Andrew T. Campbell

A world where mobile AI helps keep people healthy

Research Projects

  • mSITE project (NIMH). Study and develop a context-aware mobile social interaction therapy by exposure (mSITE) intervention based on brief, blended, technology-supported ecological momentary intervention for serious mental illness. With Professor Eric Granholm and Professor Colin Depp (UCSD).
  • Technology-based Treatments for Substance Use Disorders, “Center of Excellence” Grant (P30). Core Director with Lisa Marsch (PI), Alan Budney, Sarah Lord, Cathy Stanger​ ​​(NIH/NIDA​)​
  • West Point AI project (ARL) . Capturing soldier state through continuous smartphone sensing. With the ARL Human Variability Project and West Point.
  • StudentLife project (NIMH) is following 200 students across their four years of college using mobile sensing and brain imaging to study the stress and strains (e.g., stress, anxiety, depression) of college life. The StudentLife project initially started in 2013 with the first study but this is the most ambiguous. Professor Jim Haxby (neuroscientist at Dartmouth College) is PI.
  • Depression project (NIH/NIMH): Personalized Deep Learning Models of Rapid Changes in Major Depressive Disorder Symptoms using Passive Sensor Data from Smartphones and Wearable Devices. Professor Nicholas Jacobson (Geisel School of Medicines) is PI.

  • MOTIV project (NIMH) is studying the connection between brain networks and human behavior to understand motivation in patients with serious mental illness. Professor Deanna Barch (psychology & brain sciences at Washington University in St. Louis) is PI.
  • SABLE project (NSF) is using mobile sensing to study personality in a cohort of students at Stanford, UTA and Dartmouth. Professor Sam Gosling (Personality and social psychologist at University of Texas at Austin) is PI.
  • Crosscheck project (NIMH) is developing models to predict relapse in patients with schizophrenia as part of a randomized control trial at Long Island Hospital. Professor Dror Ben-Zeev (psychiatry and behavioral sciences at University of Washington) is PI.
  • Tessera project (IARPA) is studying (N=750, one year duration, 3 companies) the application of mobile sensing and data science to predict workplace performance. Professor Aaron Striegel (computer scientist at the University of Notre Dame) is PI.
  • Voices project (NIH) is developing mobile and ML technology to study people who experience auditory verbal hallucinations. Professor Dror Ben-Zeev (psychiatry and behavioral sciences at University of Washington) is PI.


  • ACM UbiComp Distinguished Paper Award, 2023
  • ACM UbiComp 10-year Impact Award, 2022
  • ACM SIGMOBILE Test of Time Paper Award 2019.
  • ACM SenSys Test of Time Paper Award 2018.
  • Best Video Award ACM MobiCom 2015.
  • Best Demo Award ACM MobiSys 2015.
  • CenceMe was the first paper to demonstrate how smartphones can be used to derive rich behavioral insights continuously from onboard sensors. Since its publication, the work has inspired a huge body of research and commercial endeavors that have continued to increase the breadth and depth of personal sensing. Some of the activity inference methods that are now common in smartphone operating systems can be traced back to the original CenceMe system" (2019 ACM SIGMOBILE TOT award committee citation), 2019.

  • Honorable mention award: ACM Ubicomp 2015.
  • Best Paper Award at the 1st ACM Workshop on Visible Light Communication (VLC), 2014.
  • Best Paper Nomination Awards ACM Ubicomp 2014.
  • Google Faculty Research Award, 2014.
  • Best Paper Award 4th International Conference on Mobile Computing (MobiCASE), 2012.
  • Best Paper Nomination Award ACM Ubicomp 2011.
  • Friedman Family Fellowship (Dartmouth College), 2009.
  • EPSRC Fellow (UK), Cambridge University, 2003.
  • CenceMe won the ACM SenSys Test of Time Award 2018. The award committee's citation: " At the dawn of the smart phone era, this paper had the foresight to realize that smart phones are human companions and their sensors, collectively, can be used to derive novel social behavior insights. It also pioneered applying machine learning across local devices and servers".

  • NSF Faculty Career Development (CAREER) Award, 1999.
  • IBM University Partnership Faculty Award, 1999.
  • AT&T Foundation Faculty Award, 1996.
  • EPSRC Scholarship (UK), Visiting Scholar, Columbia University, 1994.
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