2021 IEEE CIS Summer School on Data-Driven Artificial/Computational Intelligence: Theory and Applications
23 - 26 August 2021, Virtual Event
Data has been playing an ever-growing role in artificial/computational intelligence. Such role goes beyond its typical use in neural networks and learning systems, encompassing also evolutionary and other meta-heuristic optimization algorithms. The objective of this summer school is to provide a unique and vibrant platform for learning and experiencing the emerging methodologies and applications of artificial/computational intelligence highly related to data. It will offer keynotes, invited lectures, tutorials and discussion groups from high-profile UK and international experts. The summer school will target senior undergraduate, graduate students, post-doc, early career researchers and professionals from around the world who are willingly to deepen their skills in computational intelligence, in the field of artificial/computational intelligence. It will provide a unique opportunity for participants to 1) learn about artificial/computational intelligence approaches and their applications; 2) interact with world-renowned experts in computational intelligence; and 3) communicate with experts and peers with a broad range of backgrounds to exchange ideas and form new collaborations.
Venue and Dates
Given the COVID-19 global pandemic, this summer school will be running in an online format. It will take place as part of the outreach activities of the Institute for Data Science and Artificial Intelligence (AI) at the University of Exeter and the Institute for Interdisciplinary Data Science and AI at the University of Birmingham. Both institutes are actively developing and fostering a culture of effective interactions for promoting data science and AI for addressing global challenges across disciplines.
All time slots are in British Summer Time (BST).
9:00-10:00 BST, Prof. Shiping Wen, Memristive Neuromorphic Computing: New Algorithmic Approaches to the Next Generation of AI.
10:15-10:45 BST, Dr. Hao Wang, Bayesian Optimization, Surrogate Modeling, and Their Applications to Real-World Problems.
13:00-14:00 BST, Prof. Liang Feng, Evolutionary Multi-Task Optimisation
14:00-15:00 BST, Prof. Tim Menzies, Keynote: Software Engineering for AI (Mash Ups of Data Miners and Optimizers: A "DUO" Approach)
9:00-10:00 BST, Prof. Yaochu Jin, Keynote: Evolutionary Multi-objective Federated Neural Architecture Search
10:15-11:00 BST, Dr. Per Kristian Lehre, Bridging Learning and Evolution with Estimation of Distribution Algorithms
13:00-14:00 BST, Prof. Yanan Sun, A Brief Review to Evolutionary Neural Architecture Algorithms
14:00-15:00 BST, Prof. Gabriela Ochoa, Complex Networks in Search and Optimisation
9:00-10:00 BST, Prof. Xin Yao, Keynote: When Everything Else Fails, Try Co-evolution
13:00-14:00 BST, Dr. Yuan Yuan, Toward Better Evolutionary Program Repair: An Integrated Approach
14:30-16:00 BST, Prof. Jiayu Zhou, Tutorial: Multi-Task Learning: Techniques and Applications
9:00-10:00 BST, Prof. Bernhard Sendhoff, Keynote: Data-Driven AI in Engineering Design: From Tool to Partner
10:15-11:00 BST, Dr. Manuel Roveri, TinyML: Theory and Technology
13:00-14:00 BST, Prof. Ata Kaban, Tutorial: Random Projection Meets Learning Theory and Beyond
14:45-15:40 BST , Prof. Richard Everson , Topic TBC
Registration fee is 15 USD (97.5 RMB or 10.8 GBP) and includes access to all online sessions and their recordings. Please send the following information to Dr. Fan Li and Dr Jiangjiao Xu for registration.
Contact information (Email address | WeChat | Contact number)
Payment type are either Alipay (支付宝), WeChat (微信支付) or PayPal as follows.
Ke Li, University of Exeter, UK
Leandro L. Minku, University of Birmingham, UK