Distinguished Engineer, IBM Quantum Computing Technical Partnership and Systems Strategy, IBM Master Inventor and member of Academy of Technology

Dr. Qiqing Christine Ouyang is a Distinguished Engineer in IBM Quantum Computing Technical Partnership and Systems Strategy. She is an IBM Master Inventor and member of the Academy of Technology.

Dr. Ouyang is a thought leader in Collaborative Innovation for emerging technologies. She is currently building IBM Q Network, a collaboration of industrial, academic, and government organisations worldwide with the mission to advance quantum computing and launch the first waves of commercial applications. Prior to her current role, Dr. Ouyang held various technical executive positions in IBM, where she developed Hybrid Cloud Reference Architecture for Analytics and built long-term, strategic partnership with clients. Dr. Ouyang holds 120+ patents and has 100+ scientific publications in major journals and conferences. She started her career at IBM TJ Watson Research Center as a Research Staff Member. Her deep technical root is in solid-state physics and nanotechnology.

Dr. Ouyang received two B.S. degrees (double-major)with highest honours, one in Electrical Engineering, and the other in Economics and Management from Tsinghua University, Beijing, China; a M.S. in Electrical Engineering from the University of Notre Dame; and a Ph.D. in Electrical Engineering from the University of Texas, Austin.

Keynote:

From Sci-fi to Reality: Quantum Computing is Here

Abstract:

Classical computers have been and will continue to be a driving problem-solving force, but many of the world’s biggest mysteries and potentially greatest opportunities remain beyond their grasp. Here at IBM, we believe that will augment classical computing to potentially open doors that we once thought would remain locked indefinitely.

Quantum computers are incredibly powerful machines that offer a novel approach to processing information. Built on the principles of quantum mechanics, they exploit complex and fascinating laws of nature that are always there, but usually remain hidden from view. By harnessing such natural behaviour, quantum computers can run new types of algorithms to process information more holistically.
While quantum computing is still in its infancy, rapid progress is driving scientific advancements in realizing quantum’s potential in areas such as chemistry, finance, machine learning and optimization. Christine will discuss this radically different approach to computing and how the roadmap for mainstream adoption of this new technology is being forged today by IBM in collaboration with a global community across business, academia and research.

Director, National Supercomputer Centre in Guangzhou,China &
Professor, Sun Yat-sen Universitiy

Professor Yutong Lu is the Director of the National Supercomputing Center in Guangzhou, China. She is the professor in School of Computer Science, Sun Yat-sen University. She is a member of Chinese national key R&D plan HPC special expert committee She got her B.S, M.S, and PhD degrees from the NUDT. Her extensive research and development experience has spanned several generations of domestic supercomputers in China. Prof. Lu is deputy chief designer of Tianhe Project. She had won first class award and outstanding award of Chinese national science and technology progress in 2009 and 2014 respectively. She is leading several innovation projects on HPC and Bigdata supported by MOST, NSFC and Guangdong Province now. Her continuing research interests include parallel operating systems (OS), high-speed communication, large scale file system& data management, advanced HPC/BD/AI convergent application environment.

Keynote:

Capable Platform for the Next Generation Supercomputing

Abstract:

Supercomputing technology has been developing very fast, impacted science and society deeply and broadly. Computing-driven and Bigdata-driven scientific discovery have become a necessary research approach in global environment, life science, nano-materials, high energy physics and other fields. Furthermore, the rapidly increasing computing requirements from economic and social development also call for the power of Exascale system. Nowadays, the development of computing science, data science and intelligent science has brought new changes and challenges in system, technology and application of HPC. The usage mode and delivery mode based on cloud computing also attract supercomputer users. The future Exascale system design faces many challenges, such as architecture, system software, application environment and so on. This report will analyse the usage mode of the current Supercomputing Center and then discuss the design and application environment of future supercomputing systems.

Professor, Applied Mathematics,
Stony Brook University

Deng Yuefan is a Professor of Applied Mathematics at Stony Brook University, the Mt. Tai Scholar at the National Supercomputer Centre of China in Jinan, China’s most prestigious Thousand-Scholar Program awardee, and a Visiting Professor of Computer Science at the National University of Singapore. Prof. Deng earned his BA (1983) in Physics from Nankai University and his PhD (1989) in Theoretical Physics from Columbia University.

Prof. Deng’s research covers parallel computing, molecular dynamics, Monte Carlo methods, and biomedical engineering. He has published more than 85 papers in these areas and supervised 25 doctoral theses. He is the architect of the Galaxy Beowulf Supercomputer at Stony Brook built in 1997 and of the NankaiStars Supercomputer which was China’s fastest when it was completed in 2004. He also built a supercomputer prototype called RedNeurons in 2007 with financial support from China’s Ministry of Science and Technology and Shanghai’s Commission of Science and Technology. His research in the US is supported by DOE, NSF, NIH, as well as New York State. He has lectured widely in the US, Germany, Russia, Brazil, Singapore, as well as the Greater China region.

