Director of Mizzou CERI,
Curators’ Distinguished Professor, University of Missouri
Prasad Calyam is a Curators’ Distinguished Professor and the Greg L. Gilliom Professor of Cybersecurity in the Department of Electrical Engineering and Computer Science at University of Missouri-Columbia, and Director of the Center for Cyber Education, Research and Infrastructure (Mizzou CERI). His research and development areas of interest include: Cloud Computing, Machine Learning, Artificial Intelligence, Cyber Security, and Advanced Cyberinfrastructure. He has published over 235 peer-reviewed papers in various conference and journal venues. As the Principal Investigator, he has successfully led teams of graduate, undergraduate and postdoctoral fellows in Federal, State, University and Industry sponsored R&D projects. His research sponsors include: National Science Foundation (NSF), Department of Energy (DOE), National Security Agency (NSA), Department of State (DOS), Army Research Lab (ARL), VMware, Cisco, Raytheon-BBN, Dell, Verizon, IBM and others. His basic research and software on multi-domain network measurement and monitoring has been commercialized as ‘Narada Metrics’. He is a Senior Member of IEEE. He currently serves as an Associate Editor for IEEE Transactions on Network and Service Management.
With the convergence of Artificial Intelligence (AI) and Cloud Computing, there are rich opportunities to create intelligent and scalable solutions in many fields e.g., healthcare, public safety and manufacturing. To create impactful solutions, interdisciplinary collaborations involving technical, social, and economical principles need to be developed to have AI supplement current practices. In this talk, I will outline best practices for interdisciplinary AI collaborations that utilize relevant cloud platforms and foster productivity as well as reduce errors of decision makers (i.e., researchers, practitioners). Case studies of successful interdisciplinary collaborations will be presented to develop AI agents that serve applications such as: cybersecurity training via virtual reality in special education, carbon nanotube manufacturing via image analytics in material discovery, and knowledge discovery via chatbots in healthcare. Lastly, I will describe our efforts to leverage interdisciplinary AI research-inspired learning modules we are developing as part of our Mizzou CloudDevOps efforts to train the next-generation interdisciplinary AI workforce.