Program Tracks

Xiaodong Li

Xiaodong Li received his B.Sc. degree from Xidian University, Xi'an, China, and Ph.D. degree in information science from University of Otago, Dunedin, New Zealand, respectively. Currently, he is a full professor at the School of Science (Computer Science and Software Engineering), RMIT University, Melbourne, Australia. His research interests include evolutionary computation, neural networks, complex systems, multiobjective optimization, and swarm intelligence. He serves as an Associate Editor of the IEEE Transactions on Evolutionary Computation, Swarm Intelligence (Springer), and International Journal of Swarm Intelligence Research. He is a founding member of IEEE CIS Task Force on Swarm Intelligence, a Vice-chair of IEEE CIS Task Force of Multi-Modal Optimization, and a former Chair of IEEE CIS Task Force on Large Scale Global Optimization. He was the General Chair of SEAL'08, a Program Co-Chair AI'09, and a Program Co-Chair for IEEE CEC’2012. He is the recipient of 2013 ACM SIGEVO Impact Award and 2017 IEEE CIS "IEEE Transactions on Evolutionary Computation Outstanding Paper Award".

Martin Middendorf

He is Professor of Parallel Computing and Complex Systems at the University of Leipzig, Germany. He received the Diploma degree in mathematics and the Dr. rer. nat. degree from the University of Hannover, Germany and the Professoral Habilitation degree from the University of Karlsruhe, Germany. He has worked at the University of Dortmund, Germany and the University of Hannover as a Visiting Professor of Computer Science. He was a Professor of Computer Science at the Catholic University of Eichstätt, Germany. His research interests include nature inspired algorithms, swarm intelligence, bioinformatics, and self-organised systems.

Risto Miikkulainen

Risto Miikkulainen is a Professor of Computer Science at the University of Texas at Austin and a Fellow at Sentient Technologies, Inc. He received an M.S. in Engineering from the Helsinki University of Technology, Finland, in 1986, and a Ph.D. in Computer Science from UCLA in 1990. His recent research focuses on methods and applications of neuroevolution, as well as neural network models of natural language processing, and self-organization of the visual cortex; he is an author of over 370 articles in these research areas. He is an IEEE Fellow, member of the Board of Governors of the Neural Network Society, and an action editor of Cognitive Systems Research and IEEE Transactions on Computational Intelligence and AI in Games.

Emma Hart

Prof. Hart received her PhD from the University of Edinburgh. She currently leads the Centre for Emergent Computing at Edinburgh Napier University where her research focuses on optimisation and continuous learning systems, with an emphasis applying methods from Artificial Immune Systems and HyperHeuristics. She has published extensively in the field of Artificial Immune Systems, with a particular interest in optimisation and self-organising systems such as swarm robotics. Her current interests relate to the development of optimisation algorithms that continuously learn through experience, and how collectives of algorithms can collaborate to form good problem solvers. She also has interests in more theoretical work relating to modelling the immune system to learn more about its computational properties. From January 2017, she will become Editor-in-Chief of Evolutionary Computing, She is also a member of the SIGEVO Executive Board and editor of the SIGEVO newsletter.

Ekart Aniko

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).

Daniele Loiacono

He is an assistant professor at the Dipartimento di Elettronica, Informazione e Bioingegneria (DEIB) of Politecnico di Milano, where he also received his Ph.D. in 2008.
His research interests include machine learning, evolutionary computation, and computational intelligence in games.
Since 2008, he has been organizing several scientific games-related competitions at major conferences including GECCO, CEC and CIG.

Holger Hoos

Holger H. Hoos is a Professor of Computer Science and a Faculty Associate at the Peter Wall Institute for Advanced Studies at the University of British Columbia (Canada). His main research interests span empirical algorithmics, artificial intelligence, bioinformatics and computer music. He is known for his work on the automated design of high-performance algorithms and on stochastic local search methods. Holger is a co-author of the book "Stochastic Local Search: Foundations and Applications", and his research has been published in numerous book chapters, journals, and at major conferences in artificial intelligence, operations research, molecular biology and computer music. Holger was elected a Fellow of the Association for the Advancement of Artificial Intelligence (AAAI) in 2015 and won two prestigious IJCAI/JAIR best paper prizes in 2009 and 2010. He is a past president of the Canadian Artificial Intelligence Association / Association pour l'intelligence artificielle au Canada (CAIAC) and Associate Editor of the Journal of Artificial Intelligence Research (JAIR). Recently, his group has helped UBC to produce better exam timetables, Actenum Inc. to increase production efficiency in the oil and gas industry, and IBM to improve their CPLEX optimisation software, which is used by 50% of the world's largest companies and thousands of universities.

