| ICCNS 2022 - www.iccns.org
特邀报告专家
Keynote Speakers
Prof. Rajkumar Buyya
Prof. Rajkumar Buyya, Director, Cloud Computing and Distributed Systems (CLOUDS) Lab,
The University of Melbourne, Australia
CEO, Manjrasoft Pvt Ltd, Melbourne, Australia
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 155,100+ 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
Speech Title: 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.
Prof. Robert Minasian
Prof. Robert Minasian, IEEE Life Fellow, OSA Fellow, Fellow of The Royal Society of NSW
The University of Sydney, Australia
Professor Minasian is a Chair Professor with the School of Electrical and Information Engineering at the University of Sydney, Australia. He is also the Founding Director of the Fibre-optics and Photonics Laboratory. His research has made key contributions to microwave photonic signal processing. He is recognized as an author of one of the top 1% most highly cited papers in his field worldwide. Professor Minasian has contributed over 420 research publications, including Invited Papers in the IEEE Transactions and Journals. He has over 100 Plenary, Keynote and Invited Talks at international conferences. He has served on numerous technical and steering committees of international conferences. Professor Minasian was the recipient of the ATERB Medal for Outstanding Investigator in Telecommunications, awarded by the Australian Telecommunications and Electronics Research Board. He is a Life Fellow of the IEEE, a Fellow of the European Academy of Sciences, a Fellow of the Optical Society of America (now Optica), and a Fellow of The Royal Society of NSW.
Speech Title: Integrated Photonic Signal Processing and Sensing
Abstract: Integrated photonic signal processing offers new powerful paradigms for signal processing and sensing systems. This stems from its inherent advantages of wide bandwidth and immunity to electromagnetic interference. Current trends are focused on integrating photonics onto silicon platforms to leverage the highly developed CMOS fabrication technologies and to enable boosting the performance of future systems performing signal processing and deep learning, with the potential for implementing high bandwidth, fast and complex functionalities. Recent advances in silicon photonics integrated signal processing and sensing are presented. These include techniques for LIDAR on-a-chip systems and neural network assisted control for beamsteering, photonic approaches to artificial neural networks for deep learning, programmable integrated photonic processors, and high-resolution integrated sensors using optical microresonators that strongly enhance the light-matter interaction to attain high sensitivity and which utilize deep learning techniques to enhance the photonic sensor interference resilience performance. These photonic processors open new capabilities for the realisation of high-performance signal processing and sensing.
Prof. Chang Ee-Chien
Prof. Ee-Chien Chang, National University of Singapore (NUS), Singapore
Ee-Chien Chang is an Associate Professor in the School of Computing at National University of Singapore (NUS). He received his PhD in Computer Science from New York University and was a postdoctoral fellow with DIMACS in Rutgers University and NEC Labs America. His research focuses on cybersecurity security and is particularly intrigued by cross-domain problems. His earlier works include multimedia security, such as image forensic, image watermarking and biometric cryptography, which is in the intersection of multimedia and applied cryptography. More recently, he has been investigating issues on how machine learning could be applied in security applications, and the security of machine learning under malicious attack. He has published in reputable conferences and journals, including CCS, USENIX Security, AAAI, etc, and is the inventor of a few patents, some of which were acquired by third parties. He has also provided technical consultancy to various organizations. He is a lead-PI of National Cybersecurity R&D Laboratory (NCL), NUS.
Speech Title: Machine learning Forensic
Abstract: Machine learning models, in particular, deep neural networks have achieved excellent performance in many tasks. The development of easy-to-use training tools and widely available datasets further accelerate their adoption. While the wide adoption is encouraging, it would not be surprising to see involvement of ML models in illegal activities, for instance, classification models developed for contraband objects or generative models that violate personal privacy. We believe that there would be a need to investigate information found in suspicious machine learning models, similar to multimedia and digital forensic. For example, a forensic investigators might want to determine the purpose of some ML models found in seized devices, operating as remove services, or simply a badly documented binary files on platforms such as Google Drive or Hugging Face. The limited access to the models, combined with the lack of explainability in deep neural networks, poses significant challenges to investigators. There are known techniques such as membership inference and model inversion that could assist in the investigation but with subtle differences in the scenario settings. In this talk, we would look into works on model forensic and present our recent works in this direction.