Prof. Rajkumar Buyya

Redmond Barry Distinguished Professor, University of Melbourne

Director of the Cloud Computing and Distributed Systems (CLOUDS) Laboratory, University of Melbourne

Neoteric Frontiers in Cloud and Quantum Computing

Abstract: The twenty-first-century digital infrastructure and applications are driven by Cloud computing and Internet of Things (IoT) paradigms. The Cloud computing paradigm has been transforming computing into the 5th utility wherein "computing utilities" are commoditized and delivered to consumers like traditional utilities such as water, electricity, gas, and telephony. It offers infrastructure, platform, and software as services, which are made available to consumers as subscription-oriented services on a pay-as-you-go basis over the Internet. Its use is growing exponentially with the continued development of new classes of applications such as AI-powered models (e.g., ChatGPT) and the mining of crypto currencies such as Bitcoins. To make Clouds pervasive, Cloud application platforms need to offer (1) APIs and tools for rapid creation of scalable and elastic applications and (2) a runtime system for deployment of applications on geographically distributed Data Centre infrastructures (with Quantum computing nodes) in a seamless manner.
This keynote presentation will cover (a) 21st century vision of computing and identifies various emerging IT paradigms that make it easy to realize the vision of computing utilities; (b) innovative architecture for creating elastic Clouds integrating edge resources and managed Clouds, (c) Aneka 6G, a 6th generation Cloud Application Platform, for rapid development of Big Data/AI applications and their deployment on private/public Clouds driven by user requirements, (d) experimental results on deploying Big Data/IoT applications in engineering, health care (e.g., COVID-19), deep learning/Artificial intelligence (AI), satellite image processing, and natural language processing (mining COVID-19 literature for new insights) on elastic Clouds, (e) QFaaS: A Serverless Function-as-a-Service Framework for Quantum Computing, and (f) new directions for emerging research in Cloud and Quantum computing.

Dr. Rajkumar Buyya is a Redmond Barry Distinguished Professor and Director of the Cloud Computing and Distributed Systems (CLOUDS) Laboratory at the University of Melbourne, Australia. He is also serving as the founding CEO of Manjrasoft, a spin-off company of the University, commercializing its innovations in Cloud Computing. He has authored over 850 publications and seven textbooks including "Mastering Cloud Computing" published by McGraw Hill, China Machine Press, and Morgan Kaufmann for Indian, Chinese and international markets respectively. Dr. Buyya is one of the highly cited authors in computer science and software engineering worldwide (h-index=170, g-index=374, and 154,800+ citations). A bibliometric study by Stanford University and Elsevier since 2019 (for six consecutive years), Dr. Buyya is recognized as the Highest-Cited author in the Distributed Computing field worldwide. He graduated 60 PhD students who are working in world-leading research universities and high-tech companies such as Microsoft, Google, and IBM. He has been recognised as IEEE Fellow, a "Web of Science Highly Cited Researcher" for seven times since 2016, the "Best of the World" twice for research fields (in Computing Systems in 2019 and Software Systems in 2021/2022/2023) as well as "Lifetime Achiever" and "Superstar of Research" in "Engineering and Computer Science" discipline twice (2019 and 2021) by the Australian Research Review.

Software technologies for Grid, Cloud, Fog, Quantum computing developed under Dr.Buyya's leadership have gained rapid acceptance and are in use at several academic institutions and commercial enterprises in 50+ countries around the world. Manjrasoft's Aneka Cloud technology developed under his leadership has received "Frost New Product Innovation Award". He served as founding Editor-in-Chief of the IEEE Transactions on Cloud Computing. He is currently serving as Editor-in-Chief of Software: Practice and Experience, a long-standing journal in the field established 54+ years ago. He has presented over 750 invited talks (keynotes, tutorials, and seminars) on his vision on IT Futures, Advanced Computing technologies, and Spiritual Science at international conferences and institutions in Asia, Australia, Europe, North America, and South America. He has recently been recognized as a Fellow of the Academy of Europe. For further information on Dr.Buyya, please visit his cyberhome: www.buyya.com

Prof. Ruigang Yang

Distinguished Professor, Shanghai Jiao Tong University

Overcoming the Sim2Real GAP: Real2Sim2Real, with applications to Autonomous Driving

Abstract: A huge obstacle for AI, in particularly embodied AI, is data, collecting interaction data at the scale comparable to text is formidable. As such, many researchers aim to use simulation data to mitigate the data problem, however, the domain gap between simulation and real scene is still difficult to overcome in many embodied AI tasks. We propose a different solution: Real2Sim2Real, that is, we aim to capture real world data, virtualized it in simulation to generate many varities, then apply the learned policy in the real world. It possesses the authenticity in the real world with the diversity simulation can generate. We show its applications in autonomous drivng.