Sébastien Verel

Sébastien Verel is an associate professor in Computer Science at the Université du Littoral Côte d'Opale, Calais, France, since 2013, and previously at the University of Nice Sophia-Antipolis, France, from 2006 to 2013. He received a PhD in computer science from the University of Nice Sophia-Antipolis, France, in 2005. His PhD work was related to fitness landscape analysis in combinatorial optimization. He was an invited researcher in DOLPHIN Team at INRIA Lille Nord Europe, France from 2009 to 2011. His research interests are in the theory of evolutionary computation, multiobjective optimization, adaptive search, and complex systems. A large part of his research is related to fitness landscape analysis. He co-authored of a number of scientific papers in international journals, book chapters, book on complex systems, and international conferences. He is also involved in the co-organization EC summer schools, workshops, a special issue on EMO at EJOR, as well as special sessions in indifferent international conferences.

Mengjie Zhang

Mengjie Zhang is currently Professor of Computer Science at Victoria University of Wellington, where he heads the interdisciplinary Evolutionary Computation Research Group. He is a member of the University Academic Board, a member of the University Postgraduate Scholarships Committee, a member of the Faculty of Graduate Research Board at the University, Associate Dean (Research and Innovation) in the Faculty of Engineering, and Chair of the Research Committee of the Faculty of Engineering and School of Engineering and Computer Science.

His research is mainly focused on evolutionary computation, particularly genetic programming, particle swarm optimisation and learning classifier systems with application areas of feature selection/construction and dimensionality reduction, computer vision and image processing, job shop scheduling, multi-objective optimisation, and classification with unbalanced and missing data. He is also interested in data mining, machine learning, and web information extraction. Prof Zhang has published over 400 research papers in refereed international journals and conferences in these areas.

He has been serving as an associated editor or editorial board member for over ten international journals including IEEE Transactions on Evolutionary Computation, the Evolutionary Computation Journal (MIT Press), IEEE Transactions on Emergent Topics in Computational Intelligence, Genetic Programming and Evolvable Machines (GPEM, Springer), Applied Soft Computing, Natural Computing, and Engineering Applications of Artificial Intelligence, and as a reviewer of over 30 international journals. He is the Tutorial Chair for GECCO 2014 and AIS-BIO Track Co-Chair for GECCO 2016. Since 2012, he has been involving GECCO, CEC, SSCI, EvoStar, SEAL and PAKDD conferences as a general/program/technical/tutorial/track/special session chair. Since 2007, he has been listed as one of the top ten world genetic programming researchers by the GP bibliography (http://www.cs.bham.ac.uk/~wbl/biblio/gp-html/index.html).

Prof Zhang is currently chairing the IEEE CIS Emergent Technologies Technical Committee consisting of over 40 top CI researchers from the five continents and 17 task forces. He is the immediate Past Chair for the IEEE CIS Evolutionary Computation Technical Committee and a member of the IEEE CIS Award Committee. He is also a member of IEEE CIS Intelligent System Applications Technical Committee, a vice-chair of the IEEE CIS Task Force on Evolutionary Feature Selection and Construction, a vice-chair of the Task Force on Evolutionary Computer Vision and Image Processing, and the founding chair of the IEEE Computational Intelligence Chapter in New Zealand.

Will Browne

Will Browne received a BEng Mechanical Engineering, Honours degree from the University of Bath, UK in 1993, MSc in Energy (1994) and EngD (Engineering Doctorate scheme, 1999) University of Wales, Cardiff. After eight years lecturing in the Department of Cybernetics, University of Reading, UK, he was appointed to School of Engineering and Computer Science, Victoria University of Wellington, NZ in 2008. Associate Professor Browne's main area of research is Applied Cognitive Systems. This includes Learning Classifier Systems, Cognitive Robotics, and Modern Heuristics for industrial application. Blue skies research includes analogues of emotions, abstraction, memories, dissonance and machine consciousness. He is an Associate Editor for Neural Computing and Applications, and Applied Soft Computing. He has published over 100 academic papers, including in IEEE Transactions on Evolutionary Computation on scalable learning and two best paper awards in ACM Genetic and Evolutionary Computation Conference.

