Plenary Speaker

MNC 2025 Plenary Speakers List

Dr. Teruo Fujii, President, UTokyo, Japan

Paper Title
Toward the Great Convergence - beyond the silicon-based AI

Short Biography
Dr. Teruo Fujii is the 31st President of the University of Tokyo (UTokyo). He was previously the Executive Vice President in charge of finance and external relations for the university and took the office of the President on April 1, 2021. He has also served as an Executive Member (part-time) of the Japanese Cabinet Office's Council for Science, Technology and Innovation from March 2021 until February 2024.
Dr. Fujii received his Ph.D. in engineering from UTokyo in 1993. His research specializes in applied microfluidics systems and underwater technology.

Short Abstract
The hype of generative AI has led to the huge demand for silicon-based advanced semiconductor devices, and rapid increase in the number of data centers around the world. Even with the cutting-edge semiconductor technologies with high computation efficiency, this trend will be contrary to the idea of sustainability in terms of energy consumption. On the other hand, there's literally a living example of computing machines, i.e., biological computation running in living organisms with very low energy consumption. Here I would like to show the pioneering works in the field of molecular computing based on microfluidic technologies, that is opening up new ways of computation beyond the silicon-based devices. And the strong needs for the great convergence between bio-, silicon- and quantum technologies in the intelligent age will be discussed.

Dr. Jeff Burns, Director of AI Compute, IBM Research, USA

Dr. Vivek K. Singh, NVIDIA, USA

Paper Title
AI and AC for a New Computational Age

Short Biography
Vivek Singh is VP Advanced Technology at NVIDIA, working to improve the computations involved in the design and manufacture of semiconductors, using accelerated computing and AI. He was previously an Intel Fellow and Director of their Computational Imaging Department, leading the development of industry-first solutions in diffractive optics, microscopic inspection, and chip design. Vivek is an SPIE Fellow. He served as president of the Lithography Workshop, honorary visiting professor at Jawaharlal Nehru University in New Delhi, and founding member and chair of the Design Technology Co-Optimization conference in SPIE. Vivek has a B.Tech. from IIT Delhi and a Ph.D. from Stanford.

Short Abstract
Chip manufacturing gets more complex every year, and fundamental physics dampens our desire for continued scaling. The solutions to this problem often involve more precise modeling and intricate optimization strategies, across multiple modules in the Fab. It is clear that if there is a “law” that governs the annual increase in Fab computation, it has an exponent greater than Moore’s Law ever did. Accelerated Computing (AC) helps solve this problem by drastically reducing the cost and energy required for these computations, thereby making possible previously prohibitive techniques and precision. On top of that, Artificial Intelligence (AI) methods, with their increasing ability to describe the physical world, have started to prove themselves in real world situations. This talk will describe the problem, some solutions, and give examples of how AC and AI are moving into production in advanced Fabs.

Dr. Takuya Yasui, TSMC Japan Design Center, Japan

MNC 2025 Plenary Speakers List
Dr. Teruo Fujii, President, UTokyo, Japan Paper Title Toward the Great Convergence - beyond the silicon-based AI Short Biography Dr. Teruo Fujii is the 31st President of the University of Tokyo (UTokyo). He was previously the Executive Vice President in charge of finance and external relations for the university and took the office of the President on April 1, 2021. He has also served as an Executive Member (part-time) of the Japanese Cabinet Office's Council for Science, Technology and Innovation from March 2021 until February 2024. Dr. Fujii received his Ph.D. in engineering from UTokyo in 1993. His research specializes in applied microfluidics systems and underwater technology. Short Abstract The hype of generative AI has led to the huge demand for silicon-based advanced semiconductor devices, and rapid increase in the number of data centers around the world. Even with the cutting-edge semiconductor technologies with high computation efficiency, this trend will be contrary to the idea of sustainability in terms of energy consumption. On the other hand, there's literally a living example of computing machines, i.e., biological computation running in living organisms with very low energy consumption. Here I would like to show the pioneering works in the field of molecular computing based on microfluidic technologies, that is opening up new ways of computation beyond the silicon-based devices. And the strong needs for the great convergence between bio-, silicon- and quantum technologies in the intelligent age will be discussed.
Dr. Jeff Burns, Director of AI Compute, IBM Research, USA
Dr. Vivek K. Singh, NVIDIA, USA Paper Title AI and AC for a New Computational Age Short Biography Vivek Singh is VP Advanced Technology at NVIDIA, working to improve the computations involved in the design and manufacture of semiconductors, using accelerated computing and AI. He was previously an Intel Fellow and Director of their Computational Imaging Department, leading the development of industry-first solutions in diffractive optics, microscopic inspection, and chip design. Vivek is an SPIE Fellow. He served as president of the Lithography Workshop, honorary visiting professor at Jawaharlal Nehru University in New Delhi, and founding member and chair of the Design Technology Co-Optimization conference in SPIE. Vivek has a B.Tech. from IIT Delhi and a Ph.D. from Stanford. Short Abstract Chip manufacturing gets more complex every year, and fundamental physics dampens our desire for continued scaling. The solutions to this problem often involve more precise modeling and intricate optimization strategies, across multiple modules in the Fab. It is clear that if there is a “law” that governs the annual increase in Fab computation, it has an exponent greater than Moore’s Law ever did. Accelerated Computing (AC) helps solve this problem by drastically reducing the cost and energy required for these computations, thereby making possible previously prohibitive techniques and precision. On top of that, Artificial Intelligence (AI) methods, with their increasing ability to describe the physical world, have started to prove themselves in real world situations. This talk will describe the problem, some solutions, and give examples of how AC and AI are moving into production in advanced Fabs.
Dr. Takuya Yasui, TSMC Japan Design Center, Japan