Dr. David Ebert

EDUCATION
PhD, Computer Science, The Ohio State University 
MS, Computer Science, The Ohio State University
BS, Computer Science, The Ohio State University
 

EXPERIENCE

• 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
   

RESEARCH INTERESTS

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.
 

AWARDS, HONORS & PROFESSIONAL ACTIVITIES

• 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
   

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.