Organizers

Sara Silva, General Chair

University of Lisbon, Portugal | webpage

Sara Silva is a Principal Investigator at the Computer Science and Engineering Research Centre (LASIGE) in Universidade de Lisboa, Portugal. Her main research interests are machine learning and evolutionary computation, including interdisciplinary applications in the areas of remote sensing and bioinformatics. She is an associate editor at ACM Transactions on Evolutionary Learning and Optimization, Swarm and Evolutionary Computation, and Genetic Programming and Evolvable Machines. In 2018 she received the Evo* Award for Outstanding Contribution to Evolutionary Computation in Europe. She created the MATLAB Genetic Programming Toolbox (GPLAB).

Luís Paquete, Editor-in-Chief

University of Coimbra, Portugal | webpage

Luís Paquete is Associate Professor at the Department of Informatics Engineering, University of Coimbra, Portugal. He received his Ph.D. in Computer Science from T.U. Darmstadt, Germany, in 2005 and a M.S. in Systems Engineering and Computer Science from the University of Algarve, Portugal, in 2001. His research interest is mainly focused on exact and heuristic solution methods for multiobjective combinatorial optimization problems. He is in editorial board of Operations Research Perspectives and Area Editor at ACM Transactions on Evolutionary Learning and Optimization.

Leonardo Vanneschi, Local Chair

NOVA Information Management School (NOVA IMS), Universidade Nova de Lisboa, Portugal | webpage

Leonardo Vanneschi is a Full Professor at NOVA IMS. His main research interests involve Machine Learning, Data Science, Complex Systems, and in particular Evolutionary Computation. His work can be broadly partitioned into theoretical studies on the foundations of Evolutionary Computation, and applicative work. The former covers the study of the principles of functioning of Evolutionary Algorithms, with the final objective of developing strategies to outperform the existing techniques. The latter covers several different fields among which computational biology, image processing, personalized medicine, engineering, logistics, economics and marketing. He has published more than 250 contributions and he has led numerous research projects. He has served as chair in several international scientific conferences, including GECCO and several events of Evo*. He is a member of the editorial board of the GPEM and the ACM TELO journals. In 2015, he received the Evo* Award for Outstanding Contribution to Evolutionary Computation in Europe.

Nuno Lourenço, Hybridization

University of Coimbra, CISUC, DEI | webpage

Nuno Lourenço is an Assistant Professor at the Department of Informatics Engineering of the University of Coimbra, where he obtained his PhD in Information Science and Technology in 2016. He is the current coordinator of the Evolutionary and Complex Systems (ECOS) group, and is a member of the Centre for Informatics and Systems of University of Coimbra (CISUC) since 2009. Formerly, he was appointed as a Senior Research Officer at the University of Essex in the United Kingdom. His main research interests are in the areas Bio-Inspired Algorithms, Optimisation and Machine Learning. He is the co-creator of Structured Grammatical Evolution, Probabilistic Grammatical Evolution, and DENSER, a novel approach to automatically design Deep Artificial Neural Networks using Evolutionary Computation. He served as chair in the main conferences of the Evolutionary Computation field, namely EuroGP 2020 and 2021 as program-chair, and PPSN 2018 and EuroGP 2019 as publication chair. He is member of the Programme Committee of GECCO, PPSN, EuroGP; member of the Steering Committee of EuroGP; and executive board member of SPECIES. He has authored or co-authored more than 60 articles in journals and top conferences from the Evolutionary Computation and Artificial Intelligence areas and he has been involved as a researcher in 13 projects (national and international).

