Markus Wagner, General Chair
University of Adelaide, Australia | webpage
Markus Wagner is an Associate Professor at the School of Computer Science, University of Adelaide, Australia. He has done his PhD studies at the Max Planck Institute for Informatics in Saarbruecken, Germany and at the University of Adelaide, Australia. For the outcomes of his studies, he has received the university's Doctoral Research Medal - the first for his school - and three best paper awards. His research topics range from mathematical runtime analysis of heuristic optimisation algorithms and theory-guided algorithm design to applications of heuristic methods to renewable energy production, professional team cycling and software engineering. So far, he has been a program committee member 80+ times, and he has written 150+ articles with 200+ different co-authors. He is an ACM Lifetime Member, is on SIGEVO's Executive Board and serves as the first ever Sustainability Officer. He has contributed to GECCOs as Workshop Chair and Competition Chair, and he has chaired several education-related committees within the IEEE CIS, where he also served as founding chair of two task forces.
Jonathan Fieldsend, Editor-in-Chief
University of Exeter, UK | webpage
Jonathan Fieldsend, Editor-in-Chief University of Exeter, UK is Professor of Computational Intelligence at the University of Exeter. He has a degree in Economics from Durham University, a Masters in Computational Intelligence from the University of Plymouth and a PhD in Computer Science from the University of Exeter. He has over 100 peer-reviewed publications in the evolutionary computation and machine learning domains, with particular interests in multiple-objective optimisation, and the interface between optimisation and machine learning. Over the years, he has been a co-organiser of a number of different Workshops at GECCO (VizGEC, SAEOpt and EAPwU), as well as EMO Track Chair in GECCO 2019 and GECCO 2020. He is an Associate Editor of IEEE Transactions on Evolutionary Computation, and ACM Transactions on Evolutionary Learning and Optimization, and on the Editorial Board of Complex and Intelligence Systems. He is a vice-chair of the IEEE Computational Intelligence Society (CIS) Task Force on Data-Driven Evolutionary Optimisation of Expensive Problems, and sits on the IEEE CIS Task Force on Multi-modal Optimisation and the IEEE CIS Task Force on Evolutionary Many-Objective Optimisation.
Alma Rahat, Proceedings Chair
Swansea University | webpage
Dr Alma Rahat is a Lecturer in Data Science at Swansea University. He is an expert in Bayesian search and optimisation for computationally expensive problems (for example, geometry optimisation using computational fluid dynamics). His particular expertise is in developing effective acquisition functions for single and multi-objective problems, and locating the feasible space. He is one of the twenty four members of the IEEE Computational Intelligence Society Task Force on Data-Driven Evolutionary Optimization of Expensive Problems, and he has been the lead organiser for the popular Surrogate-Assisted Evolutionary Optimisation workshop at the prestigious Genetic and Evolutionary Computation Conference (GECCO) since 2016. He has a strong track record of working with industry on a broad range of optimisation problems. His collaborations have resulted in numerous articles in top journals and conferences, including a best paper in Real World Applications track at GECCO and a patent.%%%%%%Dr Rahat has a BEng (Hons.) in Electronic Engineering from the University of Southampton, UK, and a PhD in Computer Science from the University of Exeter, UK. He worked as a product development engineer after his bachelor's degree, and held post-doctoral research positions at the University of Exeter. Before moving to Swansea, he was a Lecturer in Computer Science at the University of Plymouth, UK.
Sara Tari, Student Affairs Chair
Univ. Littoral Côte d'Opale, France | webpage
Sara Tari is an associate professor at the Université du Littoral Côte d'Opale, Calais, France. She held a postdoctoral position in the ORKAD team at Université de Lille between september 2019 and august 2020. Prior to that, she received her PhD from Université d'Angers in 2019. Her research interests are combinatorial optimization, evolutionary algorithms, and multiobjective optimization. The main part of her research is related to fitness landscape analysis.
Nelishia Pillay, Student Affairs Chair
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. She is chair of the IEEE Technical Committee on Intelligent Systems Applications, IEEE Task Force on Hyper-Heuristics 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 Chair
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.
Aldeida Aleti, Publicity Chair
Monash University | webpage
Aldeida's research interests are in the area of Automated Software Engineering, which aims at creating machines that write software, from requirements elicitation, to design, code generation, testing, and finally code repair. This involves the application and advancement of novel Artificial Intelligence and optimisation techniques.
