Replay at https://www.youtube.com/YouthAILab
Brief Summary:
In this talk, Prof. Xiong outlined the rationale behind the vision for the NSF National AI Institute for Exceptional Education, shared with us the technical approaches they plan to take, and the research challenges they must overcome. He emphasized the significance of leveraging AI to ensure that no child in need of speech and language services is left behind. The success of such AI-driven initiatives could ultimately lead to a society where fewer children fall through the cracks, every child has the opportunity to reach their full communicative potential, and the barriers to learning and interaction imposed by SLP issues are significantly reduced.
Dr. Jinjun Xiong is currently an Empire Innovation Professor with the Department of Computer Science and Engineering at the University at Buffalo (UB). He also serves as the Scientific Director and Co-Director for the $20 M National AI Institute for Exceptional Education (http://ai4exceptionaled.org), and Director for the SUNY-UB Institute for Artificial Intelligence and Data Science (https://www.buffalo.edu/ai-data-scien…. Prior to that, he was a Senior Researcher and Program Director for AI and Hybrid Clouds Systems at the IBM Thomas J. Watson Research Center. He was the former co-founder and co-director of the IBM-Illinois Center for Cognitive Computing Systems Research (C3SR), the success of which in 5 years has led to the 10-year $200M expansion of the center to the IBM-Illinois Discovery Accelerator Institute. His research interests are in across-stack AI systems research, including AI applications, algorithms, tooling, and computer architectures. Many of his research results have been adopted in IBM’s products and tools. He published more than 160 peer-reviewed papers in top AI conferences and systems conferences. His publication won 8 Best Paper Awards and 9 Nominations for Best Paper Awards. He also won top awards from various international competitions, including the championship award for the IEEE GraphChallenge on accelerating sparse neural networks in 2020, and the First Place Awards for the 2019 DAC Systems Design Contest on designing an object detection neural network for edge FPGA and GPU devices, respectively.
For previous Youth AI talks, visit https://www.youtube.com/YouthAILab
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