Associate Professor, Industrial and Operational Engineering, Center for Healthcare Engineering and Patient Safety
Amy Cohn, PhD, is an Associate Professor and Thurnau Professor in the Department of Industrial and Operations Engineering at the University of Michigan College of Engineering and Director of the Center for Healthcare Engineering and Patient Safety. Her primary research interest is in robust and integrated planning for large-scale systems, predominantly in healthcare and aviation applications. She also collaborates on projects in satellite communications, vehicle routing problems for hybrid fleets, and robust network design for power systems and related applications. Her primary teaching interest is in optimization techniques, at both the graduate and undergraduate level.
Research Professor, School of Information, Learning Education and Design Lab
Dr. Teasley’s research has focused on issues of collaboration and learning, looking specifically at how sociotechnical systems can be used to support effective collaborative processes and successful learning outcomes. As Director of the LED lab, she leads learning analytics-based research to investigate how instructional technologies and digital media are used to innovate teaching, learning, and collaboration. The LED Lab is committed to providing a significant contribution to scholarship about learning at Michigan and in the broader field as well, by building an empirical evidentiary base for the design and support of technology rich learning environments.
Yi Lu Murphey
Associate Dean for Graduate Education and Research, Professor of Electrical and Computer Engineering, U-M Dearborn
Dr. Murphey’s research interests include computer vision, pattern recognition and artificial intelligence. She has publications in the areas of low level vision processes, knowledge-based computer vision processes, handwritten digit recognition, machine-printed character segmentation and recognition, medical image analysis, engineering diagnostics, intelligent systems. She is a senior member of IEEE, a member of AAAI, and an associate editor for Pattern Recognition.
Assistant Professor, Industrial and Systems Engineering, Georgia Institute of Technology
Yao Xie is an assistant professor in the Stewart School of Industrial & Systems Engineering at Georgia Tech. Her research interests are in sequential statistical methods, statistical signal processing, big data analysis, compressed sensing, optimization, and has been involved in applications to wireless communications, sensor networks, medical and astronomical imaging.
Dr. Xie previously served as Research Scientist in the Electrical and Computer Engineering Department at Duke University after receiving her Ph.D. in Electrical Engineering (minor in Mathematics) from Stanford University in 2011.
This talk is part of the MIDAS Seminar Series and will take place at the Rackham Amphitheater at 4 p.m followed by a reception at 5pm.
Professor, Electrical Engineering and Computer Science
Dr. Liu’s research interests include optimal resource allocation, sequential decision theory, incentive design, and performance modeling and analysis, all within the context of communications networks. Her most recent research involves online learning, modeling and mining of large-scale internet measurement data concerning cyber-security, and incentive mechanisms for interdependent security games.
Emily Mower Provost
Assistant Professor, Electrical Engineering and Computer Science
Dr. Mower Provost’s research focuses on mathematical representation of emotion and emotion expression and perception, integrating machine learning techniques and multimodal signal processing in pursuit of the design of interpretable data representations.
Moderator: Anna Gilbert
Professor, Mathematics, Electrical Engineering and Computer Science
WELCOME , PANEL
Dr. Gilbert’s research interests include mathematical analysis, probability, networking, and algorithms. She is especially interested in randomized algorithms with applications to harmonic analysis, signal and image processing, computer networking, and massive datasets..