Aleš Zamuda, Virtualisation Chair
University of Maribor | webpage
Assoc. Prof. Dr. Ales 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 50 scientific papers and among them several journal papers ranked in first quarter of computer science category such as 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 40 other prominent scientific journals. He has been employed by the European Commission as an expert / evaluator of EU projects (Horizon 2020 Framework Programme (H2020) Excellent science). He has also been employed at Technical University of Ostrava for three months and a monthlong visiting researcher at Aberystwyth University and several times at University of Las Palmas de Gran Canaria, and conducted dozens other weeklong 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 70 international conferences over the last few years. He is also associate editor at Swarm and Evolutionary Computation.
Ahmed Kheiri, Hybrid Scheduling Chair
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.
Erik Hemberg, Local Organizer
MIT CSAIL | webpage
Erik Hemberg is a Research Scientist in the AnyScale Learning For All (ALFA) group at Massachusetts Institute of Technology Computer Science and Artificial Intelligence Lab, USA. He has a PhD in Computer Science from University College Dublin, Ireland and an MSc in Industrial Engineering and Applied Mathematics from Chalmers University of Technology, Sweden. His work focuses on developing autonomous, pro-active cyber defenses that are anticipatory and adapt to counter attacks. He is also interested in automated semantic parsing of law, and data science for education and healthcare.
Heike Trautmann, Tutorials
University of Münster, Germany | webpage
Heike Trautmann is Professor of Data Science: Statistics and Optimization, both at the Department of Information Systems, University of Münster, Germany and the University of Twente, Netherlands. She is also Director of the European Research Center for Information Systems (ERCIS) and head of the ERCIS competence center Social Media Analytics. Moreover, she is key supporter of the Confederation of Laboratories for Artificial Intelligence Research in Europe (CLAIRE). Her research mainly focuses on Data Science, Automated Algorithm Selection and Configuration, Exploratory Landscape Analyis, (Multiobjective) Evolutionary Optimization and Data Stream Mining. She is associate editor of the IEEE Transactions on Evolutionary Computation, the ACM Transactions on Evolutionary Learning and Optimization as well as the Evolutionary Computation Journal (ECJ).
Carola Doerr, Workshops
CNRS and Sorbonne University, France | webpage
Carola Doerr, formerly Winzen, is a permanent CNRS researcher at Sorbonne University 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 regularly involved in the organization of events around evolutionary computation and related topics, for example as program chair for PPSN 2020, FOGA 2019 and the theory tracks of GECCO 2015 and 2017, as guest editor for IEEE Transactions on Evolutionary Computation and Algorithmica, as organizer of Dagstuhl seminars and Lorentz Center workshops. Carola is an associate editor of ACM Transactions on Evolutionary Learning and Optimization (TELO) and board member of the Evolutionary Computation journal. Her works have received several awards, among them the Otto Hahn Medal of the Max Planck Society, best paper awards at EvoApplications and CEC, and four best paper awards at GECCO.
Alberto Moraglio, Workshops
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).
Marcella Scoczynski Ribeiro Martins, Competitions
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.
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.
Marcus Gallagher, Hot-off-the-Press
University of Queensland | webpage
%%%%%%Marcus Gallagher is an Associate Professor in the Artificial Intelligence Group in the School of Information Technology and Electrical Engineering. His research interests are in artificial intelligence, including optimisation and machine learning. He is particularly interested in understanding the relationship between algorithm performance and problem structure via benchmarking. My work includes cross-disciplinary collaborations and real-world applications of AI techniques.%%%Dr Gallagher received his BCompSc and GradDipSc from the University of New England, Australia in 1994 and 1995 respectively, and his PhD in 2000 from the University of Queensland, Australia. He also completed a GradCert (Higher Education) in 2010.%%%
Yew-Soon Ong, Late-Breaking Abstracts
Nanyang Technological University | webpage
Yew-Soon Ong is currently President's Chair Professor of Computer Science at the School of Computer Science and Engineering at Nanyang Technological University (NTU), Singapore. At the same time, he is Chief Artificial Intelligence (CAS) Scientist of the Singapore's Agency for Science, Technology and Research (A*STAR). At NTU, he serves co-Director of the Singtel-NTU Cognitive & Artificial Intelligence Joint Lab (SCALE@NTU), co-Director of the A*Star SIMTECH-NTU Joint Lab on Complex Systems.%%%His current research interests include Artificial & Computational Intelligence spanning Memetic Computation, Evolutionary & Transfer Optimization and Machine Learning. His research grants comprises of external funding from both national and international partners that include Boeing Research & Development (USA), Rolls-Royce (UK) and Honda Research Institute Europe (Germany), the National Research Foundation of Singapore, National Grid Office, A*STAR, Singapore Technologies Dynamics and MDA-GAMBIT. His research on Memetic Computation was first featured by Thomson Scientific's Essential Science Indicators as one of the most cited emerging area of research in August 2007. He was listed as a Thomson Reuters Highly Cited Researcher in 2015 and 2016 and among the World's Most Influential Scientific Minds. He also received the 2012 IEEE Transactions on Evolutionary Computation Outstanding Paper Award, the 2015 IEEE Computational Intelligence Magazine Outstanding Paper Award and very recently the 2019 IEEE Transactions on Evolutionary Computation Outstanding Paper Award for his works in Memetic Computation.
