All Content

Thu, Aug 20, 2020

What world post COVID-19?: A conversation with Dr. Conrad Tucker

Dr. Conrad Tucker, professor of mechanical engineering at Carnegie Mellon University, explains how the pandemic is changing the conversations around higher education and emerging technologies.

Blog Post by Peter Engelke, Anca Agachi

Coronavirus Education

Thu, Nov 28, 2019

Tucker in Journal of Mechanical Design: 3D design using adversarial networks

In the News by Atlantic Council

Technology & Innovation

Mon, Nov 11, 2019

Tucker in Journal of Mechanical Design: The use of VR to teach manufacturing

In the News by Atlantic Council

Education Technology & Innovation

Dr. Conrad Tucker is currently serving as a science and policy fellow in the Foresight, Strategy, and Risks Initiative at the Atlantic Council’s Scowcroft Center for Strategy and Security.

Dr. Tucker is the Arthur Hamerschlag Career Development Professor in mechanical engineering at Carnegie Mellon University, where he also holds a courtesy appointment in machine learning and is part of the core faculty of the CyLab Security and Privacy Institute. His research focuses on the design and optimization of complex systems through the acquisition, integration, and mining of large scale, disparate data. He currently leads the Artificial Intelligence in Products Engineered for X (AiPEX) Laboratory, which researches the use of machine learning methods to predictively improve the outcome of product design solutions through the acquisition, fusion and mining of large-scale, publicly-available data.

Previously, Dr. Tucker held a joint appointment as associate professor in engineering design and industrial and manufacturing engineering at Pennsylvania State University. He was also affiliate faculty in computer science and engineering, and the director of the Design Analysis Technology Advancement (D.A.T.A) Laboratory. Three characteristics of engineered systems that Dr. Tucker’s research group explored are: i) the ability to sense an environment, ii) the ability to characterize relevant system attributes, and iii) the ability to learn and predict future states that aid decision makers. Through Dr. Tucker’s research, the concept of large scale social media networks serving as low cost, scalable sensor systems has been developed, departing from traditional perceptions of social media networks as merely being platforms for disseminating content and connecting individuals. Dr. Tucker’s research group has utilized social media platforms to quantify cyber security threats, train machine learning algorithms, and model and predict user interactions and behavior.

Dr. Tucker has served as PI/Co-PI on federally and non-federally funded grants from the National Science Foundation (NSF), the Air Force Office of Scientific Research (AFOSR), the Defense Advanced Research Projects Agency (DARPA), the Army Research Laboratory (ARL), the Office of Naval Research (ONR) via the NSF Center for eDesign, and most recently, the Bill and Melinda Gates Foundation (BMGF). He is currently serving as Co-PI in the ARL Cyber CRA at CMU. In February 2016, he was invited by National Academy of Engineering (NAE) President Dr. Dan Mote, to serve as a member of the Advisory Committee for the NAE Frontiers of Engineering Education (FOEE) Symposium. Dr. Tucker is the recipient of the American Society of the Engineering Education’s (ASEE) Summer Faculty Fellowship Program (SFFP) award and conducted research at the Air Force Institute of Technology at the Wright Patterson Air Force Base during Summer 2014 and Summer 2015.  He received his Ph.D., M.S. (Industrial Engineering), and MBA degrees from the University of Illinois at Urbana-Champaign, and his B.S. in Mechanical Engineering from Rose-Hulman Institute of Technology.