General Chair
Editor-in-Chief
Local Chair
Local Chair
Publicity
Program
Social Media
Student Affairs
Student Affairs
Electronic Media
Electronic Media
Hybridization (Visualization)
Hybridization (Visualization)
Hybrid Scheduling
Sponsorships
Sponsorships
Sponsorships
SIGEVO Eletronic Media Affairs
Event Chairs
Student Workshop
Student Workshop
Workshops
Workshops
Tutorials
Tutorials
Competitions
Competitions
Late Breaking Abstracts
Late Breaking Abstracts
Hot of the Press
Hot of the Press
Humies (Chair)
Humies (Publicity Chair)
Summer School
Summer School
Women+@GECCO
Women+@GECCO
Job Market
Job Market
Local Organization Team
Local Organizer
Local Organizer
Local Organizer
Local Organizer
Local Hybridization
Business Committee
Business Committee
Business Committee
Organizer Biographies
Leonardo Trujillo, General Chair
Instituto Tecnológico de Tijuana | webpage
Dr. Leonardo Trujillo is Professor at the Tecnológico Nacional de México/Instituto Tecnológico de Tijuana (ITT), working in the Department of Electrical and Electronic Engineering, and the Engineering Sciences Graduate Program. Dr. Trujillo received an Electronic Engineering degree and a Masters in Computer Science from ITT, as well as a doctorate in Computer Science from CICESE research center in Ensenada, Mexico. His main research interests include evolutionary computation, genetic programming, machine learning and artificial intelligence. Dr. Trujillo has been the PI of several national and international research grants, research that has been extensively published in a variety of journals, conferences and edited books. He is currently Editor-in-Chief of the Genetics Programming and Evolvable Machines journal (Springer), associate editor of the European Journal of Artificial Intelligence (Sage) and Mathematical and Computational Applications (MDPI), and series co-chair of the NEO Workshop series, and has previously been co-organizer of the Genetic Programming Theory and Practice Workshop series.
Ting Hu, Editor-in-Chief
School of Computing, Queen's University, Canada | webpage
Ting Hu is an Associate Professor in the School of Computing at Queen’s University in Kingston, Canada. She received her PhD in Computer Science from Memorial University in Canada and completed her postdoctoral training in bioinformatics at Dartmouth College in USA. Her research focuses on evolutionary algorithm methodology and its applications in biomedicine, with recent interests in explainable artificial intelligence (AI) and interpretable machine learning. Ting serves as Special Communications Editor for journal Genetic Programming and Evolvable Machines.
Sebastian Rojas Gonzalez, Local Chair
University of Ghent, Belgium | webpage
Sebastian Rojas Gonzalez holds a degree in Industrial Systems Engineering (Costa Rica Institute of Technology), Master in Applied Mathematics (Harbin Institute of Technology, China), and PhD in Optimization (KU Leuven, Belgium). He is currently an FWO Postdoctoral Fellow at the Internet and Data Science Lab at Ghent University - IMEC, and a lecturer within the Computational Mathematics group at the Data Science Institute, both in Belgium. He is interested in multiobjective optimization, uncertainty quantification and model-based optimization.
Saul Calderón Ramírez, Local Chair
Instituto Tecnológico de Costa Rica, Costa Rica
Dr. Saúl Calderón is a researcher, professor, and academic leader with experience in artificial intelligence, signal and image processing, machine learning, and high-performance computing. He holds a PhD in Computer Science from De Montfort University (United Kingdom) and a Master's degree in Electrical Engineering and a Bachelor's degree in Computer Science from the University of Costa Rica. He is currently a professor and researcher at the Costa Rica Institute of Technology (TEC), where he coordinates the PARMA (Pattern Recognition and Machine Learning) group. His career combines experience in applied research (Intel, CENAT, CITIC), scientific project leadership, technology development, and academic outreach. He has been a speaker at international forums such as Khipu 2023 and the AI for Health Meeting (WHO/ITU), an organizer of multiple summer schools and symposia on machine learning, and a recipient of the Best Doctoral Thesis 2022-2023 award at his university.
