the Wild'', International Conference on Pervasive Computing Technologies for Healthcare (PervasiveHealth), Oldenburg, Germany, May, 2014.
Tauhidur Rahman, Carlos Busso, "A personalized emotion recognition system using an unsupervised feature adaptation scheme", ICASSP 2012: 5117-5120
David Tick, Tauhidur Rahman, Carlos Busso, Nicholas R. Gans, "Indoor robotic terrain classification via angular velocity based hierarchical classifier selection", ICRA 2012: 3594-3600
Carlos Busso, Tauhidur Rahman, "Unveiling the Acoustic Properties that Describe the Valence Dimension", INTERSPEECH 2012
Tauhidur Rahman, Soroosh Mariooryad, Shalini Keshavamurthy, Gang Liu, John H. L. Hansen, Carlos Busso, "Detecting Sleepiness by Fusing Classifiers Trained with Novel Acoustic Features", INTERSPEECH 2011: 3285-3288
Contact Info

College of Information and Computer Sciences
318 Computer Science Building
140 Governors Drive
Amherst, MA 01003-9292

(413) 357-70356