Keynote:
Supercomputing Multiscale Modeling in Biomedical Engineering Guided by Machine Learning for Optimal Accuracy and Efficiency

Abstract:
TBC

Co-Founder Of SenseTime, Assistant Professor at The Chinese University of Hong Kong (CUHK)

Professor Dahua Lin is Co-Founder of SenseTime. He is also an assistant professor at the Department of Information Engineering, the Chinese University of Hong Kong (CUHK) and the director of the CUHK-SenseTime Joint Lab. Prior to joining CUHK, he served as a research assistant professor at Toyota Technological Institute at Chicago from 2012 to 2014. His research interest covers computer vision, machine learning and big data analytics. In recent years, he primarily focuses on deep learning and its applications on high-level visual understanding, probabilistic inference and big data analytics.

Professor Lin has published about seventy papers on top conferences and journals, e.g. ICCV, CVPR, ECCV, NIPSand T-PAMI. His seminal work on a new construction of Bayesian nonparametric models has won the Best Student Paper Award at NIPS 2010. He also received the Outstanding Reviewer Award at ICCV 2009 and ICCV 2011. He has supervised and co-supervised the CUHK team in international competitions and won multiple awards at ImageNet 2016, ActivityNet 2016and ActivityNet 2017. He also served as an area chair of ECCV 2018.

Dahua Lin received his PhD from the Department of Electrical Engineering and Computer Science(EECS) at Massachusetts Institute of Technology in 2012. He received his M.Phil. from the Department of Information Engineering at the Chinese University of Hong Kong in 2007, and B.Eng. from the Department of Electrical Engineering and Information Science at the University of Science and Technology of China in 2004.

Assistant Director and Director of the
R&D Center, National Supercomputing Center in Wuxi

Dr. Lin Gan is the assistant director, and director of the R&D center, at the National Supercomputing Center in Wuxi. He is also an assistant researcher in the Department of Computer Science at Tsinghua University.

His research interests include high-performance solutions to scientific applications based on state-of-the-art platforms such as CPU, FPGAs, and GPUs. He is currently leading several major projects to develop highly-efficient software and tools for the Chinese homegrown Sunway CPUs and to look for novel architectures for next-generation supercomputing systems.

Dr. Gan is the recipient of the 2016 ACM Gordon Bell Prize, the 2017 ACM Gordon Bell Prize Finalist, the 2018 IEEE-CS TCHPC Early Career Researchers Award for Excellence in HPC, the Most Significant Paper Award in 25 Years awarded by FPL 2015, and the 2017 Tsinghua-Inspur Computational Earth Science Young Researcher Award, etc.

Keynote:
Boosting the Efficiencies for HPC Systems: Lessons from Sunway and Reconfigurable Architectures

Abstract:
There is a strategic shift in HPC system platform architectures. On one side, accelerators like GPUs or even dedicated vector engines are added to the main general-purpose CPUs, whether on chip in homogeneous arrangements like Shenwei, or external like Nvidia or NEC. On the other side, FPGA reconfigurable accelerated computing is gaining traction as a possible integral part of core HPC system configuration, rather than being an options. This talk focuses on some unconventional, but important HPC systems, the Sunway many-core CPU and the FPGA-based reconfigurable engine, and introduce some uniques architectural features and algorithmic arithmetics that are greatly beneficial to the performance of some numerical applications.

Executive Director of the Institute of High
Performance Computing (IHPC), A*STAR

Dr Lim Keng Hui is the Executive Director of the Institute of High Performance Computing (IHPC) in A*STAR. He leads the research institute to advance scientific knowledge, and deliver impact to the industry and society through research in computational modelling and simulation, visualisation and artificial intelligence.

Prior to his current role, Keng Hui was the Director of the Singapore
University of Technology and Design (SUTD)’s Digital Manufacturing & Design Centre (DManD), where he co-led the research centre to develop leading edge capabilities in digital manufacturing and computational design. Concurrently, he was also the Director of the National Additive Manufacturing Innovation Cluster ([email protected]), where he set up and led the translational research centre which focuses on additive manufacturing (AM) R&D with companies, standards development, and industry outreach.

Before SUTD, Keng Hui had held several key appointments in A*STAR. He was the
Deputy Executive Director of the National Metrology Centre (NMC), where he
managed research capability development, resource planning and talent development. He was also the Director of the SERC Engineering Cluster, where he established and managed large scale strategic initiatives, including pioneering programmes in the Future of Manufacturing (e.g. AM, robotics, remanufacturing, optical engineering, logistics & supply chain management), the national Marine & Offshore (M&O) programme, as well as the A*STAR Urban Systems and MedTech programmes. He also supported the establishment of the National Robotics Programme (NRP), A*STAR Technology Adoption Programme (TAP) and Technology Centre for Offshore & Marine Singapore (TCOMS).