Stephan Winkler, Publicity
Department of Medical and Bioinformatics at University of Applied Sciences Upper Austria, Austria
After studying computer science at University Linz, Stephan Winkler joined University of Applied Siences Upper Austria at Hagenberg. Since 2009, he is professor at the Department of Medical and Bioinformatics; since 2011 he serves as head of the Bioinformatics Research group and head of the Department of Data & Life Sciences since 2019. Furthermore, Stephan Winkler serves as Scientific Head of Softwarepark Hagenberg since 2022. Stephan is founding member of Heuristic and Evolutionary Algorithms Laboratory, the research group developing and maintaining HeuristicLab.
Yazmin Maldonado, Program
Tecnológico Nacional de México/IT Tijuana, Mexico
Yazmin Maldonado Robles received her degree in Electronic Engineering from the Technological Institute of Mazatlán in 2006. She obtained her Master of Science in Digital Systems from the National Polytechnic Institute in 2008, graduating with honors, and her Ph.D. in Computer Science from the Technological Institute of Tijuana in 2012. She is a member of the National System of Researchers (SNI) level I of CONACYT. She is currently a professor and researcher in the Master's and Ph.D. programs in Engineering Sciences at the Technological Institute of Tijuana, where she heads the IS-LAB and leads the research line in cybernetics. Her research areas include embedded systems, FPGAs, heterogeneous computing, intelligent systems, and optimization.
James McDermott, Social Media
University of Galway, Ireland | webpage
James McDermott is a senior lecturer in the School of Computer Science in the College of Science and Engineering, University of Galway, in the west of Ireland. He teaches mostly at post-grad level, in particular in programming for AI, optimisation, and deep learning. He is School Director of Research & Graduate Studies. His research is in artificial intelligence - program synthesis, metaheuristic optimisation, machine learning, and computational creativity. He previously worked and studied in Massachusetts Institute of Technology, University College Dublin, University of Limerick, and Hewlett-Packard.
Jose Manuel Muñoz Contreras, Student Affairs
UABC, Mexico
José Manuel Muñoz received his Ph.D. in Engineering Science from the Technological Institute of Tijuana in 2025. He is currently a professor and researcher at the Faculty of Engineering in Valle de las Palmas, Autonomous University of Baja California (UABC). His research focuses on interpretable models in Genetic Programming (GP), new perspectives in Geometric Semantic GP (GSGP), and visualization techniques for machine learning methods. He collaborates with the TreeLab research group, working on the development of explainable and competitive evolutionary models for symbolic regression and other AI-related problems.
Giorgia Nadizar, Student Affairs
University of Toulouse Capitole, France | webpage
Giorgia Nadizar is a Postdoctoral Research Fellow at the University of Toulouse Capitole, France. She obtained her Ph.D. cum laude from the University of Trieste in 2025, but has explored various research environments through internships and research visits at the Oslo Metropolitan University (Oslo), the Centrum Wiskunde & Informatica (Amsterdam), the ISAE-Supaero (Toulouse), and the MIT (Boston). Her research interests lie at the intersection of embodied AI and explainable/interpretable AI.
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.
Mario Andrés Muñoz, Hybridization (Visualization)
School of Computing and Information Systems, The University of Melbourne, Australia. | webpage
Mario Andrés Muñoz is a Senior Research Fellow at the School of Computing 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.
Oliver Cuate, Hybridization (Visualization)
ESFM - Instituto Politécnico Nacional, Mexico
Dr. Oliver Cuate holds Ph.D. and M.Sc. degrees in Computer Science from CINVESTAV-IPN and a B.Sc. in Mathematical Engineering from the National Polytechnic Institute (IPN). He is a professor in the Mathematics Department at the Escuela Superior de Física y Matemáticas (ESFM-IPN), where he coordinates the Master’s Program in Physical-Mathematical Sciences. His research interests include multi- and many-objective optimization, continuation methods, and decision-making. He received the Springer Best Paper Award (2nd place) at EMO 2019 and the Best Doctoral Thesis Award from SMIO in 2021.
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.