杨睿刚，上海交通大学特聘教授，IEEE fellow， 2003年于美国北卡罗莱纳大学教堂山分校获博士学位，主修计算机科学。曾任美国肯塔基大学计算机系终身教授, 百度研究院机器人和自动驾驶实验室主任, 嬴彻科技CTO, 杨睿刚博士在包括IJCV、IEEE T-PAMI、SIGGRAPH、CVPR、ICCV在内的计算机视觉和图形学领域顶级期刊和会议上发表论文150 余篇，Google Scholar引用超过两万次，H 指数74.

Prof. Xian-He Sun

Distinguished Professor, Illinois Institute of Technology

AI, Data, and Dataflow under the von Neumann machine

Abstract: Big data, AI, and other data-driven applications generate massive amounts of data and create new data-discovery demands. These applications have fundamentally transformed the computing landscape, making it increasingly data-centric and data-driven. However, the performance improvement of memory and storage systems has lagged that of computing, resulting in a significant I/O performance gap. In this talk, we first introduce our dataflow under von Neumann machine theory in addressing the I/O wall problem, and then present three high performance I/O systems which are designed based on it. For high performance computing I/O systems, we showcase Hermes, an intelligent, multi-tiered, dynamic, and distributed I/O buffering system. Hermes is a big success and has been released as open source under the widely used HDF5 library. To illustrate how Hermes’ success can be extended to other data processing environments, we touch upon activity (log) data issues through our ChronoLog system for Cloud environments. Metadata is the data that manages other data. Finally, we explore enriched metadata for scientific and knowledge insights via introducing our Coeus system development project. We also reflect on the challenges and opportunities presented by the AI and big data era.

Dr. Xian-He Sun is a University Distinguished Professor, the Ron Hochsprung Endowed Chair of Computer Science, and the director of the Gnosis Research Center for accelerating data-driven discovery at the Illinois Institute of Technology (Illinois Tech). Before joining Illinois Tech, he worked at DoE Ames National Laboratory, at ICASE, NASA Langley Research Center, at Louisiana State University, Baton Rouge, and was an ASEE fellow at Navy Research Laboratories. Dr. Sun is an IEEE fellow and is known for his memory-bounded speedup model, also called Sun-Ni’s Law, for scalable computing. His research interests include high-performance data processing, memory and I/O systems, and performance evaluation and optimization. He has over 350 publications and 7 patents in these areas and is currently leading multiple large software development projects in high performance I/O systems. Dr. Sun is the Editor-in-Chief of the IEEE Transactions on Parallel and Distributed Systems, and a former department chair of the Computer Science Department at Illinois Tech. More information about Dr. Sun can be found on his web site www.cs.iit.edu/~sun/.

Prof. Adel N. Toosi

Associate Professor, University of Melbourne

Driving Innovation: Edge-to-Cloud Computing in Transportation and the Future of Electric Vehicles

Dr. Guoyao Xu

混部与基础数据团队负责人，阿里巴巴集团-爱橙科技-技术风险与效能部门TRE-集群管理团队

Large-scale colocation and resource management in Alibaba Group

Prof. Qi Hao

Professor, Southern University of Science and Technology

Towards Trustworthy Autonomous Driving Training and Testing Systems

Prof. Shuai Wang

Associate Professor/Researcher, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences

Model-based learning for fast autotuning robot navigation

Prof. Xitong Gao

Associate Professor, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences

Unseen Battles in the AI Wilderness: Adversarial Threats in AI and Potential Mitigations

Prof. Minxian Xu

Associate Professor, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences

Cloud-native System Support for Efficient Large Language Models Inference Serving

Prof. Meiying Zhang

Research Assistant Professor, Southern University of Science and Technology

Data-driven Credible Testing Scenario Generation and Evaluation System for Autonomous Driving

Prof. Jianbing Shen

Professor, University of Macau

Data-Centric Visual Perception in Self-driving Cars

Prof. Leong Hou U

Associate Professor, University of Macau

Scalable Data Processing Techniques for Effective Learning

Prof. Hui Kong

Associate Professor, University of Macau

Autonomous Robotic Mapping in Urban Environment

Prof. Huanle Xu

Assistant Professor, University of Macau

Serving Large Language Models in Heterogeneous Clusters

Prof. Li Li

Assistant Professor, University of Macau

Embedded AI systems for Federated Learning and LLM

Prof. Zhenning Li

Assistant Professor, University of Macau

Human Like Trajectory Prediction for Autonomous Driving