Organizers

Bogdan Filipic, General Chair

Jozef Stefan Institute, Slovenia | webpage

Bogdan Filipic is a senior researcher and head of Computational Intelligence Group at the Department of Intelligent Systems of the Jozef Stefan Institute, Ljubljana, Slovenia, and professor of Computer Science at the Jozef Stefan International Postgraduate School. He received his Ph.D. degree in Computer Science from the University of Ljubljana. His research interests are in computational intelligence, evolutionary computation and randomized optimization. He focuses on evolutionary multiobjective optimization, including problem characterization, constraint handling and result visualization. He is also active in promoting evolutionary computation in practice and has led optimization projects for the automotive industry, steel production and energy management. He served as the general chair of PPSN 2014 and the program chair of BIOMA 2020, and organized several special sessions and tracks at major international conferences. He was a guest lecturer at the University of Oulu, Finland, and the VU University Amsterdam, The Netherlands, and has given tutorials at recent CEC and GECCO conferences.

Gabriela Ochoa, Editor-in-Chief

University of Stirling, UK | webpage

Gabriela Ochoa is a Professor of Computing Science at the University of Stirling in Scotland, UK. Her research lies in the foundations and applications of evolutionary algorithms and metaheuristics, with emphasis on adaptive search, gray-box optimisation, fitness landscape analysis and visualisation. She holds a PhD from the University of Sussex, UK, and has worked at the University Simon Bolivar, Venezuela, and the University of Nottingham, UK. Her Google Scholar h-index is 45, and her work has obtained 8 best-paper awards and 11 other nominations. She collaborates cross-disciplines to apply evolutionary computation in healthcare and conservation. She has been active in organisation and editorial roles for: Genetic and Evolutionary Computation Conference (GECCO), Parallel Problem Solving from Nature (PPSN), EvoStar, Evolutionary Computation Journal (ECJ) and ACM Transactions on Evolutionary Learning and Optimisation (TELO). She is a member of the executive board for the ACM interest group in evolutionary computation, SIGEVO, and the editor of the SIGEVOlution newsletter. In 2020, she was recognised by the leading European event on bio-inspired algorithms, EvoStar, for her outstanding contributions to the field.

Carlos Cotta, Local Chair

Universidad de Málaga, Spain | webpage

Carlos Cotta received his Ph.D. in Computer Science from the University of Málaga, Spain, in 1998. He is currently a Professor at the Computer Science Department from the University of Málaga. His research interests are focused on the confluence of complex systems and evolutionary and memetic computing, with applications on combinatorial optimization in general and bioinformatics and videogames in particular. He has co-edited books on memetic algorithms and combinatorial optimization, and has published more than 250 papers on these topics. He has been involved in the scientific organization of different events centered on bio-inspired algorithms, evolutionary combinatorial optimization, and complex systems.

Gabriel Luque, Local Chair

University of Málaga, Spain

Gabriel Luque received his Ph.D. in Computer Science from the University of Málaga in 2006. He is currently an associate professor at the University of Málaga in Spain. He has co-authored more than 150 international publications, including 25 journal papers. His major research interests include the design of new metaheuristics, specifically parallel algorithms, and their application to complex problems in the fields of smart cities, networking, and combinatorial optimization in general. He is also actively working on Quantum Computing techniques and the application of parallel methods to solve dynamic optimization problems. He has co-chaired several special sessions and workshops on metaheuristics, parallel techniques, and tools for the development of optimization methods.

Tea Tušar, Proceedings

Jožef Stefan Institute, Slovenia | webpage

Tea Tušar is a senior research assistant at the Department of Intelligent Systems of the Jozef Stefan Institute in Ljubljana, Slovenia. She was awarded the PhD degree in Information and Communication Technologies by the Jozef Stefan International Postgraduate School for her work on visualizing solution sets in multiobjective optimization. She has completed a one-year postdoctoral fellowship at Inria Lille in France where she worked on benchmarking multiobjective optimizers. Her research interests include evolutionary algorithms for singleobjective and multiobjective optimization with emphasis on visualizing and benchmarking their results and applying them to real-world problems.

