Tauhidur Rahman

Tauhidur Rahman is an Assistant Professor at the Halıcıoğlu Data Science Institute, UC San Diego, and directs the MOSAIC Lab. His research focuses on mobile health technologies leveraging acoustic/electromagnetic signals from the human body/environment to monitor health behaviors (e.g., eating, sleep, addiction) and environmental factors (e.g., food quality, disease spread). His work integrates applied physics, machine learning, and embedded systems to create low-power, unobtrusive sensing solutions.

Education:

• PhD in Information Science, Cornell University (2017)
• MS in Electrical Engineering, University of Texas at Dallas (2012)
• BS in Electrical and Electronic Engineering, Bangladesh University of Engineering and Technology (2009)

Research Interests: Rahman's work spans three core areas:

1. Sensor Development: High-fidelity capture of physiological/environmental signals using novel modalities like backscattered waves
2. Signal Interpretation: Algorithm development to map raw signals to behavioral/health metrics (e.g., eating patterns, opioid cravings)
3. Mobile Computing: Efficient implementation of algorithms in low-resource devices

Recent Trends in Publications: Recent work emphasizes opioid use tracking, mental health interventions, and digital epidemiology. Notable projects include FluSense (influenza surveillance) and OpiTrack (clinical opioid monitoring), demonstrating real-world impact through NIH/NSF/DARPA funding.

Awards:

• Google Research Scholar Award 2023
• Google PhD Fellowship 2016
• ACM Ubicomp Best Paper Honorable Mention (2015)
• Outstanding Teaching Award (Cornell, 2015)

Grants & Labs: Current funding includes NIH grants for opioid research and NSF awards for sleep/cognitive studies. His lab collaborates with clinical partners and industry (e.g., Intel Pandemic Response Initiative). He co-founded the Digital Biomarkers Workshop series and edited Springer's Contactless Human Activity Analysis.