Robert Aiken
Professor of Computer and Information Science, Temple University

Dr. Robert Aiken
is a Professor of Computer Science and Chair of the Research Committee in the Computer and Information Sciences Department at Temple University. He is the (co-) author of three books as well as more than 80 articles in refereed journals and proceedings.  He has delivered more than 50 invited presentations.  His current research activity includes investigating the applicability of artificial intelligence models to education, developing collaborative learning systems and assessing the impact of technology in K-12 education.  He has been the Principal Investigator for Grants from the National Science Foundation (NSF) totaling over $1,500,000, including a current project, “Developing and Assessing a Course in Fluency in Information Technology”.  He is an ACM Fellow and has received various awards including the ACM Outstanding Contribution Award (1996), the IEEE Computer Society Golden Core Award (1996), IFIP’s highest award, the Silver Core, (1992) and the ACM Special Interest Group on Computer Science Education (SIGCSE) Outstanding Contributions to Computer Science Education (1995) and Lifetime Service Awards (1999).

Craig Bogli
Principal Engineer, Otis Elevator,  United Technologies Corporation

Craig Bogli is Principal Engineer at Otis Elevator.  He has worked as an electrical design engineer on Otis elevator products for 17+ years; initially through a wholly-owned subsidiary of United Technologies Corp. called Building Systems Company, then later at Otis elevator.  Over the last 4 years, he has worked in the Otis Drives group as a circuit designer working in the area of digital and analog circuit design of elevator components.  The elevator "drive" is responsible for converter 3 phase industrial AC power into variable-voltage-variable-frequency 3-phase power to control direction, speed and torque of the elevator motor. Significant engineering tasks include: drive subsystem architectures, mixed-signal ASIC design (specify requirements, test & validate ASIC, integrate ASIC into board design), I/O and communication expansion of DSP through CPLD.

Susan Coleman
Professor of Finance, University of Hartford (Project Evaluator)

Dr. Susan Coleman is the Ansley Professor of Finance at the University of Hartford.  She teaches courses in both corporate and entrepreneurial finance at the undergraduate and graduate levels.  Her research interests include small firm capital structure as well as research on women-owned and minority-owned small firms.  Prior to joining the University of Hartford, Dr. Coleman was a banker and investment banker.  She served as the Vice President in charge of Strategic Planning and New Business Development for Citytrust Bancorp and as a Vice President responsible for venture capital investments for the Wafra Investment Advisory Group.  Dr. Coleman served as the Internal Evaluator for the University of Hartford’s College of Engineering NSF grant “Integrating Engineering Design with the Humanities, Social Sciences, Sciences, and Mathematics” from 2001 through 2002.  This grant funded activities to re-design the undergraduate engineering curriculum making it more integrative across disciplines and also incorporating more “real-world” types of experiences.

Diane Cook
Professor of Computer Science and Engineering, University of Texas at Arlington

Dr. Diane Cook is Professor of Computer science and Engineering at the University of Texas at Arlington and co-director of the Machine Learning and Planning Lab.  Her research interests include machine learning, data mining, and intelligent environments, and artificial intelligence education.  Her research is supported by NSF, DARPA, NASA, and the State of Texas, and has resulted in 155 peer-reviewed publications. 

Michael Daigle
Co-founder of Software Impressions LLC

Michael Daigle is a co-founder of Software Impressions LLC, a software development services and products firm based in Farmington, Connecticut. The company specializes in the development and integration of business applications and has a track record of delivering cost-effective solutions to business problems that improve the end-user’s efficiency and software experience.  He has 22 years experience developing custom business applications. His responsibilities have ranged from development, mentoring and project management on technology projects for dozens of clients, from Fortune 100 to software startup companies. These systems have been deployed globally to hundreds of companies and thousands of users in a number of industries, including Insurance, Distribution, Software, Legal, Finance, and Training. He is currently focused on assisting enterprises to improve their knowledge sharing capabilities via the delivery of structured (data) and unstructured (documents) content into personalized user interfaces utilizing Internet or web-based channels.

Michael Georgiopoulos
Professor of Electrical Engineering, University of Central Florida

Dr. Michael Georgiopoulos is a Professor of Electrical Engineering at the University of Central Florida and co-director of the Machine Learning Lab.  His current research area is in neural network algorithms (with emphasis on ART neural networks), design of smart antennas using neural networks, and modeling of computer generated forces using neural network and symbolic techniques. He serves as an Associate Editor of the IEEE Transactions of Neural Networks.  He has published over 150 papers in journals and conference proceedings and has been principal or co-principal investigator on grants totaling more than $4M. 

Lisa Meeden
Associate Professor and Chair of Computer Science, Swarthmore College

Dr. Lisa Meeden is an Associate Professor and Department Chair of the Department of Computer Science at Swarthmore College.  Her research interests are in the areas of machine learning, artificial intelligence, robotics, and computer science education.  She has been a co-PI on two NSF CCLI grants involving robotics and artificial intelligence.  The objective of the first project was to improve the instruction of undergraduate AI courses by providing a unifying theme based on robots.  The goal of the second project was to make off-the-shelf, industrial robots more accessible to undergraduates by providing an integrated interface for writing control programs.