Richard Allmendinger, Publicity

The University of Manchester, UK | webpage

Richard is Professor of Applied Artificial Intelligence, and Associate Dean for Business Engagement, Civic & Cultural Partnerships in the Faculty of Humanities, The University of Manchester, UK. He is also an Editorial Board Member of several international journals, an Alan Turing Fellow Alumni, has served in numerous chair roles for different AI conferences, and is a Senior Scientist at Eharo, and AI Advisor for River Capital (private equity), Ark Biotech (bioprocessing), and GuruAI (music education). Currently, Richard is also creating a UoM software spinout focussed on identifying and repairing security vulnerabilities in source code. Prior to Manchester, he was Honorary Lecturer and Research Associate at the Biochemical Engineering Department, University College London. He studied Business Engineering at the Karlsruhe Institute of Technology and the Royal Melbourne Institute of Technology and completed a PhD in Computer Science (Machine Learning & Optimization) at The University of Manchester. Richard's research interests are in the development and application of sequential decision-making methods to problems with multiple objectives, uncertainties and resourcing issues arising in areas such as healthcare, manufacturing, engineering, music, sports, and finance. Richard has attracted a total of £45M+ in grant funding as PI/co- I from UKRI, industry, and other sources, and led the development of several commercially available AI tools.

Grant Dick, Student Affairs

University of Otago

Giorgia Nadizar, Student Affairs

Università degli Studi di Trieste, Italy | webpage

Giorgia Nadizar is a third year PhD student at the University of Trieste, Italy. Her research interests lie at the intersection of embodied AI and explainable/interpretable AI.

Alexander Brownlee, Student Workshop Chair

University of Stirling

Alexander (Sandy) Brownlee is a Senior Lecturer in the Division of Computing Science and Mathematics at the University of Stirling, where he leads the Data Science & Intelligent Systems research group. His main topics of interest are in search-based optimisation methods and machine learning, with a focus on decision support tools, and applications in civil engineering, transportation and software engineering. He has published over 80 peer- reviewed papers on these topics, supported by funding from UKRI, Data Lab, and industry. He has worked with several leading organisations including BT, KLM, and NHS Scotland on real-world applications of optimisation and machine learning. He serves as a reviewer for several journals and conferences in evolutionary computation, civil engineering and transportation, and is currently an Editorial Board member for Journal of Scheduling and Complex And Intelligent Systems. He has also organised several workshops and tutorials at GECCO, CEC and PPSN.

Marcella Scoczynski Ribeiro Martins, Electronic Media

Federal University of Technology - Paraná, Brazil | webpage

Marcella Scoczynski is an Assistant Professor at Federal University of Technology - Parana UTFPR, Brazil. She has done her PhD on Computer Engineering at Federal University of Technology - Parana UTFPR, Brazil. Her thesis has awarded at the Theses Competition during Brazilian Conference on Intelligent Systems (BRACIS 2018) and at the Theses Contest during 5th IEEE Latin American Conference on Computational Intelligence (LA-CCI 2018). Her main research interests are numerical and combinatorial optimization, evolutionary computation and metaheuristics (with a particular interest in estimation of distribution algorithms), and landscape analysis. She co-authored scientific papers in international journals and conferences.

Hirad Assimi, Electronic Media

University of Adelaide, Australia | webpage

Hirad completed his B.Sc and M.Sc degrees in Mechanical Engineering from the University of Guilan and pursued his PhD in Computer Science at the University of Adelaide. He has a keen interest in applying Evolutionary Computation to real-world complex optimisation problems, particularly within the mining and energy sectors. Currently, Hirad is a postdoctoral researcher working on the Mine Operational Vehicle Electrification project.

Nadarajen Veerapen, SIGEVO Eletronic Media Affairs

Université de Lille, France

Nadarajen Veerapen is an Associate Professor (maître de conférences) at the University of Lille, France. Previously he was a research fellow at the University of Stirling in Scotland. He holds a PhD in Computing Science from the University of Angers, France, where he worked on adaptive operator selection. His research interests include local search, hybrid methods, search-based software engineering and visualisation. He is in charge of Electronic Media Affairs for SIGEVO. He has served as Electronic Media Chair for GECCO 2020 and 2021, Publicity Chair for GECCO 2019 and as Student Affairs Chair for GECCO 2017 and 2018. He has previously co-organised the workshop on Landscape-Aware Heuristic Search at PPSN 2016, GECCO 2017-2024.