Aleš Zamuda, Hybridization

University of Maribor | webpage

Assoc. Prof. Dr. Aleš Zamuda received his B.Sc., M.Sc., and Ph.D. degrees in computer science from University of Maribor, Slovenia, in 2006, 2008, and 2012, respectively. As an affiliate of Faculty of Electrical Engineering and Computer Science at the University of Maribor he is positioned within research group Computer Architecture and Languages Laboratory and programme-funded unit Computer Systems, Methodologies, and Intelligent Services, and project DAPHNE: Integrated Data Analysis Pipelines for Large-Scale Data Management, HPC, and Machine Learning. His areas of interest include differential evolution, multiobjective optimization, evolutionary robotics, artificial life, and cloud computing. He has written over 80 scientific papers and among them several journal papers ranked in first quarter of computer science category such as ESWA, INS, SWEVO, APEN, JoCS, Applied Soft Computing, and Information Sciences; and received several citations of his scientific works. He started programming in elementary school and since then won several national and international awards, such as Danubius Young Scientist at few years after his habilitation; from his dissertation, 2012 gold medal at international invention fair in Seoul; and international IEEE R8 SPC 2007 award for diploma work. His biography is selected in Marquis Who is Who in the World and he is an IEEE Senior Member, IEEE CIS member, and chaired several IEEE positions at chapter, section, and society level. He is also a regular reviewer for the best journals in computer science, like IEEE Transactions on Evolutionary Computation and more than 50 other prominent scientific journals. He is member of SLAIS (part of EurAI) and SLING (supporting EuroHPC Vega). He has been employed as an expert / evaluator by the European Commission for EU projects (Horizon 2020 Framework Programme (H2020) Excellent science; MSCA PF) and other research funding agencies (COST, SPIRIT, Mexico/Poland). He has also been employed at Technical University of Ostrava (IT4Innovations national supercomputing center) for three months and a month-long visiting researcher at Aberystwyth University and several times at University of Las Palmas de Gran Canaria, and conducted dozens other week-long visits at universities in across EU (Ghent University, University of Iceland, University of Alicante, Tomas Bata University in Zlín, University of Chemistry and Technology, Prague). He has been a member of the program/technical committees of more than hundred international conferences and held over dozen editorial roles.

Ahmed Kheiri, Hybrid Scheduling

Lancaster University, UK | webpage

Ahmed Kheiri is a Senior Lecturer (Associate Professor) at Lancaster University. 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.

Arnaud Liefooghe, Hybrid Scheduling

University of Lille, France | webpage

Arnaud Liefooghe has been an Associate Professor (Maître de Conférences) with the University of Lille, France, since 2010. He is a member of the CRIStAL research center, CNRS, and of the Inria Lille-Nord Europe research center. He is also the Co-Director of the MODŌ international lab between Shinshu University, Japan, and the University of Lille. He received a PhD degree from the University of Lille in 2009, and the Habilitation in 2022. In 2010, he was a Postdoctoral Researcher with the University of Coimbra, Portugal. In 2020, he was on CNRS sabbatical at JFLI, and an Invited Professor with the University of Tokyo, Japan. Since 2021, he has been appointed as a Collaborative Professor at Shinshu University, Japan. His research activities deal with the foundations, the design and the analysis of stochastic local search and evolutionary algorithms, with a particular interest in multi-objective optimization and landscape analysis. He has co-authored over ninety scientific papers in international journals and conferences. He was a recipient of the best paper award at EvoCOP 2011 and at GECCO 2015. He has recently served as the co-Program Chair for EvoCOP 2018 and EvoCOP 2019, as the Proceedings Chair for GECCO 2018, as the co-EMO Track Chair for GECCO 2019, and as the Virtualization Chair for GECCO 2021.

Bing Xue, Proceedings

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 300 papers published in fully refereed international journals and conferences including many highly cited papers and top most popular papers. %%%%%%Bing is currently 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. Conference Chair of IEEE CEC 2024, Co-ambassador for Women in Data Science NZ 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: https://homepages.ecs.vuw.ac.nz/~xuebing/index.html%%%

