Frank Klassner is a Professor in Villanova's Computing Sciences Department and has served as the second Director of Villanova's Center of Excellence in Enterprise Technology since 2006. His research has studied topics in high-level adaptive signal processing, educational robotics, simulation, and now virtual reality and 3D visualization. He has served as a member of the North America Lego Education Advisory Panel and as a consultant for the Vatican Internet Office and the Vatican Museums. He is founding Treasurer of THECAAV, an organization for promoting best practices for VR on campuses. Dr. Klassner holds MS and PhD degrees in Computer Science from the University of Massachusetts at Amherst and BS degrees in Computer Science and Electronics Engineering from the University of Scranton, Pennsylvania.
Researcher Bios
Robert Beck is a Professor of Computing Sciences at Villanova. He was the founding chair of the Department of Computing Sciences and served as chair for 21 years. He has also served as chair of the Department of Mathematics. He conducts research in the area of Human Computer Interaction and is currently working with persuasive HCI for promoting sustainability. He also leads the Program for Website Creation and Evaluation for the Center of Excellence in Enterprise Technology. His work in the area of Computer Science Education has recently focused on computing in context and the use of inquiry-based learning, problem based learning and authentic research to promote collaboration between disciplines. In the area of Software Engineering, Dr. Beck has focused on formal models of systems and systems.
Benjamin Mitchell is an Assistant Professor in Villanova's Computing Sciences Department. His research is broadly in the field of Machine Learning, with a focus on Deep Learning, Understandable AI, and Computer Ethics. Dr. Mitchell's recent work has included exploring the inductive biases which have enabled these systems to be so successful and describing the practical and ehicall impacts of modern machine learning systems in terms understandable by laypeople. He also has an interest in pedagogy, and researches better ways to teach machine learning and ethics to students.
Mirela Damian is a Professor in Villanova's Computing Sciences Department. Her research is broadly in the areas of computational geometry and graph theory, inspired by problems in wireless networks, graphics, robotics and computational biology. Her most recent work focuses on the design of wireless networks with directional antennas, where the goal is to maximize communication robustness and security while minimizing power consumption and interference. Other projects of interest include reconfigurations of modular robots into structures suited for a certain enviroments or tasks, polyhedra unfolding motivated by industrial design, and DNA computing.
Vijay Gehlot is currently an Associate Professor and Graduate Programs Director in the department of Computing Sciences at Villanova University. He received his PhD in Computer and Information Science from the University of Pennsylvania. His current research focus is applications of Colored Petri Nets (CPNs) in modeling and analysis of systems, including system of systems and system dynamics. Specific focus of his research work include healthcare applications pertaining to workflow and patient safety issues; enterprise service oriented architectures and scalability issues; emergent behaviors of cyber-physical systems; broadband networks architecture, modeling, measurement, and analysis; systems biology and signaling pathways modeling.
Thomas Way is an Associate Professor of Computing Sciences at Villanova. He led a team of 9 faculty, 12 graduate students, 5 undergraduate students and 2 full-time research associates, collaborating with industry engineers from Gestalt LLC (now part of Accenture) and managers from the USAF’s Electronic Systems Center on the Applied Research in Computing Enterprise Services (ARCES) program, CEET’s flagship research project funded by the Department of Defense. His current research is exploring parsing in a variety of forms, such as big data opinion mining, social network extraction, compiler analysis, positional characterization, textual analysis and data translation. He incorporates machine learning, natural language processing and sentiment analysis techniques into his parsing research.