Mario Andrés Muñoz, Hybridization (Visualization)

School of Computer and Information Systems, The University of Melbourne, Australia. | webpage

Mario Andrés Muñoz is a Senior Research Fellow at the School of Computer and Information Systems, The University of Melbourne, and the ARC Training Centre in Optimisation Technologies, Integrated Methodologies and Applications (OPTIMA). He received the B.Eng. and M.Eng. degrees in Electronics Engineering from Universidad del Valle, Colombia, in 2005 and 2008, respectively, and the Ph.D. degree in Engineering from The University of Melbourne, Australia, in 2014. His research interests focus on applying optimisation, computational intelligence, signal processing, data analysis, and machine learning methods to ill-defined science, engineering and medicine problems.

Ahmed Kheiri, Hybrid Scheduling

University of Manchester, UK | webpage

Dr Ahmed Kheiri is a Senior Lecturer (equivalent to Associate Professor) in Management Science at Alliance Manchester Business School, The University of Manchester. He was previously at Lancaster University Management School for seven years. He received his B.Sc. (Hons - First Class) from the University of Khartoum, Sudan, and received his M.Sc. (Distinction) and PhD. from the University of Nottingham, UK. He held research positions at the University of Exeter, and the Cardiff School of Mathematics. He has designed and implemented intelligent, ready-to-use hyper-heuristic methods for decision support and applied them to a wide range of real-world problems. He has been successful in winning research funding from a variety of sources including EPSRC and KTP. He has published more than 40 refereed papers in reputable journals and highly respected international conferences. He has published two invited review papers on selection hyper-heuristics and Meteheuristics in EJOR. During his career, he received several academic awards some are awarded from participation in international optimisation challenges. In 2020, he received the Lancaster University Management School Dean's Award for his excellent achievements across the board in research, teaching and engagement.

Jamal Toutouh, Sponsorships

MIT, USA | webpage

I am a Marie Skłodowska Currie Postdoctoral Fellow at Massachusetts Institute of Technology (MIT) in the USA, at the MIT CSAIL Lab. I obtained my Ph.D. in Computer Engineering at the University of Malaga (Spain). The dissertation, Natural Computing for Vehicular Networks, was awarded the 2018 Best Spanish Ph.D. Thesis in Smart Cities. My dissertation focused on the application of Machine Learning methods inspired by Nature to address Smart Mobility problems.%%%My current research explores the combination of Nature-inspired gradient-free and gradient-based methods to address Adversarial Machine Learning. The main idea is to devise new algorithms to improve the efficiency and efficacy of the state-of-the-art methodology by mainly applying co-evolutionary approaches. Besides, I am working on the application of Machine Learning to address problems related to Smart Mobility, Smart Cities, and Climate Change.

Carla Silva, Sustainability

University of Lisbon, Portugal | webpage

Mechanical Engineer in 2001, PhD in Mechanical Engineer in 2005 Professor at University of Lisbon, coordinator of the Master in Eng. Energy and Environment of the Faculty of Sciences Lectures Environmental impact and Life cycle analysis; Sustainable mobility; Biorefinery analysis; Research methods and dissertation project; Energy conversion by combustion Research in mass and energy balances applied to complex systems such as transportation and biorefinery systems Supervised more than 50 master students and more than 10 PhD students h=36, 4136 citations according to Google Scholar.

Francisco Chicano, Posters

University of Malaga, Spain | webpage

Francisco Chicano holds a PhD in Computer Science from the University of Málaga and a Degree in Physics from the National Distance Education University. Since 2008 he is with the Department of Languages and Computing Sciences of the University of Málaga. His research interests include quantum computing, the application of search techniques to Software Engineering problems and the use of theoretical results to efficiently solve combinatorial optimization problems. He is in the editorial board of Evolutionary Computation Journal, Engineering Applications of Artificial Intelligence, Journal of Systems and Software, ACM Transactions on Evolutionary Learning and Optimization and Mathematical Problems in Engineering. He has also been programme chair and Editor-in-Chief in international events.