Daniel Hernández, Sponsorships
Tecnológico Nacional de México/IT Tijuana, Mexico
Daniel E Hernandez is a professor at the Tecnológico Nacional de México/ IT de Tijuana, in Tijuana, BC, Mexico. He holds Ph.D. and M.Sc. degrees in Computer Science the from Centro de Investigación Científica y de Educación Superior de Ensenada, B.C., (CICESE), Mexico. His research interests include several data science and artificial intelligence topics such as: machine learning, feature engineering, evolutionary computation and computer vision. .
Yanan Sun, Sponsorships
Sichuan University, China
Yanan Sun is a professor at Sichuan University, China. He has been a research postdoc at Victoria University of Wellington, New Zealand. His research focuses mainly on evolutionary neural architecture search. He has published >100 papers in fully referred journals and conferences, including IEEE TEVC, IEEE TNNLS, IEEE TCYB, NeurIPS, CVPR, ICCV, GECCO, ICML, and CEC. 12 out of the published papers have been selected as ESI Hot Paper, ESI Highly Cited Paper, IEEE CIS Chengdu Section Best Paper, AJCAI2024 Spotlight Paper, and MLMI2022 Best Paper. He is the funding chair of the IEEE CIS Task Force on Evolutionary Deep Learning and Applications. He is the leading chair of the special session on EDLA at IEEE CEC 2019, 2020, 2021, 2022, and 2024, and the symposium on ENASA at IEEE SSIC 2019-2023. He is an associate editor of IEEE Transactions on Evolutionary Compuyation, an associate editor of IEEE Transactions on Neural Networks and Learning Systems, and an editorial member of Memetic Computing.
Edgar Galvan, Sponsorships
Computer Science Department, Maynooth University, Ireland
Dr. Edgar Galván is a full-time academic in the Department of Computer Science at Maynooth University. Prior to this, he held multiple senior research positions at University College Dublin, Trinity College Dublin, and INRIA Paris-Saclay. He is an expert in the properties of encodings, such as neutrality and locality, in Genetic Programming, and a pioneer in the study of Semantic-Based Genetic Programming. His research interests also include applications in combinatorial optimisation, games, and software engineering. Dr. Edgar Galván has been independently ranked among the all-time top 1% of researchers in Genetic Programming, according to University College London.
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.
Event Chair Biographies
Evelyne Lutton, Student Workshop
INRAE, France
Evelyne Lutton is senior scientist (Directeur de Recherche) at INRAE, MATHNUM department, in the EKINOCS research team of the UMR MIA 518 (AgroParisTech, université Paris-Saclay). She is also associate researcher at the ISC-PIF, the french institute for complex systems and at the LLB-CEA MMB group (CNRS UMR 12). Her scientific research concern Evolutionary Algorithms, Fractals, Cooperative-coevolution, and Interactive evolution, with applications in image and signal processing, medical imaging, agri-food process modeling, as well as in art and design.
Pierrick Legrand, Student Workshop
INP Bordeaux, and IMS (UMR CNRS 5218), and Inria ASTRAL team, France
Pierrick Legrand is a Full Professor at Bordeaux INP and IMS, member of the ASTRAL Inria team, and holder of the IBM France Chair at ENSC. He received his PhD in Applied Mathematics from École Centrale de Nantes and the University of Nantes in 2004. His research interests span multifractal analysis, wavelets, signal processing, and evolutionary computation, with applications ranging from signal processing to biomedical engineering. He is President of the Artificial Evolution Association, Editor of the Artificial Evolution volume series in LNCS (Springer), and a recipient of the French Palmes Académiques.