Ying Bi, Student Affairs

Zhengzhou University, China | webpage

Ying Bi is currently a researcher at Zhengzhou University, China. She received the Ph.D. degree in 2020 from the Victoria University of Wellington (VUW), New Zealand. Her research focuses mainly on evolutionary computer vision and machine learning. She has published an authored book on genetic programming for image classification and over 50 papers in fully refereed journals and conferences. Dr Bi is currently the Vice-Chair of IEEE CIS Task Force on Evolutionary Computer Vision and Image Processing, and a member of IEEE CIS Task Force on Evolutionary Computation for Feature Selection and Construction. She is serving as the workshop chair of IEEE CEC 2024, organizer of the EDMML workshop in IEEE ICDM 2022 and IEEE ICDM 2021, and co-chair of the special session on ECVIP at IEEE CEC 2022 and IEEE CIMSIVP at IEEE SSCI 2022. She is serving as guest editor for two international journals. She has been serving as an organizing committee member of IEEE CEC 2019 and Australasian AI 2018, PC member/reviewer of over ten conferences and reviewer of over twenty international journals.

Nelishia Pillay, Student Affairs

University of Pretoria | webpage

Nelishia Pillay is a Professor at the University of Pretoria, South Africa. She holds the Multichoice Joint-Chair in Machine Learning and SARChI Chair in Artificial Intelligence for Sustainable Development. She is chair of the IEEE Technical Committee on Intelligent Systems Applications, IEEE CIS WCI sub-commitee and the IEEE Task Force on Automated Algorithm Design, Configuration and Selection. Her research areas include hyper-heuristics, automated design of machine learning and search techniques, combinatorial optimization, genetic programming, genetic algorithms and deep learning for and more generally machine learning and optimization for sustainable development. These are the focus areas of the NICOG (Nature-Inspired Computing Optimization) research group which she has established.

Irene Moser, Electronic Media

Swinburne University of Technology, Australia | webpage

Irene Moser is an Associate Professor in Computer Science and Software Engineering at Swinburne University of Technology. She holds a BBA from Helsinki Business Polytechnic, Finland, a MCSc from Reutlingen University and a Masters of IT as well as a PhD in Computer Science from Swinburne University. Her interests include all aspects of optimisation, in particular heuristics and their application to practical problems, among them vehicle routing, traffic and active transport. A major line of investigation is the characterisation of problems and heuristics.

Arthur Guijt, Electronic Media

Centrum Wiskunde & Informatica, The Netherlands

Arthur Guijt is a PhD student at Centrum Wiskunde & Informatica, working on applying Model-based Evolutionary Algorithms in parallel and distributed settings, in particular for Neural Architecture Search. Arthur has obtained his MSc on the application of MBEAs to permutation based scheduling problems.

Jéssica Catarino, Publicity

University of Lisbon, Portugal | webpage

Jéssica Catarino is a PhD student in informatics at the LASIGE Research Centre, located at the Faculty of Sciences of the University of Lisbon (FCUL). Her research focuses on applying AI models for breast cancer diagnosis in medical imaging.

Pablo García-Sánchez, Publicity

University of Granada, Spain | webpage

Pablo García-Sánchez was born in Granada (Spain) in 1983 and graduated in Computer Science in 2007 at the University of Granada (UGR). He received his PhD in 2014 in the same university, for his dissertation on the field of service-oriented evolutionary algorithms. His other research lines are the distributed and parallel algorithms, and artificial intelligence applied to videogames and scientometry. He is working as a Associate Lecturer at the Department of Computer Architecture and Computer Technology of the UGR. He has published more than 60 papers in international conferences and 20 papers in indexed journals. Dr. García-Sánchez has been a program committee member of more than 10 international conferences, being part of the organization team of conferences such as IEEE CIG, GECCO, EVOAPPS or the Python Spain Conference, among others.

Leonardo Trujillo, Sponsorships

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 Master's in Computer Science degree from ITT, as well as a doctorate in Computer Science from CICESE research center in Ensenada, Mexico. He is involved in interdisciplinary research in the fields of evolutionary computation, computer vision, machine learning and pattern recognition. His research focuses on Genetic Programming (GP) and developing new learning and search strategies based on this paradigm. Dr. Trujillo has been the PI of several national and international research grants, receiving several distinctions from the Mexican science council (CONACYT). His work has been published in over 70 journal papers, 60 conference papers, 18 book chapters, and he has edited 6 books on EC and GP. He is on the Editorial Board of the journals GPEM (Springer) and MCA (MDPI), and associate editor of AI Communications, Special Issue Guest Editor on 5 occasions, and regularly serves as a reviewer for highly respected journals in AI, EC and ML, is series co-chair of the NEO Workshop series, and has organized, been track chair or served as PC member of various prestigious conferences, including GECCO, GPTP, EuroGP, PPSN, CEC, CVPR and ECCV.