Ignacio Hidalgo, Workshops

Universidad Complutense de Madrid, Spain

Iñaki Hidalgo is Full Professor of Computing Science at Complutense University of Madrid (UCM). He received a PhD in Physics from the same university in 2001 under the Informatics and Automation doctoral program, with a dissertation on application of evolutionary algorithms for%%%computer architecture problems. He has published more than 150 papers in journals and international conferences, most of them related to RWA of EC. He was local chair of Gecco 2015 in Madrid and is currently co-chair of EvoApps 2022. Recently his group has been working on biomedical problems, some of them dealing with uncertainty not only of the data, but also of the model. He has successfully supervised 10 PhD theses and is currently supervising 4 PhD students.

Carola Doerr, Workshops

CNRS and Sorbonne University, France | webpage

Carola Doerr, formerly Winzen, is a CNRS research director at Sorbonne Université in Paris, France. Carola's main research activities are in the analysis of black-box optimization algorithms, both by mathematical and by empirical means. Carola is associate editor of IEEE Transactions on Evolutionary Computation, ACM Transactions on Evolutionary Learning and Optimization (TELO), and the Evolutionary Computation journal. She is/was program chair for the BBSR track at GECCO 2025 and 2024, the GECH track at GECCO 2023, for PPSN 2020, FOGA 2019, and for the theory tracks of GECCO 2015 and 2017. She has organized Dagstuhl seminars and Lorentz Center workshops. Together with Pascal Kerschke, Carola leads the 'Algorithm selection and configuration' working group of COST action CA22137. Carola's works have been distinguished by several awards, among them the CNRS bronze medal, the Otto Hahn Medal of the Max Planck Society, and best paper awards at GECCO, CEC, and EvoApplications.

Mengjie Zhang, Tutorials

Victoria University of Wellington, New Zealand | webpage

Prof Mengjie Zhang is a Fellow of Royal Society of New Zealand, a Fellow of Engineering New Zealand, a Fellow of IEEE, an IEEE Distinguished Lecturer, currently Professor of Computer Science at Victoria University of Wellington, where he heads the interdisciplinary Evolutionary Computation and Machine Learning Research Group. He is the Director of the Centre for Data Science and Artificial Intelligence at the University.%%%%%%His research is mainly focused on AI, machine learning and big data, particularly in evolutionary learning and optimisation, feature selection/construction and big dimensionality reduction, computer vision and image analysis, scheduling and combinatorial optimisation, classification with unbalanced data and missing data, and evolutionary deep learning and transfer learning. Prof Zhang has published over 900 research papers in refereed international journals and conferences. He has been serving as an associated editor for over ten international journals including IEEE Transactions on Evolutionary Computation, IEEE Transactions on Cybernetics, the Evolutionary Computation Journal (MIT Press), and involving many major AI and EC conferences as a chair. He received the “EvoStar/SPECIES Award for Outstanding Contribution to Evolutionary Computation in Europe” in 2023. Since 2007, he has been listed as a top five (currently No. 3) world genetic programming researchers by the GP bibliography (http://www.cs.bham.ac.uk/~wbl/biblio/gp-html/index.html). He is also a Clarivate Highly Cited Researcher in the field of Computer Science -- 2023. %%%%%%He is the Tutorial Chair for GECCO 2014, 2023 and 2024, an AIS-BIO Track Chair for GECCO 2016, an EML Track Chair for GECCO 2017, and a GP Track Chair for GECCO 2020 and 2021. %%%%%%Prof Zhang is currently the Chair for IEEE CIS Awards Committee. He is also a past Chair of the IEEE CIS Intelligent Systems Applications Technical Committee, the Emergent Technologies Technical Committee and the Evolutionary Computation Technical Committee, a past Chair for IEEE CIS PubsCom Strategic Planning subcommittee, and the founding chair of the IEEE Computational Intelligence Chapter in New Zealand.