Lee Spector, Workshops
Amherst College, Hampshire College, and the University of Massachusetts, Amherst | webpage
Dr. Lee Spector is a Professor of Computer Science at Amherst College, an Adjunct Professor and member of the graduate faculty in the College of Information and Computer Sciences at the University of Massachusetts, Amherst, and an affiliated faculty member at Hampshire College, where he taught for many years before moving to Amherst College. He received a B.A. in Philosophy from Oberlin College in 1984, and a Ph.D. from the Department of Computer Science at the University of Maryland in 1992. At Hampshire College he held the MacArthur Chair, served as the elected faculty member of the Board of Trustees, served as the Dean of the School of Cognitive Science, served as Co-Director of Hampshire’s Design, Art and Technology program, supervised the Hampshire College Cluster Computing Facility, and served as the Director of the Institute for Computational Intelligence. At Amherst College he teaches computer science and directs an initiative on Artificial Intelligence and the Liberal Arts. My research and teaching focus on artificial intelligence and intersections of computer science with cognitive science, philosophy, physics, evolutionary biology, and the arts. He is the Editor-in-Chief of the Springer journal Genetic Programming and Evolvable Machines and a member of the editorial boards of the MIT Press journal Evolutionary Computation and the ACM journal Transactions on Evolutionary Learning and Optimization. He is a member of the Executive Committee of the ACM Special Interest Group on Evolutionary Computation (SIGEVO) and he has produced over 100 scientific publications. He serves regularly as a reviewer and as an organizer of professional events, and his research has been supported by the U.S. National Science Foundation and DARPA among other funding sources. Among the honors that he has received is the highest honor bestowed by the U.S. National Science Foundation for excellence in both teaching and research, the NSF Director's Award for Distinguished Teaching Scholars.
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.
Oliver Schuetze, Tutorials
CINVESTAV-IPN, Mexico | webpage
Oliver Schütze received the Diploma degree (equivalent to MSc) in Mathematics from the University of Bayreuth, Bayreuth, Germany, and the Ph.D. degree in Natural Sciences from the University of Paderborn, Paderborn, Germany. He is Full Professor with the CINVESTAV-IPN, Mexico City, Mexico. His research interests include numerical and evolutionary optimization.
Alberto Moraglio, Tutorials
University of Exeter, UK | webpage
Alberto Moraglio is a Senior Lecturer at the University of Exeter, UK. He holds a PhD in Computer Science from the University of Essex and Master and Bachelor degrees (Laurea) in Computer Engineering from the Polytechnic University of Turin, Italy. He is the founder of a Geometric Theory of Evolutionary Algorithms, which unifies Evolutionary Algorithms across representations and has been used for the principled design and rigorous theoretical analysis of new successful search algorithms. He gave several tutorials at GECCO, IEEE CEC and PPSN, and has an extensive publication record on this subject. He has served as co-chair for the GP track, the GA track and the Theory track at GECCO. He also co-chaired twice the European Conference on Genetic Programming, and is an associate editor of Genetic Programming and Evolvable Machines journal. He has applied his geometric theory to derive a new form of Genetic Programming based on semantics with appealing theoretical properties which is rapidly gaining popularity in the GP community. In the last three years, Alberto has been collaborating with Fujitsu Laboratories on Optimisation on Quantum Annealing machines. He has formulated dozens of Combinatorial Optimisation problems in a format suitable for the Quantum hardware. He is also the inventor of a software (a compiler) aimed at making these machines usable without specific expertise by automating the translation of high-level description of combinatorial optimisation problems to a low-level format suitable for the Quantum hardware (patented invention).
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).
Aishwaryaprajna , Competitions
University of Exeter, UK
Aishwaryaprajna is a Lecturer in Artificial Intelligence at the Department of Computer Science, University of Exeter. Her research focuses on developing AI systems for decision-making that incorporate optimisation and learning, particularly with a focus on meta-heuristic algorithms, especially evolutionary algorithms. She also investigates optimisation under constraints, multi-objective problems, and the performance analysis of algorithms. Additionally, she explores how various noise (or uncertainty) models can affect decision-making within the system and its environment.%%%Aishwaryaprajna is particularly interested in applying AI to real-world scenarios, such as clinical decision support systems and UAV path planning for surveillance. She is also involved in the development of self-aware multi-agent systems for modelling sustainability dilemmas. Aishwaryaprajna completed her PhD at the University of Birmingham and is currently a Faculty Associate at the Trustworthy AI Lab of Ontario Tech University, where she was a postdoctoral researcher. She is a Responsible Metrics Champion at the University of Exeter, actively supporting the research culture within the institution.
Heike Trautmann, Late Breaking Abstracts
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).
