Enabling Practical and Rich User Digitization for Health and Wellness

Title: Enabling Practical and Rich User Digitization for Health and Wellness

Abstract: A long-standing vision in computer science has been to evolve computing devices into proactive assistants that enhance our health and wellness and many other aspects of our lives. User digitization is crucial in achieving this vision as it allows computers to intimately understand their users, capturing activity, pose, routine, and behavior. Today's consumer devices - like smartphones and smartwatches - provide a glimpse of this potential, offering coarse digital representations of users with metrics such as step count, pulse, blood oxygenation, and a handful of human activities like running and biking. Even these very low-dimensional representations are already bringing value to millions of people's lives, but there is significant potential for improvement. In my research, I develop new technologies that allow consumer devices to capture rich, continuous representations of their users. Armed with such knowledge, our future devices could offer longitudinal wellness tracking, prevent injuries, extend independence into old age, track progress during rehabilitation, more accurately count calories, promote mental health, monitor chronic diseases, and create safer and more productive work environments, to name just a few domains. Critically, these advances cannot come at the expense of device practicality, meaning my work must be strategic in selecting new sensors and making clever use of existing sensors and edge computation.

Bio: Karan is a Ph.D. candidate at the Human-Computer Interaction Institute in the School of Computer Science at Carnegie Mellon University. He uses his background in machine learning, signal processing, and human-computer interaction to create novel sensing technologies. In his thesis work, Karan has focused on increasing the fidelity of user digitization technologies while retaining or improving user practicality, opening new paradigms in health sensing, natural user interfaces, and context-aware computing. To date, Karan has published over 25 papers at top venues. He is a Siebel Fellow and the Editor-in-Chief of ACM Crossroads (XRDS). His research has been widely covered in the media, including NBC Nightly News, Today Show, CNN, TechCrunch, Engadget, NPR, Fast Company, and Gizmodo among others.