Professor Bocko earned his PhD in Physics from the University of Rochester in 1984 with research in the field of gravitational wave detectors and the quantum limits of weak force detection in the group of David H. Douglass. After a brief post-doctoral appointment in the same laboratory, he joined the Rochester ECE department in 1985. His research has spanned multiple areas with its current focus on audio and acoustic signal processing.  Previous research has been in the areas of electromechanical transducers, image sensors, non-contact ECG sensors, low-noise electronics, digital superconducting electronics, quantum coherent electronics, quantum computing, and quantum noise. He is also the Director of the Center for Emerging and Innovative Sciences (CEIS), a NYSTAR-supported Center for Advanced Technology at the University of Rochester with the mission of promoting economic development through joint university-industry research and technology development. Professor Bocko has taught courses on solid state devices, microwaves, circuits and systems, audio signal processing, and acoustics. He won five teaching awards at the University of Rochester and was named the Mercer Brugler Distinguished Teaching Professor at the University from 2008 to 2011. He was named Distinguished Professor of Electrical and Computer Engineering in 2013 and served as Chair of the ECE Department from 2004-2010 and again from 2012-2015.

Raffaella Borasi is currently the founding director of the University of Rochester Center for Learning in the Digital Age, whose mission is to help educators leverage digital technologies through a combination of research projects, program offerings, networking opportunities, and services.  Trained as a mathematics educator, over her career Borasi has expanded her interests and projects to include online learning, integration of technology, teacher preparation and educational entrepreneurship across fields.  To date, she has been a principal investigator in 17 NSF grants totaling over $19M, many of which have involved interdisciplinary teams.  The author of five books and over 40 peer-reviewed articles and book chapters, she has also been exploring other venues for dissemination – including ebooks, videos and websites, as well as a variety of professional publications. She has also sponsored doctoral dissertations on applications of AR/VR to education. Her most recent work has focused on applications and implications of AI for education.

Karl Guttag has 43 years of experience in the areas of display devices (LCOS and DLP) and systems including Heads Up Displays (HUD) and Near-Eye Display (augmented reality and virtual reality), Graphics and Image Processors/Co-processors, Digital Signal Processing (DSP), memory architecture, and CPU architecture and consumer video devices.

Mr. Guttag holds a bachelor’s degree in electrical engineering from Bradley University and a master’s in electrical engineering from the University of Michigan. He worked as a fellow at Texas Instruments and served as a leader of multiple display companies: he was the CTO of Silicon Display Incorporated, Syndiant, Navdy, and the CEO of iTreatR Inc. and Ravn.

Since 2011, he has written the technical blog KG On Technology (www.kguttag.com). KGOnTech is a leading source of technical information on the microdisplays (LCOS, DLP, Laser Scanning, OLED, and MicroLED), small projectors, Augmented Reality Headsets, and Heads Up Displays for Automotive use. Over 20,000 people have read articles in KGOnTech in a single month.

He is named inventor on 150 issued U.S. Patents, including key patents related to display devices, graphics/ imaging processors, graphics interface circuits, microprocessors, signal processing (DSP), Synchronous DRAMs, and Video/Graphics DRAM. Billions of dollars of revenue have been attributed to products using these inventions.

Bernie has over 35 years of experience in space and airborne applications focused on imaging and data analytics. He has over 30 publications and 9 patents.

• As the AI Chief Architect, he is leading the AI Strategic Initiative Space and Airborne Systems. This strategic initiative includes a coordinated development of AI capability that spans Intelligent space, Cyber, autonomous systems, Cognitive Electronic warfare, data analytics, and aviation safety. Developing technology roadmaps on how to leverage the most recent Advances in AI Technology like Convolutional Neural Networks (CNN), Large Language Models (LLMs), Knowledge Graphs, explainable AI (XAI) and Graphical Neural Networks (GNN). This strategic Initiative includes significant Internal Research and Development, organizational changes, AI training, and University and small business partnerships. As part of this strategy, Bernie has developed the company’s Responsible AI Policy and Guidelines.

• Bernie is part of the team that reviews AI companies for our partnership with Shield Capital Venture Investment fund and is overseeing multiple partnerships with startup AI companies.

• Bernie is co-chairing the Corporate wide Technical Network on Artificial Intelligence and Autonomous Systems. This group helps defines the technology trends and disruptors that will impact the company. This group also coordinates internal Technical Exchange meetings between internal groups, external groups, universities, and startups on AI Technology.

• Serving on the Technical Guidance Board for HowSo (an explainable AI company that L3Harris has invested in) and previously served on the board of directors for the Rochester Data Science Consortium a NY state initiative with the University of Rochester, L3Harris, and Wegmans to increase AI and Data Science in upstate NY.

• Bernie has been in many leadership roles including the Chairman of the National Imagery Transmission Format (NITFS) Bandwidth Compression Board that defined 4 standards within the NITFS suit of standards. He also Spent 10 years as the ANSI Chairman and head of US delegation to ISO/JTC1 for the development of JPEG 2000, JPEG-XR, JBIG, and JBIG-2.

Dr. Venu Govindaraju is Distinguished Professor and Vice President for Research and Economic Development at the University at Buffalo, State University of New York.

With a prolific career spanning over three decades, Dr. Govindaraju has led research projects funded by federal agencies and high-tech companies totaling nearly $100 million, holds six patents, and authored close to 500 refereed scientific papers. He is the principal investigator of the National AI Institute for Exceptional Education at UB, a prestigious $20 million initiative funded by the National Science Foundation and the Institute of Educational Sciences.

Dr. Govindaraju is a Fellow of the American Association for the Advancement of Science (AAAS), Association of Computing Machinery (ACM), International Association of Pattern Recognition (IAPR), Institute of Electrical and Electronics Engineers (IEEE), and National Academy of Inventors. In 2024, he received the University at Buffalo President’s Medal; as well, he was named Person of the Year by the Council of Heritage and Arts of India for his contributions to AI.

Christopher Kanan’s research lies in deep learning, with an emphasis on lifelong (continual) machine learning, bias-robust artificial intelligence, medical computer vision, and language-guided scene understanding. He has worked on online continual learning, visual question answering, computational pathology, semantic segmentation, object recognition, object detection, active vision, object tracking, and more. Beyond machine learning, he also has a strong background in eye tracking, primate vision, and theoretical neuroscience.

Research Interests
Artificial Intelligence
Deep Learning
Computer Vision
Cognitive Science
Applied Machine Learning (e.g. Medical Computer Vision)

Learn More about Chris Kanan

Dr. Brendan Mort is the Director of the Center for Integrated Research Computing (CIRC), which provides researchers with hardware, software, training, and support necessary to utilize computational science and big data computing technology in research activities in all areas of academic scholarship. Brendan is responsible for managing a team of computational scientists, software developers, and system engineers who oversee the identification, development, and deployment of computational tools and systems for modeling, analyzing, and visualizing computer-driven research projects. Brendan is a member of the faculty in the Department of Chemistry and affiliated with the Goergen Institute for Data Science and Artificial Intelligence. His research interests include the development of accurate methods to predict chemical structure and properties using computational chemistry, data science, and artificial intelligence. Brendan teaches courses in the application of data science tools and building software applications for data science at scale.