Ying Bi, Late Breaking Abstracts
Zhengzhou Universit
Dr. Bi Ying is professor at the School of Electrical and Information Engineering at Zhengzhou University, China. She has published one monograph in English, and 100+ papers in SCI/EI journals or conferences, including IEEE Transactions on Evolutionary Computation and IEEE Transactions on Cybernetics. She has been awarded the IEEE CIS Outstanding PhD Dissertation Award and the PGSA Research Excellence Award of Victoria University of Wellington (only one person per faculty). She has served as an associate editor or editorial board member for seven journals, including IEEE Transactions on Evolutionary Computation, IEEE Transactions on Artificial Intelligence, and Applied Soft Computing. She serves as the chair of the IEEE CIS Women in Computational Intelligence Subcommittee, and the Chair of the IEEE CIS Task Force on Evolutionary Computer Vision and Image Processing. She was the workshop chair of IEEE CEC 2024, student affairs chair of GECCO 2023, GECCO 2024, and student workshop chair of GECCO 2024. She has been organizing workshops/tutorials/special sessions in conferences related to machine learning, data mining, and evolutionary computation, such as workshops in IEEE ICDM 2021-2024, special sessions/workshops in IEEE CEC 2023-2024, symposiums in IEEE SSCI 2023, etc.
Bing Xue, Hot of the Press
Victoria University of Wellington, New Zealand | webpage
Bing Xue is currently Professor of Artificial Intelligence, and Deputy Head of School in the School of Engineering and Computer Science at Victoria University of Wellington. Her research focuses mainly on evolutionary computation, machine learning, big data, feature selection/learning, evolving neural networks, explainable AI and their real-world applications. Bing has over 400 papers published in fully refereed international journals and conferences including many highly cited papers and top most popular papers. Bing was the Editor of IEEE CIS Newsletter, Chair of the Evolutionary Computation Technical Committee, member of ACM SIGEVO Executive Committee and Chair of IEEE CIS Task Force on Evolutionary Deep Learning and Applications. She also chaired the IEEE CIS Data Mining and Big Data Technical Committee, Students Activities committee, and a member of many other committees. She founded and chaired IEEE CIS Task Force on Evolutionary Feature Selection and Construction, and co-founded and chaired IEEE CIS Task Force on Evolutionary Transfer Learning and Transfer Optimisation. She also won a number of awards including Best Paper Awards from international conferences, and Early Career Award, Research Excellence Award and Supervisor Award from her University, IEEE CIS Outstanding Early Career Award, IEEE TEVC Outstanding Associate Editor and others.%%%Bing has also been served as an Associate/Guest Editor or Editorial Board Member for > 10 international journals, including IEEE TEVC, ACM TELO, IEEE TETCI, IEEE TAI, and IEEE CIM. She is a key organiser for many international conferences, e.g. General Chair of PRICAI 2025 and IVCNZ 2025, Conference Chair of EuroGP 2025 and 2024, Conference Chair of IEEE CEC 2024, ambassador for Women in Data Science NZ 2025, 2024, and 2023, Chair Women+@GECCO 2024, Proceeding Chair of GECCO 2023, Tutorial Chair for IEEE WCCI 2022, Publication Chair of EuroGP 2022, Track Chair for ACM GECCO 2019-2022, Workshop Chair for IEEE ICDM 2021, General Co-Chair of IVCNZ 2020, Program Co-Chair for KETO 2020, Senior PC of IJCAI 2019-2021, Finance Chair of IEEE CEC 2019, Program Chair of AJCAI 2018, IEEE CIS FASLIP Symposium founder and Chair since 2016, and others in international conferences. More can be seen from her website.
