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Mon, Aug 14, 2017

Using Machine-Learning to Improve Policymaking

The Atlantic Council’s Science and Policy Fellow presented early-stage research on how machine-learning techniques can help decision makers better understand the public’s perception of new technologies, with significant implications for future policymaking. Dr. Conrad Tucker, an associate professor of computer science and engineering at the Pennsylvania State University, and a science and policy fellow in […]

FutureSource by Samuel Klein

Fri, Jun 23, 2017

Cognitive Systems and the Policy Challenges of the Twenty-First Century

This blog is the first in a series exploring the implications of different policies on the development and deployment of artificial intelligence, machine learning, and cognitive systems. The term “cognition” is defined as “of, relating to, being, or involving conscious intellectual activity”.1 Our world is surrounded by cognitive organisms that range in complexity from an […]

FutureSource by Conrad Tucker

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 holds a joint appointment as associate professor in engineering design and industrial and manufacturing engineering at the Pennsylvania State University. He is also affiliate faculty in computer science and engineering. Dr. Tucker is the director of the Design Analysis Technology Advancement (D.A.T.A) Laboratory. His research focuses on the design and optimization of complex systems through the acquisition, integration, and mining of large scale, disparate data. Three characteristics of engineered systems that Dr. Tucker’s research group explores 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 is a departure 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 principal investigator (PI)/Co-PI on several National Science Foundation (NSF) funded grants and is currently serving as PI and site director of an NSF Industry/University Cooperative Research Center (I/UCRC) at Penn State. Dr. Tucker is part of the inaugural class of the Gates Millennium Scholars (GMS) program. In February 2016, Dr. Tucker 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. 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.