Embodied Intelligence
Janusz A. Starzyk
pcyborg
Address

School of Electrical Engineering and Computer Science

Russ College of Engineering and Technology

Stocker Center r. 347
Ohio University, U.S.A.

 

Contact

Dr. Janusz Starzyk

e-mail: starzyk@bobcat.ent.ohiou.edu

Phone: (740)593-1580

Fax: (740)593-0007

 

Short Biography

Janusz A. Starzyk  received M.S. degree in applied mathematics and Ph.D. degree in electrical engineering both from Warsaw University of Technology, Warsaw, Poland, and habilitation degree in electrical engineering from Silesian University of Technology in Gliwice, Poland. He worked as an Assistant Professor at the Institute of Electronics Fundamentals, Warsaw University of Technology, Warsaw, Poland. Subsequently, he spent two years as a Post-Doctorate Fellow and research engineer at McMaster University, Hamilton, Canada. Since 1991he has been a professor of Electrical Engineering and Computer Science, at Ohio University, Athens, Ohio, USA, and a director of Embodied Intelligence Lab.

He cooperated with the National Institute of Standards and Technology in the area of testing and mixed signal fault diagnosis for eight years.  He has been a visiting professor at University of Florence, Italy, and at Nanyang Technological University in Singapore. He has been a technical advisor and Senior Scientist at Magnolia Broadband Inc. He has been a consultant to Magnetek Corp. and Anteon Corporation, a General Dynamics Company. For several summers he was a visiting faculty at Wright Labs - Advanced Systems Research Group and at Redstone Arsenal - U.S. Army Test, Measurement, and Diagnostic Activity.  For one year he held the position of an IPA fellow at Wright Research Labs, Automatic Target Recognition Group.  He was a visiting researcher at ATT Bell Laboratories - VLSI Systems Research Group and Sarnoff Research Labs. - Mixed Signal VLSI Design Group. 

His current research includes embodied machine intelligence, motivated goal driven learning, self-organizing associative spatio-temporal memories, active learning of sensory-motor interactions, machine consciousness, as well as applications of machine learning to autonomous robots and avatars.