Understanding the complexity and finding certainty in such uncertain times can deliver major operational advantages for any economical, industrial or scientific assets. The operational team are under increasing pressure to optimize performance while minimising risks and increasing productivity. All set against a volatile global backdrop.
A digital twin is a virtual representation — a true-to-reality simulation of physics and materials — of a real-world physical asset or system, which is continuously updated.
Digital twins aren’t just for inanimate objects and people. They can be a virtual representation of computer networking architecture used as a sandbox for cyberattack simulations. They can replicate a fulfillment center process to test out human-robot interactions before activating certain robot functions in live environments. The applications are as wide as the imagination.
Digital twin technology, with data at its core, is helping scientists, engineers, biologist or even economist gain control and understanding over their resources and assets.
By connecting the right people to the right data, the right processes (mathematics and simulation), one can gain greater end-to-end insights. One can quickly identify the actions and strategies needed to deliver sustainable performance improvements.
In this talk, we discuss how Mathematics, data, simulation and AI make digital twins possible.
Professor Simon See is currently the Solution Architecture and Engineering Senior Director and Chief Solution Architect & Global Head for Nvidia AI Technology Center, NVIDIA Corporation. He is also a Professor at Shanghai Jiao Tong University, Professor in Beijing University of Posts and Telecommunications (BUPT), and Professor in Universitas Indonesia (UI). He is being conferred as a Distinguished Fudan Scholar in September 2018 by Fudan University, Shanghai, China. Previously Professor See is also the Chief Scientific Computing Advisor for BGI (China) and has a position in Nanyang Technological University (Singapore) and King-Mong Kung University of Technology (Thailand). Professor See is currently involved in a number of International computational, mathematical science projects and national AI initiatives. Recently Dr Simon has been appointed as the Executive Director of the ASEAN Applied Research Centre (AARC). His research interests are in the area of High-Performance Computing, Big Data, Artificial Intelligence, Machine Learning, Computational Science, Applied Mathematics and Simulation Methodology. Professor See is also leading some of the AI initiatives in the Asia Pacific. He is a Steering Committee member of NSCC’s flagship High Performance Computing Conference Supercomputing Asia (SCA) since March 2018. He has published over 200 papers in these areas and has won various awards.
Professor See is a Fellow member of IET, Chairman of TaskForce of IEEE’s CIS Neural Networks Technical Committee, a member of IEEE, SIAM, AAAI, and also on the Advisory Team of AIP (AI Professional Association), International Advisory Board of Institute of Operations Research & Analytics (IORA), Advisory Team of Machine Intelligence and Data Analytics Research Centre (MIDARC), School of Computing Sciences (India) and Board of Studies, MS Tech Programs of Mahindra University and the committee member of more than 50 conferences.
Professor See graduated from the University of Salford (UK) with a Ph.D. in electrical engineering and numerical analysis in 1993. Prior to joining NVIDIA, Dr. See worked for SGI, DSO National Lab. of Singapore, IBM, International Simulation Ltd (UK), Sun Microsystems and Oracle. He is also providing consultancy to a number of national research and supercomputing centers.