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=31, 3224 citations according to Google Scholar.

Nadarajen Veerapen, SIGEVO Electronic 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 the Electronic Media Chair for GECCO 2021 and has served as Electronic Media Chair for GECCO 2020, 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 2017-2019.

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.

Nguyen Dang, Workshops

University of St Andrews, UK

Nguyen Dang is a Senior Research Fellow at the University of St Andrews (UK). Her research interests include automated algorithm configuration, algorithm selection, dynamic algorithm configuration (DAC), and the applications of such methods to the domain of constraint programming.

Carola Doerr, Workshops

CNRS and Sorbonne University, France | webpage

Carola Doerr, formerly Winzen, is a permanent 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 board member of the Evolutionary Computation journal. She is/was program chair for 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. Her works have received several awards, among them the CNRS bronze medal, the Otto Hahn Medal of the Max Planck Society, best paper awards at EvoApplications, CEC, and GECCO.

Nelishia Pillay, Student Workshop

University of Pretoria | webpage

Nelishia Pillay is a Professor at the University of Pretoria, South Africa. She holds the Multichoice Joint-Chair in Machine Learning and SARChI Chair in Artificial Intelligence for Sustainable Development. She is chair of the IEEE Technical Committee on Intelligent Systems Applications, IEEE CIS WCI sub-commitee and the IEEE Task Force on Automated Algorithm Design, Configuration and Selection. Her research areas include hyper-heuristics, automated design of machine learning and search techniques, combinatorial optimization, genetic programming, genetic algorithms and deep learning for and more generally machine learning and optimization for sustainable development. These are the focus areas of the NICOG (Nature-Inspired Computing Optimization) research group which she has established.

Marco Tomassini, Student Workshop

University of Lausanne

Marco Tomassini is an emeritus professor of Computer Science at the Information Systems Department of the University of Lausanne, Switzerland. He got a Doctor's degree in theoretical chemistry from the University of Perugia, Italy, working on computer simulations of condensed matter systems. His current research interests are centered around complex systems and complex networks. He is active in evolutionary game theory, fitness landscape analysis and problem difficulty, optimization, and complex networks dynamics. He has been Program Chairman of several international events and has published many scientific papers and several authored and edited books in these fields. He has received the EvoStar 2010 Award in recognition for oustanding contribution to evolutionary computation.

Penousal Machado, Tutorials

University of Coimbra, CISUC, DEI | webpage

Penousal Machado leads the Cognitive and Media Systems group at the University of Coimbra. His research interests include Evolutionary Computation, Computational Creativity, and Evolutionary Machine Learning. In addition to the numerous scientific papers in these areas, his works have been presented in venues such as the National Museum of Contemporary Art (Portugal) and the “Talk to me” exhibition of the Museum of Modern Art, NY (MoMA).

William La Cava, Competitions

Harvard, Boston Children’s Hospital, USA | webpage

William La Cava is an Assistant Professor in the Computational Health Informatics Program (CHIP) at Boston Children’s Hospital and Harvard Medical School. He received his PhD from UMass Amherst with a focus on interpretable modeling of dynamical systems. Prior to joining CHIP, he was a post-doctoral fellow and research associate in the Institute for Biomedical Informatics at the University of Pennsylvania.

