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Dept. Seminar: Conrad Tucker, Penn State University

Dept. Seminar: Conrad Tucker, Penn State University

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ITB 201

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Ridha Khedri, Fei Chiang, Peter Robinson


Mining Large Scale, Disparate Data for AI-Driven Concept Generation and Evaluation 

The objective of this research is to develop machine learning methods that predictively improve the outcome of design solutions through the acquisition, fusion and mining of large-scale, disparate data. It has been reported that 70-80% of the manufacturing costs of a product are determined during the design phase. Towards enhancing the efficiency of the design process and creating personalized design solutions, our research focuses on three core thrusts: 

  • Research Thrust 1: Feature Discovery and Quantification: Develop machine learning algorithms that mine large scale, data in order to identify and quantify relevant design features 
  • Research Thrust 2: Scalable Generative Design: Develop machine learning models based on Deep Neural Network principles that result in the automatic, scalable generation of design concepts (both 2D sketches and 3D CAD models) 
  • Research Thrust 3: Scalable Design Evaluation: Develop design evaluation methods based on Deep Reinforcement Learning principles that result in the automatic evaluation of design concepts based on computer-learned properties about the physical laws of nature. 

This research has broad applicability across several domains including conceptual design (e.g., AI generated design concepts), manufacturing (e.g., AI model for improving the efficiency of the additive manufacturing process), and education (e.g., advancing personalized learning through adaptive AI). 

BIO:  Dr. Conrad 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 systems through the acquisition, integration and mining of large scale, disparate data. 

Dr. Tucker has served as PI/Co-PI on several federally funded grants from the National Science Foundation (NSF), the Air Force Office of Scientific Research (AFOSR), the Defense Advanced Research Projects Agency (DARPA) and the Office of Naval Research (ONR). He is currently serving as PI and Site Director of the NSF Center for Health Organization Transformation (CHOT), an NSF Industry/University Cooperative Research Center at Penn State. 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. Dr. Tucker is part of the inaugural class of the Gates Millennium Scholars (GMS) program, funded by a $1 billion grant from the Bill and Melinda Gates Foundation.