Keng Hui was formerly the Head of Product Development at a manufacturing company; CTO and co-founder of a medical image diagnostics startup based on his inventionwith NUS and the National Skin Centre; CTO and co-founder of a medical imaging and robotics start-up in Boston based on his invention at MIT and the Massachusetts General Hospital; and research scientist at the National University Hospital.

Keng Hui is currently an adjunct professor in SUTD. He has served on national-level
R&D committees in advanced manufacturing, robotics and urban solutions, as well as standards committee in AM. He holds several patents, and was a recipient of the
Innovator’s Award from the Prime Minister’s Office for his MedTech work. He received his degrees from Imperial College, MIT and NUS.

Keynote:
Modelling and Simulation: Innovations to Solve Challenges in Data Centres

Abstract:
Data centers are increasingly important due to societal progress and technological advancement. The mobile wireless telecommunication industry’s progress from 4G to 5G is expected to bring about a significant capacity demand for data centers. In addition, moving towards Industry 4.0, cyber-physical systems’ interconnectivity will accelerate further the growth of data center. In view of the increasing criticality of data centers, it has to be protected against many disruptive factors, including heat build up. This is because electronic devices consume electricity and its natural byproduct is heat. In order to ensure reliable operation and satisfactory equipment lifetime, ambient temperature for electronics must be maintained within acceptable limits as temperature affects the performance of electronic systems in many ways. In this talk, I will share how modelling and simulation have been used to develop innovations to solve challenges in data centers, particularly in heat management. Those innovation successes are in collaboration with companies, research institutes, agencies and the academia. This includes server rack design, system modelling of refrigeration cycle and passive on-demand cooling system.

Division Director, Scientific Networking Division, Lawrence Berkeley National Lab
Executive Director, Energy Sciences Network

Indermohan (Inder) S. Monga serves as the Division Director for Scientific Networking Division at Lawrence Berkeley National Lab and Executive Director of Energy Sciences Network, a high-performance network user facility optimized for large-scale science, interconnecting the National Laboratory System in the United States. Under his leadership, the organization also focuses on advancing the science of networking for collaborative and distributed research applications. He contributes to ongoing research projects tackling network programmability, analytics and quality of experience driving convergence between application layer and the network. He currently holds 23 patents and has 20+ years of industry and research experience in telecommunications and data networking. His undergraduate degree in electrical/electronics engineering is from Indian Institute of Technology in Kanpur, India, with graduate studies from Boston University.

Keynote:
Cracking open the network ‘black-box’

Abstract:
The size of the digital universe is growing at an exponential rate, with machine-generated data adding significantly to that growth. Data acquisition in its raw form and its transformation through data analysis into insights requires a network infrastructure that makes collection and movement of data from instrument to data center to high-performance computing or cloud a seamless experience. This talk discusses emerging trend of integrating application workflows with compute, storage, and network resources in unique ways with experiences from Energy Sciences Network, the science network super-highway supporting big-data research in US.

Executive Director, Pawsey Supercomputing Centre

Mark Stickells is a research executive with more than 20 years’ experience working at a senior level in innovative research and business development roles in complex, multi-stakeholder environments.  Through national and international programs and joint-ventures, Mark had successfully led initiatives to accelerate the impact of research, development and education programs for Australia’s key energy, mining and agricultural sectors.

He is a former Chief Executive of an LNG research and development alliance of CSIRO, Curtin University and UWA, partnering with Chevron, Woodside and Shell.  Prior to his appointment at Pawsey Mark led the innovation and industry engagement portfolio at The University of Western Australia. In addition, Mark is the current Chair of the Board of All Saints’ College and was appointed an adjunct Senior Fellow of the Perth USAsia Centre (an international policy think tank) in 2017.

Keynote:
Beyond hyperscale, to hyper-connected – an emerging Asian HPC zone

Abstract:
HPC futures isn’t just a consideration of hardware and software challenges and developments. The future of HPC will largely be shaped by how we use it. The nature of science and the multi-disciplinary complexity of the world’s wicked problems means that collaboration between research and infrastructure providers, subject experts, industry and government will only increase. We need to collaborate at scale across geographic boundaries to tackle issues that affect us worldwide, embracing technology, diversity, and utility.
Our HPC future is hyper-connected. We are uniquely placed to accommodate challenges of both distance and scale. But in addition to making advances in hardware and software, and growing a pipeline of talent with the necessary digital skills, we need digitally-literate people who can build linkages, support collaboration, and span historical boundaries. By engaging, collaborating, and working at scale across both geographic and organisational boundaries, we recruit diverse perspectives and talents for our problem solving, and enlarge our discovery bandwidth.
Asia has long been an important economic zone. Its future is also as an emerging zone of HPC collaboration and engagement.