The University at Buffalo Artificial Intelligence Institute brings together educators and researchers from around the world to advance the promise of machine or human-machine systems that can address complex cognitive tasks.
UBuffalo.AI will explore how to combine machines’ superior ability to ingest, connect and recall information with concepts that humans excel at, such as reasoning, judgement and strategizing, to develop dynamic human-machine partnerships.
Bringing together educators and researchers in an interdisciplinary environment to continue to make significant breakthroughs in advancing the promise of machine or human-machine systems that can address complex cognitive tasks.
Although computers can process large amounts of information and perform repetitive tasks rapidly and accurately, modern machine learning approaches are still limited to situations that reflect a fixed set of assumptions, and cannot match human intelligence in coping with unpredictable real-world complexities.
The University at Buffalo Artifical Intelligence Institute was established in 2018 to explore ways to combine machines’ superior ability to ingest, connect and recall information with concepts that humans excel at, such as reasoning, judgement and strategizing, to develop dynamic human-machine partnerships.
The University at Buffalo Artificial Intelligence Institute was established in 2018 to bring together the wealth of expertise in artificial intelligence that exists on campus, in the community and across the state.
AI has the potential to transform every segment of industry; it can accelerate the pace of innovation by enhancing creative intelligence and labor productivity, thus making new products and services possible, as well as new approaches to producing and delivering goods and services.
Recent advances in AI offer tremendous potential for enhancing patient healthcare outcomes and controlling costs. Our goal is to advance the use of AI technologies to yield new breakthroughs in fundamental research into diseases, and apply them across the care continuum for diagnosis, prognosis, treatment planning, patient monitoring, and personalized care.
Hard decisions about criminal justice are increasingly being turned over to “smart machines” that use computer algorithms to analyze vast amounts of data. We are understanding and helping shape how artificial intelligence (AI) tools are used to make decisions that affect the rights and opportunities of citizens
The Advanced Materials Thrust focuses on research at the nexus of materials informatics, human-machine interactions and robotics leading to accelerated innovation in environmentally conscious materials manufacturing and sustainable materials design
Advanced Research Computing, in addition to providing the other AI areas access to advanced computational resources, conducts research and develops tools to improve the performance of machine learning/AI algorithms. This builds on CCR's nationally recognized program for optimizing application performance on HPC infrastructure using XDMoD.
The Language and Vision Thrust area builds on the pioneering work at UB in enabling AI innovation in language and vision analytic sub-systems and their application to the fields of document analysis, biometrics, & scene understanding.
Steve Ko is an associate professor within UB’s Department of Computer Science & Engineering. His research interest is in systems in general. He graduated with PhD from UIUC in 2009, spent one year as a postdoc at Princeton, and joined UB in 2010.
Professor Rajan is the leading proponent of the field of Materials Informatics. His research is centered on the application of information science and data intensive methodologies for the discovery, characterization and modeling of materials.
John E. Tomaszewski MD, is SUNY Distinguished Professor and Peter A. Nickerson PhD Professor and Chair of the Department of Pathology and Anatomical Sciences. Dr Tomaszewski is a leader in digital pathology, computational modeling in histopathology, and the informatics revolution in pathology, where he contributes to international diagnostic guidelines.
Karthik Dantu is an assistant professor in UB’s Computer Science and Engineering Department. His areas of expertise include robotics, sensor networks, embedded systems, and mobile computing. Recently, Dr. Dantu has been coordinating mulit-robot systems, specifically micro-aerial vehicle swarms.
Chunming Qiao is a SUNY Distinguished Professor and Chair of the CSE Department. He has lead the Lab for Advanced Network Design, Evaluation and Research (LANDR) at UB since 1993.
Associate Professor Mark Shepard holds a join appointment in the departments of Architecture and Media Study at the University at Buffalo. He directs the Media Arts and Architecture Program (MAAP) and co-directs the Center for Architecture and Situated Technologies (CAST). His research investigates the implications of emerging technologies for architecture and urbanism.