Emma Hart, Tutorials

Edinburgh Napier University

Prof. Hart gained a 1st Class Honours Degree in Chemistry from the University of Oxford, followed by an MSc in Artificial Intelligence from the University of Edinburgh. Her PhD, also from the University of Edinburgh, explored the use of immunology as an inspiration for computing, examining a range of techniques applied to optimisation and data classification problems. She moved to Edinburgh Napier University in 2000 as a lecturer, and was promoted to a Chair in 2008 where she leads a group in Nature-Inspired Intelligent Systems, specialising in optimisation and learning algorithms applied in domains that range from combinatorial optimisation to robotics. Her work mainly involves development of algorithms inspired by biological evolution to discover novel solutions to challenging problems. She was appointed as Editor-in-Chief of Evolutionary Computation (MIT Press) in 2017. She has been invited to give keynotes at major international conferences including CLAIO 2020, IEEE CEC 2019, EURO 2016 and UKCI 2015 and was General Chair of PPSN 2016, and as a Track Chair at GECCO for several years. She is an elected member of the Executive Board of the ACM SIG on Evolutionary Computation. More broadly, she invited member of the UK Operations Research Society Research Panel, and in Scotland, co-leads the Artificial Intelligence theme within SICSA. She was appointed as a panel member for REF2021 (UoA11 Computer Science). In 2020 she was appointed to the Steering Committee that developed Scotland's AI Strategy published in 2021 . She has a sustained track record of obtaining funding from the EU, EPSRC and of engaging with industry via KTP projects and consultancy, and participates enthusiastically in public-engagement activity, e.g Pint of Science. Her work in evolutionary robotics has attracted significant media attention, e.g. in New Scientist, the Guardian, Telegraph and the Conversation. In 2021, she gave a TED Talk on Evolutionary Robotics, available online

Hemant Kumar Singh, Competitions

University of New South Wales | webpage

Hemant Kumar Singh is an Associate Professor at the School of Engineering and Technology at the University of New South Wales (UNSW), Australia. He completed his PhD from UNSW in 2011 and B.Tech in Mechanical Engineering from Indian Institute of Technology (IIT) Kanpur in 2007. He worked with General Electric Aviation at John F. Welch Technology Centre as a Lead Engineer during 2011-13. His research interests include development of evolutionary computation methods to deal with various challenges such as multiple objectives, constraints, uncertainties, hierarchical (bi-level) objectives, and decision-making. He has co-authored over 125 refereed publications on these topics collectively. He is an Associate Editor for IEEE Transactions on Evolutionary Computation and has been in the organizing team of several conferences, e.g., IEEE CEC (Program co-chair 2021), SSCI (MCDM co-chair 2020-23), ACM GECCO (RWACMO workshop co-chair 2018-21). More details of his research and professional activities can be found at his website.

Yuri Lavinas, Competitions

University of Toulouse 1 Capitole, University of Toulouse | webpage

I’m an associate professor at the University of Toulouse 1 Capitole, France, at the Institut de Recherche en Informatique de Toulouse (IRIT) and I’m part of the REVA team. I did a postdoc research working with histopathology image analysis for cancer treatment with Genetic Programming in the IRIT@CRCT group. I got my PhD degree from the University of Tsukuba, Japan. Originally, I’m from Brazil, where I did my undergraduate course, at the University of Brasilia.%%%%%%My research interests are related to Computational Intelligence, such as Evolutionary Computation and Artificial Life, with a greater focus on multi-objective optimization, fitness landscape and Genetic Programming. Overall, I’m interested in programs that can adapt themselves, in applications of Evolutionary Computation (black box optimization, multi-agent systems, games), as well as more speculative use of these Computational Intelligence for Artificial Life ( such as the evolution of virtual creatures and the worlds where the live).%%%

Heike Trautmann, Late Breaking Abstract

Paderborn University, Germany | webpage

Heike Trautmann is Professor of Machine Learning and Optimisation, both at the Department of Computer Science, Paderborn University, Germany and the University of Twente, Netherlands. Moreover, she is key supporter of the Confederation of Laboratories for Artificial Intelligence Research in Europe (CAIRNE). Her research mainly focuses on Trustworthy AI, Data Science, Automated Algorithm Selection and Configuration, Exploratory Landscape Analysis, (Multiobjective) Evolutionary Optimisation and Data Stream Mining. She is associate editor of the IEEE Transactions on Evolutionary Computation and the Evolutionary Computation Journal (ECJ).

Eric Medvet, Hot-off-the-Press

University of Trieste | webpage

Eric Medvet is an Associate Professor in Computer Engineering at the Department of Engineering and Architecture of University of Trieste, Italy. He is the founder and head of the Evolutionary Robotics and Artificial Life lab (ERALLab); he was the co-founder of the Machine Learning Lab. His research activities include evolutionary computation, artificial life, and the application of machine learning techniques to engineering and computer security problems. He authored more than 160 peer-reviewed articles on international journals or conferences, with more than 60 coauthors. He was a recipient of the Google Faculty Research Award 2020.