Anna Esparcia-Alcázar, Women+@GECCO

Agència Valenciana de la Innovació, Spain | webpage

Anna I. Esparcia-Alcázar holds a degree in Electrical Engineering from the Universitat Politècnica de València (UPV), Spain, and a PhD from the University of Glasgow, UK. She has over 20 years experience in developing and leading R&D projects & teams both in industry and academia. Her research involved the application of Evolutionary Computation to areas as diverse as signal processing, logistics and cybersecurity. She is currently with the Valencian Innovation Agency (AVI). In 2015 she earned the Evostar Award for Outstanding Contribution to Evolutionary Computation in Europe. She is an elect member of the Executive Committee of SIGEVO, and a Senior Member of both the IEEE and the ACM. She is currently coordinator of the EvoStar conferences and vicepresident of the SPECIES society, of which she was one of the founding members.

Andrejaana Andova, Women+@GECCO

Jozef Stefan Institute, Slovenia

Giorgia Nadizar, Women+@GECCO

Università degli Studi di Trieste, Italy | webpage

Giorgia Nadizar is a PhD student in Applied Data Science and Artificial Intelligence at the University of Trieste. Her main research focus is bio-inspired evolutionary robotics, but her interests also include genetic programming and interpretable AI.

Aniko Ekart, Late Breaking Abstracts

Aston University, UK | webpage

Aniko Ekart is currently Head of Computer Science at Aston University, Birmingham, United Kingdom. She holds a PhD in Informatics from Eötvös Loránd University, Budapest, Hungary. Her research interests include the theory and application of evolutionary computation and genetic programming in particular. She has experience in real-world applications of a variety of computational intelligence and data mining methods, including visual art, logistics (engineering) and vascular health (medicine). She has been working on various European Union funded research projects, including Advanced predictive analysis based decision support engine for logistics (ADVANCE), Actions for Excellence in Smart Cyber-Physical Systems applications through exploitation of Big Data in the context of Production Control and Logistics (EXCELL) and INdividual Vascular SignaTure: A new machine learning tool to aid personalised management of risk for cardiovascular disease (INVeST).

Justyna Petke, Late Breaking Abstracts

University College London | webpage

Justyna Petke is a Principal Research Fellow and Proleptic Associate Professor, conducting research in genetic improvement. She has a doctorate in Computer Science from University of Oxford and is now at the Centre for Research on Evolution, Search and Testing (CREST) at University College London. Her work on genetic improvement was awarded a Silver and a Gold 'Humie' at GECCO 2014 and GECCO 2016. She also organised several Genetic Improvement Workshops. She currently serves on the editorial board of the Genetic Programming and Evolvable Machines (GPEM), Empirical Software Engineering (EMSE), and Automated Software Engineering (ASE) journals.

John Koza, Humies

- | webpage

Erik Goodman, Humies

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

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.

Alberto Moraglio, Hot-off-the-Press

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).

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.

Bogdan Filipic, Evolutionary Computation in Practice

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 associate 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 stochastic optimization. He focuses on evolutionary multiobjective optimization, including result visualization, constraint handling and use of surrogate models. He is also active in promoting evolutionary computation in practice and has led optimization projects for steel industry, car manufacturing and energy management. He was the general chair of PPSN 2014, organized several special sessions and tracks at major international conferences, and serves as a program chair for BIOMA 2020. He was a guest lecturer at the University of Oulu, Finland, and the VU University Amsterdam, The Netherlands, and was giving tutorials at recent CEC and GECCO conferences.

Tea Tušar, Job Market

Jožef Stefan Institute, Slovenia | webpage

Tea Tušar is a research fellow 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.

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.

Illya Bakurov, Team Member

NOVA Information Management School (NOVA IMS), Universidade Nova de Lisboa, Portugal

Illya Bakurov holds a PhD in Information Management by NOVA IMS where he is an auxiliary invited professor and conducts research in the fields of evolutionary computation and image processing.

João Batista, Team Member

LASIGE, Faculty of Sciences of the University of Lisbon, Lisbon, Portugal

João Batista is a PhD Student in Informatics at the LASIGE Computer Science and Engineering Research Centre at the Faculty of Sciences of the University of Lisbon (FCUL). On the computer science field, his main research interests are focused on using evolutionary computation algorithms for automatic feature engineering. His work studied topics such as feature selection, feature construction, model explainability and model complexity. Outside the computer science field, his work is applied in remote sensing data, namely to the mapping of land cover types using satellite imagery.

