Keynote Speakers
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Topic: Breakthroughs in Cognitive Robots and AI Programming Underpinned by Discoveries in Intelligence Science and Software Science
Abstract
Breakthroughs of basic research in Intelligence Science (IS) [1], [2], [3], [4], [5], [6], [7] and Cognitive Computing (CC) [8], [9], [10], [11], [12], [13], [14] have triggered the emergence of Cognitive Robots (CR) [15], [16], [17] and AI Programming (AIP) technologies [18], [19], [20], [21] towards autonomous software engineering. The latest advances enable the synergy of classical pre-programmed AI and pre-trained AI to an unprecedented platform for machine intelligence generation mimicking human brains and brain-inspired cognitive systems [2], [7], [8]. [31], [35]. It is discovered in IS and CC in general, and in CR and SE in particular, that the target entities had already out of the denotational power of the classic domains of real (R) and binary (B) numbers [21], [25], [29]. This leads to the latest discoveries on that the basic unit of human knowledge as a hyperstructure is a binary relation (bir). Therefore, a new framework of Intelligence Mathematics (IM) [22], [23], [24], [25], [26], [27], [28], [29], [30] has been created for rigorously manipulating the cognitive entities in the brain and cognitive robots spanning from formal concepts, semantics, knowledge, causalities, inferences, and consciousness by contemporary mathematical means for advancing both AI [31], [32], [33] and SE [34], [35], [36], [37].
This keynote lecture presents fundamental theories and ground-breaking technologies for designing and implementing cognitive robots based on AIP and autonomous intelligence generation methodologies beyond classic reflexive neural networks and imperative programming platforms. The latest advances have paved a new way for cognitive computing and autonomous software generation, which put the house before the cart for the software and AI industries [38], [39], [40], [41], [42], [43], [44], [45]. The keynote will demonstrate disruptive technologies encompassing autonomous systems, cognitive robots, real-time autonomous learning and trustworthy systems for symbiotic human-machine applications.
Keywords— Intelligence science, software science, AI programming, cognitive robots, intelligent mathematics, autonomous systems, cognitive robots, software engineering, applications.
Breakthroughs of basic research in Intelligence Science (IS) [1], [2], [3], [4], [5], [6], [7] and Cognitive Computing (CC) [8], [9], [10], [11], [12], [13], [14] have triggered the emergence of Cognitive Robots (CR) [15], [16], [17] and AI Programming (AIP) technologies [18], [19], [20], [21] towards autonomous software engineering. The latest advances enable the synergy of classical pre-programmed AI and pre-trained AI to an unprecedented platform for machine intelligence generation mimicking human brains and brain-inspired cognitive systems [2], [7], [8]. [31], [35]. It is discovered in IS and CC in general, and in CR and SE in particular, that the target entities had already out of the denotational power of the classic domains of real (R) and binary (B) numbers [21], [25], [29]. This leads to the latest discoveries on that the basic unit of human knowledge as a hyperstructure is a binary relation (bir). Therefore, a new framework of Intelligence Mathematics (IM) [22], [23], [24], [25], [26], [27], [28], [29], [30] has been created for rigorously manipulating the cognitive entities in the brain and cognitive robots spanning from formal concepts, semantics, knowledge, causalities, inferences, and consciousness by contemporary mathematical means for advancing both AI [31], [32], [33] and SE [34], [35], [36], [37].
This keynote lecture presents fundamental theories and ground-breaking technologies for designing and implementing cognitive robots based on AIP and autonomous intelligence generation methodologies beyond classic reflexive neural networks and imperative programming platforms. The latest advances have paved a new way for cognitive computing and autonomous software generation, which put the house before the cart for the software and AI industries [38], [39], [40], [41], [42], [43], [44], [45]. The keynote will demonstrate disruptive technologies encompassing autonomous systems, cognitive robots, real-time autonomous learning and trustworthy systems for symbiotic human-machine applications.
Keywords— Intelligence science, software science, AI programming, cognitive robots, intelligent mathematics, autonomous systems, cognitive robots, software engineering, applications.