Erik Goodman, Humies (Chair)

Michigan State University and BEACON Center for the Study of Evolution in Action, USA | webpage

Erik D. Goodman is PI and Executive Director of the BEACON Center for the Study of Evolution in Action, an NSF Science and Technology Center headquartered at Michigan State University, funded by NSF for 2010-20, and now continuing with funding from MSU. BEACON has a dynamic research program and extensive education and outreach programs, and includes evolutionary biologists as well as computer scientists/engineers studying evolutionary computation (for search and optimization) and evolution of digital organisms. Goodman is a professor in Electrical and Computer Engineering, Mechanical Engineering, and Computer Science and Engineering. He was co-founder and VP Technology, Red Cedar Technology, Inc., (now a division of Siemens), which developed design optimization software that has become a best-selling system in industry. He was named Michigan Distinguished Professor of the Year, 2009, and received the MSU Distinguished Faculty Award in 2011. He was elected Chair of the Executive Board (2003-2005) and Senior Fellow, International Society for Genetic and Evolutionary Computation; then was Founding Chair of the ACM SIG on Genetic and Evolutionary Computation (SIGEVO), 2005. His current personal research is on evolutionary algorithms for optimization of heterogeneous propellant grains for solid-fuel rockets and on evolutionary approaches to neural architecture search.

William B. Langdon, Humies (Publicity Chair)

University College London, UK | webpage

William B. Langdon has been working on GP since 1993. His PhD was the first book to be published in John Koza and Dave Goldberg's book series. He has previously run the GP track for GECCO 2001 and was programme chair for GECCO 2002 having previously chaired EuroGP for 3 years. More recently he has edited SIGEVO's FOGA and run the computational intelligence on GPUs (CIGPU) and EvoPAR workshops. His books include A Field Guide to Genetic Programming, Foundations of Genetic Programming and Advances in Genetic Programming 3. He also maintains the genetic programming bibliography. His current research uses GP to genetically improve existing software, CUDA, search based software engineering and Bioinformatics.

John Koza, Humies (Sponsor)

- | webpage

Miguel Nicolau, Summer School

University College Dublin, Ireland | webpage

Miguel is a Lecturer in Business Analytics, in the School of Business of University College Dublin, Ireland. His research interests revolve around Artificial Intelligence, Machine Learning, Evolutionary Computation, Business Analytics, Genetic Programming, and Real-World Applications. He is a senior member of the UCD's NCRA (Natural Computing Research & Applications) group.

Vanessa Volz, Summer School

CWI (Netherlands) | webpage

Vanessa Volz is currently a tenure track researcher in the Evolutionary Intelligence (EI) group at Centrum Wiskunde & Informatica (CWI), Amsterdam, The Netherlands. She received her PhD in 2019 from TU Dortmund University, Germany, for her work on surrogate-assisted evolutionary algorithms applied to game optimisation. Her current research focus is on transfer learning in the context of evolutionary computation, especially in the context of recurring or otherwise dynamic problems.

Elena Raponi, Women+@GECCO

Leiden University | webpage

Elena Raponi is an Assistant professor in Bayesian optimization at the Leiden Institute of Advanced Computer Science (LIACS), in the Natural Computing research cluster. Previously, she held postdoctoral positions at LIACS, the Technical University of Munich (TUM), and Sorbonne Université. She received her PhD in Applied Mathematics from the University of Camerino, Italy, in May 2021. Her research focuses on surrogate-based and high-dimensional Bayesian optimization in continuous domains. She also works on the development of analytical and numerical modeling techniques for the optimization of geometries and materials in structural mechanics. Her hybrid research profile enables algorithm design inspired by concrete challenges emerging from real-world applications.

Maria J. Blesa, Women+@GECCO

Universitat Politècnica de Catalunya | webpage

Maria J. Blesa obtained a PhD in Computer Science from the Universitat Politècnica de Catalunya (Technical University of Catalonia, UPC) in 2006. She is an associate professor in the School of Informatics (FIB) and the School of Mathematics (FME) at the same University. Her current research interests include the theoretical and experimental study of problems that arise in information dissemination processes in social networks and the design of algorithms for combinatorial optimization problems.

