Executive Advisory Committee

The External Advisory Committee (EAC) for the mDOT Center is composed of eminent scholars with diverse and complementary expertise and is assembled with the explicit purpose to obtain feedback and guidance on research directions, software development, CP and SP selection, as well as in the overall structure and operations of the Center.

Current Executive Advisory Committee

EAC Members

Jason Hong, Ph.D.

Professor, School of Computer Science, Human Computer Interaction Institute, Carnegie Mellon University


Carnegie Mellon

Dr. Jason Hong is a professor in the HCI Institute in School of Computer Science at Carnegie Mellon University (CMU). Dr. Hong works at the intersection of human-computer interaction (HCI), privacy, security, and computing systems. His work discovers novel utility of sensors for improving human lives while making security and privacy easier for every human. He is advising the mDOT team on ensuring users’ behavioral privacy and anonymity during mHealth biomarker data analytics, optimization of sensor-triggered mHealth interventions, and real-life deployment of mHealth interventions. Visit Google Scholar page

David Kennedy, Ph.D.

Professor, Psychiatry, UMASS Chan Medical School



Dr. David Kennedy is a professor of Psychiatry at UMass Medical School – Dr. Kennedy is an expert in neuro-informatics, known for his contributions to the advent of MRI-based morphometric analysis, functional MRI, and diffusion tensor pathway analysis. He is the PI of P41 Center called the “Center for Reproducible Neuroimaging Computation (CRNC)”. He is advising mDOT on its administrative and training activities. Visit Google Scholar page

Veena Misra, Ph.D.

Distinguished Professor, Electrical Engineering & Director, ASSIST Center

Susan Murphy


Dr. Veena Misra is is a Distinguished Professor of Electrical and Computer Engineering at North Carolina State University (NCSU) – Dr. Misra is an expert in ultra-low power and self-powered biosensor design, hybrid silicon-molecular electronics, and nano-magnetics. She is the PI of NSF Nanosystems Engineering Research Center (ERC) on Advanced Self-Powered Systems of Integrated Sensors and Technologies (ASSIST). She is advising mDOT’s TR&D3 team on sensor and signal processing architectures to support resource-efficient real-time computation of complex biomarkers on resource-constrained high data-rate sensor arrays. Visit Google Scholar page

David C. Mohr, Ph.D.

Professor, Preventive Medicine (Behavioral Medicine), Medical Social Sciences, & Psychiatry and Behavioral Sciences

Benjamin Marlin

U Mass Amherst

Dr. David C. Mohr received his PhD in Clinical Psychology from the University of Arizona. He was on the faculty at the University of California, San Francisco from 1994 to 2006, when he moved to join the Department of Preventive Medicine at Northwestern University. He is the founder and director of the Center for Behavioral Intervention Technologies (CBITs). Dr. Mohr has been elected as a Fellow of the American Psychological Association and of the Society for Behavioral Medicine. Dr. Mohr’s work focuses on the design and implementation of digital mental health treatments that fit into the fabric of people’s lives and can be sustainably implemented in real-world settings. His research integrates user centered design processes to incorporate stakeholder input into the creation and evaluation of digital mental health services. He is also examining methods of harnessing sensor data from devices such as smartphones to identify behaviors, states, and environmental conditions, and using these to design digital mental health tools that are more effective and easier for people to use. Visit Google Scholar page

Jimeng Sun, Ph.D.

Professor, Health Innovation

Emre Ertin

Ohio State

Dr. Jimeng Sun is the Health Innovation Professor at Computer Science Department and Carle's Illinois College of Medicine at University of Illinois, Urbana-Champaign. Previously, he was at the College of Computing at Georgia Institute of Technology. Dr. Sun develops AI for Healthcare who is known for contributions in deep learning for drug discovery, computation phenotyping, clinical predictive modeling, treatment recommendation, and clinical trial optimization. He is advising mDOT’s TR&D1 team on uncertainty-aware modeling of personalized risk dynamics from sensor-derived biomarkers to enable the discovery of new mHealth interventions. Visit Google Scholar page