2021 IEEE CIS Summer School on Data-Driven Artificial/Computational Intelligence: Theory and Applications

Objectives

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.

Program

All time slots are in British Summer Time (BST).

Monday 23/08/21

• 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)

Tuesday 24/08/2021

• 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

Wednesday 25/08/2021

• 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

Thursday 26/08/2021

• 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

Organizers

General Chairs

• Ke Li, University of Exeter, UK

• Leandro L. Minku, University of Birmingham, UK

Organizing Committee Members

• Jiangjiao Xu, University of Exeter, UK, j.xu@exeter.ac.uk

• Fan Li, University of Exeter, UK, f.li@exeter.ac.uk

• Per Kristian Lehre, University of Birmingham, UK, p.k.lehre@cs.bham.ac.uk

• Rodrigo Soares, Federal Rural University of Pernambuco, Brazil, rodrigo.gfsoares@ufrpe.br