Abhishek Gupta, Late-Breaking Abstracts
Singapore Institute of Manufacturing Technology | webpage
Abhishek Gupta is a Scientist in A*STAR’s Singapore Institute of Manufacturing Technology (SIMTech). He holds a PhD in Engineering Science from the University of Auckland, New Zealand. His current research is on developing algorithms at the intersection of optimization and machine learning, with particular application to cyber-physical production systems.
Erik Goodman, Humies
Michigan State University and BEACON Center for the Study of Evolution in Action, USA | webpage
Erik Goodman is a Professor of Electrical & Computer Engineering, of Mechanical Engineering, and of Computer Science & Engineering at Michigan State University. He is Director of the BEACON Center for the Study of Evolution in Action, an NSF Science and Technology Center funded at $25 million in 2010. He studied genetic algorithms under John Holland at the University of Michigan, before they had been named. His use of a genetic algorithm in 1971 to solve for 40 coefficients of a highly nonlinear model of a bacterial cell was the first known GA application on a real-world problem, and required nearly a year for one run on a dedicated computer. He has developed and used evolutionary algorithms ever since, including for parameterization of complex ecosystem models, for evolution of cooperative behavior in artificial life, for factory layout and scheduling, for protein folding and docking, for design of composite structures, and for data mining and pattern classification. His recent research has centered on sustainable evolutionary computation, design of mechatronic systems using genetic programming, and multi-objective evolutionary algorithms in support of multi-criterion decision making. He was co-founder and formerly VP Technology of Red Cedar Technology, which provides tools for automated engineering design based on evolutionary computation. He chaired ICGA-97 and GECCO-2001, chaired GECCO's sponsoring organization, ISGEC, from 2001-2004, and was the founding chair of ACM SIGEVO, 2005-2007.
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.
Christine Zarges, Summer School
Aberystwyth University, Wales, UK | webpage
Christine Zarges received her degree and PhD from the TU Dortmund, Germany, in 2007 and 2011, respectively. Afterwards, she held a postdoctoral research position at the University of Warwick, England, UK, and a Birmingham Fellowship at the University of Birmingham, England, UK. She is a Lecturer at Aberystwyth University, Wales, UK, since August 2016.%%%Her research focuses on the theoretical analysis of all kinds of randomised search heuristics such as evolutionary algorithms and artificial immune systems with the aim to understand their working principles and guide their design and application. She is also interested in computational and theoretical aspects of natural processes and systems. She has given tutorials on """"Artificial Immune Systems for Optimisation"""" at previous GECCOs and was co-chair of the Artificial Immune Systems track at GECCO 2014, the Artificial Immune Systems and Artificial Chemistries track at GECCO 2015 and Hot off the Press chair at GECCO 2017. She is member of the editorial board of Evolutionary Computation (MIT Press) and was co-organiser of FOGA 2015 and co-workshop chair at PPSN 2016 and 2018. She is a Management Committee member for the UK and working group leader in COST Action CA15140 (Improving Applicability of Nature-Inspired Optimisation by Joining Theory and Practice).
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.
William La Cava, Student Workshop
Harvard Medical School, Boston Children's Hospital | webpage
William La Cava is a faculty member 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.
Marie-Eléonore Kessaci, Women@GECCO
Université de Lille, France | webpage
Marie-Eléonore Kessaci carries out her research in the ORKAD team and she teaches in the department Informatique et Statistique (Computer science and statistics) in the engineering school Polytech Lille. She hold her habilitation (HDR in France), entitled """"Knowledge-based Design of Stochastic Local Search Algorithms in Combinatorial Optimization"""", in November 2019. Between September 2012 and August 2013, she had a postdoctoral position at Université Libre de Bruxelles. She got her PhD in Computer Science in December 2011 at Université Lille 1.
Swetha Varadarajan, Women@GECCO
Colorado State University, United States | webpage
Swetha Varadarajan is a PhD scholar at Colorado State University.
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.
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.