Christine Zarges, Hot of the Press
Aberystwyth University, Wales, UK | webpage
Christine Zarges is a Senior Lecturer (Associate Professor) in the Department of Computer Science at Aberystwyth University which she joined as a Lecturer in 2016. Before, she held a postdoctoral research position at the University of Warwick, UK, and a Birmingham Fellowship at the University of Birmingham, UK. She obtained her PhD from TU Dortmund, Germany, in 2011. Christine's research focuses on theory and applications of randomised search heuristics in the context of combinatorial optimisation. She has given tutorials on these topics at various conferences and workshops and contributed to the organisation of these conferences in different capacities, most importantly as track and event chair at GECCO, workshop chair at PPSN, programme chair at FOGA and EvoCop as well as local chair of EvoStar 2024. She is member of the editorial board of Evolutionary Computation (MIT Press) and Associate Editor of IEEE Transactions of Evolutionary Computation and Engineering Applications of Artificial Intelligence. She is a Management Committee member for the UK in European research networks concerned with Randomised Optimisation Algorithms (COST actions CA15140 and CA22137).Christine's research focuses on theory and applications of randomised search heuristics such as evolutionary algorithms and artificial immune systems in the context of combinatorial optimisation. She has given tutorials on these topics at various conferences and workshops and contributed to the organisation of these conferences in different capacities, most importantly as track and event chair at GECCO, workshop chair at PPSN, programme chair at FOGA and EvoCop as well as local chair of EvoStar 2024. She is member of the editorial board of Evolutionary Computation (MIT Press) and Associate Editor of Engineering Applications of Artificial Intelligence (Elsevier). She is a Management Committee member for the UK in European research networks concerned with Randomised Optimisation Algorithms (COST actions CA15140 and CA22137).
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.
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.
Gloria Pietropolli, Women+@GECCO
University of Trieste
Gloria Pietropolli is a Postdoctoral Research Fellow at the University of Trieste, Italy. She obtained her PhD in Computer Science from the same university in 2024. Her research interests span various areas, which she has explored through research visits at institutions such as NOVA University (Lisbon), MIT (Boston), and NEOMA Business School (Paris). Specifically, her work focuses on the design and analysis of machine learning algorithms, particularly GP, and their application across interdisciplinary domains including oceanography, cryptography, economics, and medicine.
Eva Tuba, Women+@GECCO
Trinity University, USA
Eva Tuba is an Assistant Professor of Computer Science at Trinity University, San Antonio, TX, researcher and ERA chair for the EU AutoLearn-SI project at Jozef Stefan Institute in Ljubljana, Slovenia, and researcher on Characterizing crises-caused air pollution alterations project at Singidunum University, Serbia. Prof. Tuba is recipient of the 2024 ACM Women Rising Star award. Prof. Tuba received B. S. and M. S. degrees from the Faculty of Mathematics, University of Belgrade, M. S. from the Graduate School of Computer Science, John Naisbitt University and PhD in Computer Science from Singidunum University. She received a grant for postdoc research at the Southern University of Science and Technology, Shenzhen, China. She is the author or coauthor of around 100 scientific papers (cited more than 4,000 times). Her research interests include Artificial Intelligence, Deep Learning, Neural Networks, Nature-inspired Optimization Algorithms, Image Processing. She is a member of IEEE (and IEEE Young Professionals), ACM (and ACM-W), AMS, SIAM, SCRS Fellow.
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.
Elena Raponi, Job Market
Leiden University | webpage
Elena Raponi is an Assistant professor in Bayesian optimization at the Leiden Institute of Advanced Computer Science (LIACS) of Leiden Univeristy, 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.
Local Organization Team Biographies
Esteban Meneses Rojas, Local Organizer
Instituto Tecnológico de Costa Rica, Costa Rica
Esteban Meneses is the director of the Advanced Computing Laboratory at the Costa Rica High Technology Center. In addition, he works part-time as a Computer Science Professor at the Costa Rica Institute of Technology. He finished his PhD in Computer Science at the University of Illinois at Urbana-Champaign. His research work spans several topics of High Performance Computing: parallel programming, reliability in supercomputing, and deep learning applications.
Esteban Arias Mendez, Local Organizer
Instituto Tecnológico de Costa Rica, Costa Rica
Esteban Arias Méndez is an engineer with a Master's degree in Computer Science from the Technological Institute of Costa Rica. He is currently pursuing a PhD in Engineering at the ITCR-UCR, focusing on the phenomenon of long-term memory learning for cognitive architectures of autonomous robots. He is part of the School of Computer Engineering at the Technological Institute of Costa Rica.