Mauro Castelli, Team Member

NOVA Information Management School (NOVA IMS), Universidade Nova de Lisboa, Portugal

Mauro Castelli is an associate professor and a senior research scientist in the field of Computational Intelligence and Machine Learning in the NOVA Information Management School (NOVA IMS), Universidade NOVA de Lisboa (Portugal). He received his Ph.D. in Computer Science at the University of Milano Bicocca (Italy). His research interests are in the field of machine learning, in particular, evolutionary algorithms. His research focuses on the development, implementation, and application of computational intelligence systems for addressing complex real-world problems in different domains. Mauro has a proven record of outstanding research, as evidenced by existing high quality publications. He has published more than 120 contributions in a variety of top-quality academic journals and international conferences.

Guilherme Espada, Team Member

LASIGE, Faculdade de Ciências da Universidade de Lisboa, Portugal

Guilherme Espada is a PhD student at the LASIGE lab in Lisbon, Portugal. His research centers on analysing programs by bridging the gap between Programming Language/Computation Theory and Evolutionary Computation research.

Alcides Fonseca, Team Member

LASIGE, Faculdade de Ciências da Universidade de Lisboa, Portugal | webpage

Alcides Fonseca is an Assistant Professor at the University of Lisbon, and the Reliable Software Systems research line leader at LASIGE. He has a PhD in automatic optimization of parallel programs by the University of Coimbra. Alcides leads the LASIGE side of the CAMELOT project, that aims to improve the machine learning development process in collaboration with Feedzai, U. Coimbra, IST and CMU. He is also the PI of Resource Aware Programming, a project that aims to give programmers immediate feedback on the energy consumption of their code. He is also a consultant with Genomed, a genetics diagnosis company and a mentor at Decipad, a company that is re-inventing spreadsheets as computable documents.

Karina Brotto Rebuli, Team Member

Università di Torino, Italy | webpage

Karina Brotto Rebuli is a Data Scientist, with a Masters in Advanced Analytics from the NOVA University of Lisbon.%%%Her research interests are Evolutionary Computation, Automatic Machine Learning and ethics of Artificial Intelligence systems.%%%Currently, she is doing a PhD at the University of Turin on developing and applying Machine Learning modelling to improve animal welfare.

Nuno Rodrigues, Team Member

LASIGE, Faculty of Sciences of the University of Lisbon, Lisbon, Portugal

Nuno Rodrigues is a researcher at LASIGE, in the Faculty of Sciences of the University of Lisbon, and an invited professor at NOVA IMS. He has a Master's degree in Informatics from the University of Lisbon, and his Ph.D. project focuses on the development of deep learning systems for prostate cancer radiomics, included in the Horizons 2020 ProCAncer-I project.

Rita Sousa, Team Member

LASIGE, Faculdade de Ciências da Universidade de Lisboa, Portugal

Rita Sousa is a researcher at LASIGE, in the Faculty of Sciences of the University of Lisbon, and a teaching assistant at Catolica-Lisbon School of Business and Economics. She has a Master's degree in Bioinformatics and Computational Biology from the University of Lisbon, and her Ph.D. project focuses on evolving knowledge graph-based representations to improve the performance of machine learning algorithms in biomedical applications.

Peter A. N. Bosman, Business Committee

Centre for Mathematics and Computer Science, The Netherlands | webpage

Peter Bosman is a senior researcher in the Life Sciences research group at the Centrum Wiskunde & Informatica (CWI) (Centre for Mathematics and Computer Science) located in Amsterdam, the Netherlands. Peter obtained both his MSc and PhD degrees on the design and application of estimation-of-distribution algorithms (EDAs). He has (co-)authored over 150 refereed publications on both algorithmic design aspects and real-world applications of evolutionary algorithms. At the GECCO conference, Peter has previously been track (co-)chair, late-breaking-papers chair, (co-)workshop organizer, (co-)local chair (2013) and general chair (2017).

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.