General Introduction to Blockchain
Dr. Qinghua Lu
Senior research scientist at CSIRO, Australia
Blockchain is an emerging technology that enables decentralisation as new forms of distributed systems where participants can transact without trusting each other. Applications built on blockchain can take advantage of properties such as data immutability, integrity, fair access, transparency, and non-repudiation of transactions. On the other hand, as IoT has become a reasonably mature technology and ready to be widely deployed in various application fields. Garner predicated 5.8 billion enterprise and automotive IoT endpoints will be in use in 2020, which includes not only small sensors, but also big automotive devices consisting a large number of sensors and devices, such as drones and self-driving vehicles. However, how to integrate IoT with blockchain are still unclear. In this tutorial, we will explore the potential opportunities in integration of IoT and blockchain.
Dr Qinghua Lu is a senior research scientist at CSIRO’s Data61, Australia. Before she joined Data61, she was an associate professor at China University of Petroleum. She formerly worked as a researcher at NICTA (National ICT Australia). She received her PhD from University of New South Wales in 2013. Her recent research interest includes architecture design of blockchain systems, blockchain for federated/edge learning, self-sovereign identity, and software engineering for machine learning. She has published 100+ academic papers in international journals and conferences. She is an IEEE senior member.
An Introduction of Membrane Computing
Membrane computing is an unconventional computing area that aims to abstract computing ideas (e.g., computing models, data structures, data operations) from the structure and functioning of cells, as well as from more complex biological entities, like tissues, organs and populations of cells. The computational models that are part of this paradigm are generically called P systems, which are distributed and parallel computing devices. In this talk, inspired by different biological facts, some variants of P systems and their computational power are introduced.
Bosheng Song received the Ph.D. degree in control science and engineering from Huazhong University of Science and Technology, Wuhan, China, in 2015. He spent eighteen months working in the Research Group on Natural Computing, University of Seville, Seville, Spain, from November, 2013 to May, 2015. He was worked as a post-doctoral researcher with the School of Artificial Intelligence and Automation, Huazhong University of Science and Technology, Wuhan, China, from March, 2016 to February, 2019. He is currently an Associate Professor with the College of Information Science and Engineering, Hunan University, Changsha, China. He has published over 50 scientific papers in international journals or conferences, and his current research interests include membrane computing and computational complexity theory.