November 8
@
12:00 PM
–
1:00 PM
ECE is proud to welcome alumnus Matthew Bruehl (BSEE’00), Senior Hardware Infrastructure Engineer with NVIDIA, to campus for a special seminar:
Impacts of AI in Industry
Matthew Bruehl
Artificial Intelligence (AI) has rapidly transformed industries worldwide, reshaping sectors such as healthcare, automotive, manufacturing, and education. By automating complex processes, enhancing data analysis, and enabling predictive insights, AI has increased efficiency and innovation across the board. To succeed in today’s tech industry, employees need a solid understanding of AI and machine learning principles, proficiency in programming languages like Python, and familiarity with AI frameworks such as TensorFlow and PyTorch. Skills in data analysis, ethical considerations of AI deployment, and a commitment to continuous learning are also crucial. In our current roles, we leverage AI through tools that boost productivity, automate routine tasks, and provide data-driven decision support. AI-powered chatbots and virtual assistants enhance customer interactions, while predictive analytics inform strategic planning. Embracing these AI applications positions us at the forefront of technological advancement and value.
Bio: Matthew received a Bachelor’s degree in Computer Engineering, specializing in digital design, from the University of Wisconsin-Madison in 2000. He began his career with Hewlett-Packard in Colorado, where he designed test circuits for the Floating Point Unit of the McKinley Itanium processor. Transferring to Intel in 2005, he continued work on Itanium and Xeon servers, focusing on L1D cache physical design, full-chip composition, and static timing analysis. He later enhanced BIOS testing infrastructure as part of Intel’s BIOS software testing team and led the physical design tool automation flows team for a Department of Energy chip. Returning to the Xeon design team, he served as the physical design automation lead for Skylake and Sapphire Rapids chips. Transitioning to machine learning and artificial intelligence, he developed models for resource utilization and ML training in physical design and validation. After leaving Intel, he joined NVIDIA as a Logic Design ML expert, building server tools and license forecasting models. He currently leads Generative AI LLM inference and infrastructure for the ChipNemo project.