Thomas Bartz-Beielstein, Evolutionary Computation in Practice

TH Koeln, Germany | webpage

* Academic Background: Ph.D. (Dr. rer. nat.), TU Dortmund University, 2005, Computer Science. * Professional Experience: Shareholder, Bartz & Bartz GmbH, Germany, 2014 – Present; Speaker, Research Center Computational Intelligence plus, Germany, 2012 – Present; Professor, Applied Mathematics, TH Köln, Germany, 2006 – Present. * Professional Interest: Computational Intelligence; Simulation; Optimization; Statistical Analysis; Applied Mathematics. * ACM Activities: Organizer of the GECCO Industrial Challenge, SIGEVO, 2011 – Present; Event Chair, Evolutionary Computation in Practice Track, SIGEVO, 2008 – Present; Tutorials Evolutionary Computation in Practice, SIGEVO, 2005 – 2013; GECCO Program Committee Member, Session Chair, SIGEVO, 2004 – Present. * Membership and Offices in Related Organizations: Program Chair, International Conference Parallel Problem Solving from Nature, Jozef Stefan Institute, Slovenia, 2014; Program Chair, International Workshop on Hybrid Metaheuristics, TU Dortmund University, 2006; Member, Special Interest Group Computational Intelligence, VDI/VDE-Gesellschaft für Mess- und Automatisierungstechnik, 2008 – Present. * Awards Received: Innovation Partner, State of North Rhine-Westphalia, Germany, 2013; One of the top 20 researchers in applied science by the Ministry of Innovation, Science and Research of the State of North Rhine-Westphalia, 2017.

Boris Naujoks, Job Market

Cologne University of Applied Sciences, Germany | webpage

Boris Naujoks is a professor for Applied Mathematics at TH Köln - Cologne University of Applied Sciences (CUAS). He joint CUAs directly after he received his PhD from Dortmund Technical University in 2011. During his time in Dortmund, Boris worked as a research assistant in different projects and gained industrial experience working for different SMEs. Meanwhile, he enjoys the combination of teaching mathematics as well as computer science and exploring EC and CI techniques at the Campus Gummersbach of CUAS. He focuses on multiobjective (evolutionary) optimization, in particular hypervolume based algorithms, and the (industrial) applicability of the explored methods.

Anne Auger, Business Committee

Inria, France | webpage

Anne Auger is a research director at the French National Institute for Research in Computer Science and Control (Inria) heading the RandOpt team. She received her diploma (2001) and PhD (2004) in mathematics from the Paris VI University. Before to join INRIA, she worked for two years (2004-2006) at ETH in Zurich. Her main research interest is stochastic continuous optimization including theoretical aspects, algorithm designs and benchmarking. She is a member of ACM-SIGECO executive committee and of the editorial board of Evolutionary Computation. She has been General chair of GECCO in 2019. She has been organizing the biannual Dagstuhl seminar """"Theory of Evolutionary Algorithms"""" in 2008 and 2010 and all seven previous BBOB workshops at GECCO since 2009. She is co-organzing the forthcoming Dagstuhl seminar on benchmarking.

Manuel López-Ibáñez, Business Committee

University of Manchester, UK | webpage

Dr. López-Ibáñez is a senior lecturer in the Decision and Cognitive Sciences Research Centre at the Alliance Manchester Business School, University of Manchester, UK. Between 2020 and 2022, he was also a """"Beatriz Galindo"""" Senior Distinguished Researcher at the University of Málaga, Spain. He received the M.S. degree in computer science from the University of Granada, Granada, Spain, in 2004, and the Ph.D. degree from Edinburgh Napier University, U.K., in 2009. He has published 32 journal papers, 9 book chapters and 54 papers in peer-reviewed proceedings of international conferences on diverse areas such as evolutionary algorithms, multi-objective optimization, and various combinatorial optimization problems. His current research interests are experimental analysis and the automatic configuration and design of stochastic optimization algorithms, for single and multi-objective problems. He is the lead developer and current maintainer of the irace software package for automatic algorithm configuration (http://iridia.ulb.ac.be/irace) and the EAF package for the analysis of multi-objective optimizers (https://mlopez-ibanez.github.io/eaf/).