Dr. David Doermann is a professor of Empire Innovation and the interim chair of Computer Science and Engineering at the University of Buffalo (UB). He was the inaugural chair of the Institute for Artificial Intelligence and Data Science (IAD) from 2018-2023. Before coming to UB, he was a program manager at the Information Innovation Office of the Defense Advanced Research Projects Agency (DARPA). At DARPA, he developed, selected, and oversaw research and transition funding in computer vision, human language technologies, voice analytics, and media forensics.
From 1993 to 2018, David was a research faculty member at the University of Maryland, College Park. In his role at the Institute for Advanced Computer Studies, he served as Director of the Laboratory for Language and Media Processing and as an adjunct member of the graduate faculty for the Department of Computer Science and the Department of Electrical Engineering. He and his group of researchers focused on many innovative topics related to analyzing and processing document images and video, including triage, visual indexing and retrieval, enhancement, and recognition of visual media's textual and structural components. His recent research has focused on advanced AI techniques for computer vision, medical image analysis, federated learning, neural architectural search, binary neural networks, and detecting false and misinformation in multimedia content. David has over 300 publications in conferences and journals, is a fellow of the IEEE and IAPR, has numerous awards, including an honorary doctorate from the University of Oulu, Finland, and is a founding Editor-in-Chief of the International Journal on Document Analysis and Recognition.
David also successfully co-founded and managed Applied Media Analysis, Inc, building a team of 12 research and developers from 2001-2014. He recognized the need for a cross platform implementation of computer vision algorithms on mobile devices and developed the architecture to port basic image processing and document analysis capabilities to various devices from a wide range of manufacturers. The work, which was supported by Small Business Innovative Research grants, government contracts, Nokia and Ricoh, resulted in the ability to implement an early version of both barcode readers (1D and 2D) and optical character recognition technologies on many devices. David is a leading researcher and innovative thinker in the areas of document image analysis and recognition. He is interested in applying his skills in leadership, mentoring and transition of research to help change the way we perceive and comprehend visual information. The impacts and scale of David's interests are global because documents range from containers for textual and visual info-graphics to dynamic powerful resources that have the ability to seamlessly drive business processes in today’s evolving digital environment.
