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Tutorials

Title Organizers
Advanced Use of Automatic Algorithm Configuration: Single- and Multi-Objective Approaches Jeroen Rook
University of Twente
Manuel López-Ibáñez
University of Manchester, UK
Advances in Evolutionary Hyper-Heuristics Nelishia Pillay
University of Pretoria
Automated Machine Learning Tools for Data Science, Modeling, and Algorithm Benchmarking Ryan Urbanowicz
Cedars Sinai Medical Center, Los Angeles, California, USA
Bayesian Optimisation Jürgen Branke
University of Warwick, UK
Sebastian Rojas Gonzalez
University of Ghent, Belgium
Ivo Couckuyt
University of Ghent
Benchmarking single- and multi-objective optimization algorithms: how to make your experimental data more valuable Carola Doerr
CNRS and Sorbonne University, France
Diederick Vermetten
Leiden Institute for Advanced Computer Science
Jacob de Nobel
Leiden Institute of Advanced Computer Science
Thomas Bäck
LIACS, Leiden University, The Netherlands
Cartesian Genetic Programming - From foundations to recent developments and applications Kalkreuth Roman
RWTH Aachen University
Sylvain Cussat-Blanc
Université Toulouse Capitole, IRIT - CNRS UMR5505, Institut Universitaire de France
Dennis G. Wilson
ISAE-SUPAERO, University of Toulouse, France
Coevolutionary Computation for Adversarial Deep Learning Jamal Toutouh
University of Malaga, Spain
Una-May O’Reilly
MIT, USA
Combinatorial Optimisation Can be Different from Continuous Optimisation for MOEAs Li Miqing
School of Computer Science, University of Birmingham
Constraint-Handling Techniques used with Evolutionary Algorithms Carlos Coello Coello
CINVESTAV-IPN, Mexico
Decomposition Evolutionary Multi-Objective Optimization: What We Know from the Literature and What We are not Clear from a Data Science Perspective Ke Li
University of Exeter, UK
Qingfu Zhang
City University of Hong Kong
Evolution of Neural Networks Risto Miikkulainen
The University of Texas at Austin and Cognizant Technology Solutions, USA
Sebastian Risi
IT University of Copenhagen
David Ha
Sakana
Yujin Tang
Sakana
Evolutionary Art and Design in the Machine Learning Era Penousal Machado
University of Coimbra, CISUC, DEI
João Correia
University of Coimbra, Portugal
Evolutionary Computation and Evolutionary Deep Learning for Image Analysis, Signal Processing and Pattern Recognition Stefano Cagnoni
University of Parma
Ying Bi
Zhengzhou Universit
Yanan Sun
Sichuan University, China
Evolutionary Computation for Feature Selection and Feature Construction XUE Bing
Victoria University of Wellington
Mengjie Zhang
Victoria University of Wellington, New Zealand
Evolutionary computation for stochastic problems Frank Neumann
University of Adelaide, Australia
Aneta Neumann
The University of Adelaide, Australia
Hemant Kumar Singh
University of New South Wales
Evolutionary Computation meets Machine Learning for Combinatorial Optimisation Yi Mei
School of Engineering and Computer Science, Victoria University of Wellington, New Zealand
Günther Raidl
TU Wien, Austria
Evolutionary Reinforcement Learning Antoine Cully
Imperial College London, UK
Bryan Lim
Autodesk Research
Manon Flageat
Imperial College London
Paul Templier
Imperial College London
Fair Performance Comparison of Evolutionary Multi-Objective Algorithms Hisao Ishibuchi
Southern University of Science and Technology
Lie Meng Pang
Southern University of Science and Technology
Genetic Programming as a Hyper-Heuristic for Solving Combinatorial Optimisation Problems Marko Đurasević
University of Zagreb, Faculty of electrical engineering and computing
Francisco J. Gil Gala
Department of Computer Science, University of Oviedo
Domagoj Jakobovic
University of Zagreb, Faculty of electrical engineering and computing, Croatia
Yi Mei
School of Engineering and Computer Science, Victoria University of Wellington, New Zealand
Intelligent Evolution Optimization: Guided from Deep Learning to Large Language Model Hua Xu
Tsinghua University
Xiaodong Li
RMIT University, Australia
Yuan Sun
La Trobe Business School, La Trobe University
Huigen Ye
Department of Computer Science, Tsinghua University
Introduction to Quantum Optimization Alberto Moraglio
University of Exeter, UK
Francisco Chicano
University of Malaga, Spain
Introductory Mathematical Programming for EC Ofer Shir
Tel-Hai College and Migal Institute, Israel
Linear Genetic Programming Wolfgang Banzhaf
Michigan State University
Ting Hu
School of Computing, Queen's University, Canada
Machine Learning Assisted Evolutionary Multi- and Many-objective Optimization Kalyanmoy Deb
Michigan State University, USA
DHISH KUMAR SAXENA
PROFESSOR, IIT ROORKEE, INDIA
Sukrit Mittal
Franklin Templeton Investments
Model-Based Evolutionary Algorithms Dirk Thierens
Utrecht University, The Netherlands
Peter A. N. Bosman
Centre for Mathematics and Computer Science, The Netherlands
New, more efficient crossover and local search operators for recombination lattices. Darrell Whitley
Colorado State University, United States
Pareto Optimization for Subset Selection: Theories and Practical Algorithms Chao Qian
Nanjing University
Recent Advances in Meta-features Used for Representing Black-box Single-objective Continuous Optimization Gjorgjina Cenikj
Jožef Stefan Institute, Ljubljana, Slovenia
Ana Nikolikj
Jozef Stefan Institute, Ljubljana, Slovenija
Tome Eftimov
Jožef Stefan Institute, Slovenia
Recent developments in data structures and algorithms for evolutionary multiobjective optimization Andrzej Jaszkiewicz
Poznan University of Technology
Piotr Zielniewicz
Poznan University of Technology
Representations for Evolutionary Algorithms Franz Rothlauf
Universität Mainz
Statistical Forward Planning Algorithms Simon Lucas
Queen Mary University of London
Structural bias in optimisation algorithms Anna V Kononova
LIACS, Leiden University, The Netherlands
Niki van Stein
Leiden University
Theory and Practice of Population Diversity in Evolutionary Computation Dirk Sudholt
University of Passau, Germany
Giovanni Squillero
Politecnico di Torino, Italy
Tutorial: A Gentle Introduction to Theory (for Non-Theoreticians) Benjamin Doerr
École Polytechnique, France
What You Always Wanted to Know About Evolution Strategies, But Never Dared to Ask Hans-Georg Beyer
Vorarlberg University of Applied Sciences