David Ebert

Professor of CS and ECE Gallogly Chair #3
Associate VP of Research and Partnerships Director
Data Institute for Societal Challenges

Email: ebert@ou.edu
Phone: (405) 325-4275
Office: 5 Partners Pl – 201 Stephenson Pkwy, Ste. 4600

Curriulum Vitae

Education
Ph.D., Computer Science
The Ohio State University
M.S., Computer Science
The Ohio State University
B.S., Computer Science
The Ohio State University

Research Focus

Visual analytics, human-computer teaming, trustable AI, fundamental data science advances with targeted impact in energy and climate resiliency and sustainability, defense and security, health and digital humanities.

Experience and Awards

Dr. Ebert was recently awarded the National Science Foundation's ART: Intensifying Translation of Research in Oklahoma (InTRO) grant.
Silicon Valley Professor of Electrical and Computer Engineering
Director, U.S. DHS Center of Excellence in Visual Analytics
Director, Center for Education and Research in Information Assurance and Security
Director, Purdue University Visual Analytics Center
Associate Professor, School of Electrical and Computer Engineering,
Purdue University
IEEE Fellow
Entrepreneur Leadership Academy Fellow
University Faculty Scholar
IEEE Computer Society Leadership
IEEE Computer Society vgTC Visualization Academy
IEEE Computer Society vgTC Technical Achievement Award
United States Coast Guard Certificate of Merit, VACCINE Social Media Analytics and Reporting Toolkit Project Team
U. S. Coast Guard Meritorious Team Commendation, U.S. Coast Guard, Port Resilience for Operational Tactical Enforcement to Combat Terrorism (PROTECT) Team
Impact Award, DHS S&T
Award of Excellence, DHS S&T

Biography

David S. Ebert is currently a Gallogly Chair Professor of electrical and computer engineering, and the Director of the Data Institute for Societal Challenges. He is the recipient of the 2017 IEEE Computer Society vgTC Technical Achievement Award, member of the IEEE vgTC Visualization Academy, an adjunct Professor of electrical and computer engineering with Purdue University, and the Director of the Visual Analytics for Command Control and Interoperability Center (VACCINE), the Visualization Science team of the Department of Homeland Security’s Visual Analytics and Data Analytics Emeritus Center of Excellence. He received his Ph.D. in computer and information science from The Ohio State University, Columbus, OH, USA, and performs research in visual analytics, novel visualization techniques, interactive machine learning and explainable AI, human–computer teaming, advanced predictive analytics, and procedural abstraction of complex, massive data.

Selected Patents

US Patent No. 8,924,332 – “Public safety camera identification and monitoring system and method,” issued on July 2, 2019.
US Patent No. 8,924,332 – "Forecasting Hotspots Using Predictive Visual Analytics," issued on December 30, 2014.
US Patent No. 8,882,664 – "Animal Symptom Visual Analytics," issued on November 11, 2014.
US Patent No. 8,849,728 – "Visual Analytics Law Enforcement Tools," issued on September 30, 2014.

Selected Publications

Snyder, L. S., Lin, Y.-S., Karimzadeh, M., Goldwasser, D., & Ebert, D. S., “Interactive Learning for Identifying Relevant Tweets to Support Real-time Situational Awareness,” IEEE Transactions on Visualization and Computer Graphics, to appear 2020.
Zhao, J., Karimzadeh, M., Snyder, L. S., Surakitbanharn, C., Qian, Z. C., & Ebert, D. S., “MetricsVis: A Visual Analytics System for Evaluating Employee Performance in Public Safety Agencies,” IEEE Transactions on Visualization and Computer Graphics, to appear 2020.
Khayat, M., Karimzadeh, M., Ebert, D. S., Ghafoor, A. “The Validity, Generalizability and Feasibility of Summative Evaluation Methods in Visual Analytics,” IEEE Transactions on Visualization and Computer Graphics, to appear 2020.
Khayat, M., Karimzadeh, M., Zhao, J., Ebert, D. S. “VASSL: A Visual Analytics Toolkit for Social Spambot Labeling,” IEEE Transactions on Visualization and Computer Graphics, to appear 2020.
Lee, C., Jin, S. Kim, D., Maciejewski, R., Ebert, D., Ko, S., “An Visual Analytics System for Exploring, Monitoring, and Forecasting Road Traffic Congestion,” IEEE Transactions on Visualization and Computer Graphics, 2019.
Chen, M., Ebert, D., “An Ontological Framework for Supporting the Design and Evaluation of Visual Analytics Systems,” Computer Graphics Forum (Proc. IEEE EuroVis 2019), 2019.