Biography
Dr. Yingxu Wang is professor of cognitive systems, brain science, software science, and intelligent mathematics. He is the founding President of International Institute of Cognitive Informatics and Cognitive Computing (I2CICC). He is FIEEE, FBCS, FI2CICC, FAAIA, and FWIF. He has held visiting professor positions at Univ. of Oxford (1995, 2018-2023), Stanford Univ. (2008, 2016), UC Berkeley (2008), MIT (2012), and a distinguished visiting professor at Tsinghua Univ. (2019-2022). He received a PhD in Computer Science from the Nottingham Trent University, UK, in 1998 and has been a full professor since 1994. He is the founder and steering committee chair of IEEE Int’l Conference Series on Cognitive Informatics and Cognitive Computing (ICCI*CC) since 2002. He is founding Editor-in-Chiefs and Associate Editors of 10+ Int’l Journals and IEEE Transactions. He is Chair of IEEE SMCS TC-BCS on Brain-inspired Cognitive Systems, and Co-Chair of IEEE CS TC-CLS on Computational Life Science. His basic research has spanned across contemporary scientific disciplines of intelligence, mathematics, knowledge, robotics, computer, information, brain, cognition, software, data, systems, cybernetics, neurology, and linguistics. He has published 600+ peer reviewed papers and 38 books/proceedings. He has presented 68 invited keynote speeches in international conferences. He has served as honorary, general, and program chairs for 41 international conferences. He has led 10+ international, European, and Canadian research projects as PI. He is recognized by Google Scholar as world top 1 in Software Science, top 1 in Cognitive Robots, top 8 in Autonomous Systems, top 2 in Cognitive Computing, and top 1 in Knowledge Science with an h-index 69. He is recognized by ResearchGate as among the world’s top 1.0% scholars in general and in several contemporary fields encompassing artificial intelligence, autonomous systems, theoretical computer science, engineering mathematics, software engineering, cognitive science, information science, and computational linguistics, etc.
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Biography
Zhi Jin is professor of computer science at Peking University. She is currently the deputy director of Key Lab of High Confidence Software Technologies (PKU), Ministry of Education. Her main research interest is AI for SE, with a long-term focus on domain knowledge-led requirements engineering. She has published over 200 scientific articles in refereed international journals, such as IEEE T-KDE, T-SE, ACM T-OSEM, and T-CPS, and high rank conferences, such as ICSE, FSE, ASE and RE. She has co-authored five books and has held more than 30 approved invention patents. She is four times recipient of ACM SIGSOFT Distinguished Paper Awards.
Prof. Jin serves as an Associate Editor of IEEE Transactions on Software Engineering, IEEE Transactions on Reliability, and ACM Transactions on Autonomous and Adaptive Systems, and serves on the Editorial Board of Requirements Engineering Journal and Empirical Software Engineering. She was the director of CCF (China Computer Federation) Technical Committee of Software Engineering (2016-2019), currently the director of CCF Technical Committee of System Software (2020-2023)and the IEEE Fellow selected in 2023.
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Biography
Tao Xie is a Peking University Chair Professor, Chair of the Department of Software Science and Engineering in the School of Computer Science at Peking University, a Deputy Director of the Key Lab of High Confidence Software Technologies (PKU), Ministry of Education. He was a Full Professor at the Department of Computer Science, the University of Illinois at Urbana-Champaign (UIUC), USA. He is a Foreign Member of Academia Europaea, and a Fellow of ACM, IEEE, AAAS, and China Computer Federation (CCF). He won an Xplorer Prize, NSFC Overseas Distinguished Young Scholar Award and its Extension Category, NSF Faculty CAREER Award, ACM SIGSOFT Influential Educator Award, ACM SIGSOFT Distinguished Service Award, IEEE TCSE Distinguished Service Award, MSR Foundational Contribution Award, ASE 2021 Most Influential Paper Award, etc. He serves as Deputy Director of CCF TCSE and Co-Editor-in-Chief of Wiley Journal of Software Testing, Verification and Reliability (STVR). He served as Program Chair of China National Computer Congress (CNCC 2020), Program Co-Chair of ICSE 2021, and Program/General Chair of Tapia 2017/2018. His main research interests include software engineering, system software, software security, trustworthy AI.
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Biography
Philippe Fournier-Viger (Ph.D) is a Canadian researcher, distinguished professor at Shenzhen University (China). Five years after completing his Ph.D., he came to China in 2015 and became full professor after receiving a talent title from the National Science Foundation of China. He has published more than 375 research papers related to data mining algorithms for complex data (sequences, graphs), intelligent systems and applications, which have received more than 11,000 citations. He is the founder of the popular SPMF data mining library, offering more than 250 algorithms to find patterns in data, cited in more than 1,000 research papers. He is former associate editor-in-chief of the Applied Intelligence journal and has been keynote speaker for over 15 international conferences and co-edited four books for Springer. He is a co-founder of the UDML, PMDB and MLiSE (Machine Learning in Software Engineering) series of workshops held at the ICDM, PKDD, DASFAA and KDD conferences.