2022 was the inaugural year of the Institute for Artificial Intelligence and Data Science (IAD) Distinguished Speaker Series. Each year we bring some of the nation's most prominent researchers and innovators from academia, government, and industry to speak on topics of interest to the artificial intelligence, computational science, and data science community in Buffalo.
Scientific modeling has transformed healthcare phenomenally. There are several problems in healthcare that are not solved yet owing to lack of full understanding of the underlying mechanism. More recently, machine learning has come into prominence. Several problems are shown to be addressed by machine learning. However, the limitation is its indifference to biology and natural principles. A novel hybrid approach called Scientific ML which leverages the best of both approaches will be presented. The potential problems that this revolutionary paradigm can help with will be discussed.
A renowned scientist in the area of quantitative disease models and their application to decisions, Joga heads the interdisciplinary team at Pumas-AI and is instrumental in shaping the company’s vision and roadmap. He is a Professor with the School of Pharmacy and the School of Medicine, University of Maryland, Baltimore and has held various positions at the US FDA between 1999 and 2011.
During his illustrious tenure at the US FDA, Joga oversaw the review of thousands of Investigational New Drug Applications (INDs), over 250 New Drug and Biological Licensing Applications, numerous FDA guidances and policies and was part of the committee responsible for the 21st Review Process. He led both the formation of the Division of Pharmacometrics and a Pharmacometrics Fellowship Program at the FDA. Besides a number of FDA awards, Joga received the Outstanding Leadership Award from the American Conference on Pharmacometrics (2008), the Tanabe Young Investigator Award from the American College of Clinical Pharmacology (ACCP) (2008) and the Sheiner-Beal Pharmacometrics Award from the American Society of Clinical Pharmacology and Therapeutics in 2019.
Joga is on the editorial boards of several journals and a Fellow of ACCP, AAPS and International Society of Pharmacometrics. He has published over 100 papers and book chapters.
Feeling stuck in your job search? Marcelo Barros, Founder, The International Advantage, will be back at UB’s School of Engineering and Applied Sciences as part of IAD Days to lead a session that will focus on how international students can capitalize on the power of strategic networking to overcome visa challenges, get advice, get smarter, and ultimately secure job referrals.
Marcelo Barros is the founder of The International Advantage, LLC, a small firm with a big ambition: to help every international student in the U.S. achieve their job search goals. With a rare combination of career services experience working with international students and 10+ years of work experience with top U.S. global firms, plus the experience of having been an international student himself, Marcelo helps international students, accomplish their job search goals by using innovative job search methods and frameworks. In his book, The International Advantage Get Noticed. Get Hired!, Marcelo shares the strategies he has used to help international students secure quality jobs. Marcelo's work has been noticed by Forbes, Bloomberg, Business Week, American Marketing Association, The Times of India, Inside Higher Ed, Vault, France 2, and several other publications.
Our national power grid has evolved to a pivotal point – not only does the grid need to provide reliable, resilient, and affordable electricity for societal prosperity and economic development, but also the grid needs to ensure a sustainable and equitable energy future, aligning with the new administrative goals of clean electricity by 2035 and fully decarbonized economy by 2050. As a result, the energy mix is shifting toward clean energy resources, and it leads to significant technical and policy challenges. Driven by the big push for deeper electrification and decarbonization, the electricity demand could double in the next two decades, and more than 80% of electricity will be generated, transferred, and/or consumed through power electronics interfaces. These include wind and solar generation, electric vehicle charging, and new building equipment. This is fundamentally changing the system dynamics as the new resources displace conventional inertia-heavy synchronous generators. But this is also bringing an opportunity for a better future grid – more responsive and flexible! To this end, the electric infrastructure needs to expand; energy storage needs to meet grid-scale application requirements; plus, new markets need to be in place to incentivize the support and services from these new resources. This talk will discuss the trends, challenges, and opportunities for grid modernization in this unprecedented clean energy transition.
Dr. Zhenyu (Henry) Huang is Laboratory Fellow at Pacific Northwest National Laboratory (PNNL), Richland, WA and holds a joint appointment of Research Professor at Washington State University, Pullman, WA. He is also Policy Advisor for the US Department of Energy (DOE)’s Undersecretary for Science and Innovation, leading the DOE crosscutting Grid Modernization Initiative and the White House interagency Net Zero Grid and Electrification Game Changers Initiative. He was a Technical Advisor at the DOE EERE Solar Energy Technologies Office (SETO) in 2019 – 2020. At PNNL, Dr. Huang is leading the power electronics and renewable integration portfolios and served as Deputy Sector Manager for grid research. Prior to joining PNNL in 2003, Dr. Huang conducted extensive research on power system stability and harmonics at the University of Alberta (Canada), McGill University (Canada), and the University of Hong Kong. Dr. Huang received his B. Eng. from Huazhong University of Science and Technology, Wuhan, China, and Ph.D. degree from Tsinghua University, Beijing, China. His research interests include high performance computing, data analytics, and optimization and control for inverter- and renewable-dominant power and energy systems. Dr. Huang has over 200 peer-reviewed publications. He is a Fellow of IEEE and is active in several IEEE Power and Energy Society technical committees. Dr. Huang is a registered Professional Engineer in Washington State.
Distributed inference when the participants are only machines or electronic devices, e.g., sensors, has been explored extensively in the signal processing and machine learning literature. However, there are fundamental differences between such rational systems and systems where the agents include humans due to their cognitive limitations, imperfect rationality as well as behavioral uncertainties. In information fusion systems that include humans, modeling and analysis need to take several factors into account, including cognitive biases of humans, mechanisms to handle uncertainties and noise, and unpredictability of humans, in contrast to inference processes consisting of only machine agents.
In this talk, we discuss aspects of human-sensor networks by focusing on specific problems, including collaborative human decision-making with random local thresholds, decision fusion in integrated human-machine networks, prospect theoretic human decision-making in multi-agent systems, and portfolio theory-based resource management. In each case, we aim to optimize the system performance based on appropriate modeling of human behavior. We also summarize current challenges and research directions related to this problem domain.
Dr. Pramod K. Varshney (S’72–M’77–SM’82– F’97–LF’18) is currently a Distinguished Professor of electrical engineering and computer science at Syracuse University and the Director of the Center for Advanced Systems and Engineering. As the Director of CASE, he is responsible for the technology transition of university expertise to make an economic impact in the high-tech economy of New York. He is the author of Distributed Detection and Data Fusion (New York, NY, USA: Springer-Verlag, 1997). His current research interests include distributed sensor networks and data fusion, detection and estimation theory, wireless communications, image processing, radar signal processing, physical layer security, and machine learning.