Miguel Abreu Cárdenas, Local Organizer
Instituto Tecnológico de Costa Rica, Costa Rica
Miguel Guillermo Abreu Cárdenas is a Computer Engineer who graduated in 2020 from the Technological University of Havana, Cuba. He completed his Master’s degree in Computer Science at the Costa Rica Institute of Technology at the end of 2024 and is currently pursuing a Ph.D. in Engineering, where he researches uncertainty estimation in ophthalmic image segmentation using training techniques that require only small amounts of data. He has worked as a researcher at PARMA Group since 2023 and was previously a researcher providing teaching support at the Technological University of Havana (2021–2023). He has participated as a speaker at leading workshops on AI safety and other outreach activities.
Cindy Calderón-Arce, Local Organizer
Instituto Tecnológico de Costa Rica, Costa Rica
Cindy Calderón-Arce has a background in Computer-Assisted Mathematics Education, holds a Master’s degree in Applied Mathematics from the University of Puerto Rico, Mayagüez Campus, and a Ph.D. from DOCINADE with an emphasis in Applied Electronic Technologies. She is a Full Professor, researcher, and extensionist at the Costa Rica Institute of Technology (Instituto Tecnológico de Costa Rica). Her areas of interest include optimization, numerical analysis and surrogate modeling, as well as prediction, classification, and pattern recognition based on machine learning and deep learning.
Felipe Meza Obando, Local Hybridization
Instituto Tecnológico de Costa Rica, Costa Rica
Dr. Felipe Meza-Obando has over 20 years of experience in the telecommunications industry and has combined his professional career with academic work as a Professor and Researcher at the Costa Rica Institute of Technology (TEC) and the University of Costa Rica (UCR). At TEC, he leads the ASTRIA research line within the Artificial Intelligence Laboratory for Natural Sciences, while at UCR he serves as a Scientific Researcher at the Laboratory of Solar Astrophysics and Space Weather, contributing to the improvement of predictions of solar activity affecting the interplanetary environment. He holds a Doctorate in Engineering, a Master of Science in Electronic Engineering with a specialization in Digital Signal Processing (DSP), and a Master Universitario in Astronomy and Astrophysics. His research focuses on the development and application of advanced artificial intelligence architectures to address complex problems in astrophysics, integrating DSP, machine learning, generative learning, and genetics algorithms.
Business Committee Biographies
Manuel López-Ibáñez, Business Committee
University of Manchester, UK | webpage
Prof. López-Ibáñez is a Full Professor (Chair) of Optimisation 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 Ph.D. degree from Edinburgh Napier University, U.K., in 2009. He is Editor-in-Chief of ACM Transactions on Evolutionary Learning and Optimization (https://telo.acm.org). Prof.~López-Ibáñez has published more than 100 papers in international peer-reviewed journals and conferences on topics that include stochastic local search, black-box optimization, empirical reproducibility, multi-objective and interactive optimization algorithms for continuous and combinatorial problems, and the automatic configuration and design of optimization algorithms. He is the lead developer and current maintainer of the 'irace' software package for automatic algorithm configuration (https://mlopez-ibanez.github.io/irace/), the 'eaf' package for the analysis of multi-objective optimizers (https://mlopez-ibanez.github.io/eaf/) and the 'moocore' packages for multi-objective optimization (https://github.com/multi-objective/moocore/).
Sara Silva, Business Committee
University of Lisbon, Portugal | webpage
Sara Silva is an Associate Professor at the Faculty of Sciences and a member of the Computer Science and Engineering Research Centre (LASIGE) in the Univerity of Lisbon, Portugal. Her main research interests are machine learning and evolutionary computation, including interdisciplinary applications in the areas of remote sensing and bioinformatics. She is associate editor of Transactions on Evolutionary Learning and Optimization (TELO), Swarm and Evolutionary Computation (SWEVO), and Genetic Programming and Evolvable Machines (GPEM). In 2015 she was Editor-in-Chief of GECCO, and in 2017 and 2018 she was chair of its Genetic Programming track. In 2018 she received the EvoStar Award for Outstanding Contribution to Evolutionary Computation in Europe. In 2023 she was General Chair of GECCO. She created the MATLAB Genetic Programming Toolbox (GPLAB) and co-authored the Springer book Lectures on Intelligent Systems.