Tea Tušar

Tea Tušar is a postdoctoral researcher at the Department of Intelligent Systems of the Jožef Stefan Institute in Ljubljana, Slovenia. She received the BSc degree in Applied Mathematics and the MSc degree in Computer and Information Science from the University of Ljubljana. She was awarded the PhD degree in Information and Communication Technologies by the Jožef Stefan International Postgraduate School for her work on visualizing solution sets in multiobjective optimization. She has recently 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.

She was involved in the organization of a number of workshops at previous GECCOs (Student Workshop, Black-Box-Optimization-Benchmarking Workshop and Women@GECCO) and held a tutorial on Visualization in Multiobjective Optimization at GECCO 2016.

Carlos M. Fonseca

Carlos M. Fonseca is an Associate Professor at the Department of Informatics Engineering of the University of Coimbra, Portugal, and a member of the Evolutionary and Complex Systems (ECOS) group of the Centre for Informatics and Systems of the University of Coimbra (CISUC). He graduated in Electronic and Telecommunications Engineering from the University of Aveiro, Portugal, in 1991, and obtained his doctoral degree from the University of Sheffield, U.K., in 1996. His research has been devoted mainly to evolutionary computation and multiobjective optimization. His current research interests include preference articulation in evolutionary multiobjective optimization, experimental assessment of algorithms, evolutionary algorithm dynamics, and engineering-design optimization. He was a General co-Chair of the International Conference on Evolutionary Multi-Criterion Optimization (EMO) in 2003, 2009 and 2013, a Technical co-Chair of the IEEE Congress on Evolutionary Computation (CEC) in 2000 and 2005, and an EMO Track co-Chair of the Genetic and Evolutionary Computation Conference (GECCO) in 2016. He is a founding member of the Evolutionary Multi-Criterion Optimization Steering Committee, and a member of the Portuguese Operations Research Association (APDIO) and of the Portuguese Association of Automatic Control (APCA).

Nikolaus Hansen

Nikolaus Hansen is a research scientist at INRIA, France. Educated in medicine and mathematics, he received a Ph.D. in civil engineering in 1998 from the Technical University Berlin under Ingo Rechenberg. Before he joined INRIA, he has been working in evolutionary computation, genomics and computational science at the Technical University Berlin, the InGene Institute of Genetic Medicine and the ETH Zurich. His main research interests are learning and adaptation in evolutionary computation and the development of algorithms applicable in practice. His best-known contribution to the field of evolutionary computation is the so-called Covariance Matrix Adaptation (CMA).

Marcus Gallagher

Dr Marcus Gallagher is an Associate Professor in the School of Information Technology and Electrical Engineering at the University of Queensland, Brisbane Australia. He was awarded his PhD from the University of Queensland in 2000. His main research interests are in the areas of Optimization, Metaheuristics, Evolutionary Computation and Machine Learning. More specifically, he is interested in the intersections between these areas, including the use of probabilistic models in black-box optimization algorithms (e.g. Estimation of Distribution Algorithms) and using machine learning and data-driven techniques to better understand the nature of optimization problems and algorithms.

Dirk Thierens

Dirk Thierens is affiliated with the Department of Information and Computing Sciences at Utrecht University, the Netherlands, where he is teaching courses on Evolutionary Computation and on Computational Intelligence. He has been involved in genetic algorithm research since 1990. His current research interests are mainly focused on the design and application of model learning techniques to improve evolutionary search. Dirk is (has been) a member of the Editorial Board of the journals Evolutionary Computation, Evolutionary Intelligence, IEEE Transactions on Evolutionary Computation, and a member of the program committee of the major international conferences on evolutionary computation. He was elected member of the SIGEVO ACM board and contributed to the organization of several GECCO conferences: workshop co-chair (2003, 2004), track (co-)chair (2004, 2006, 2014), and Editor-in-Chief (2007).

Alberto Moraglio

Alberto Moraglio is a Lecturer in Computer Science in the College of Engineering, Mathematics and Physical Sciences at the University of Exeter, UK. He has been active in evolutionary computation research for the last 10 years with a substantial publication record in the area. He is the founder of the Geometric Theory of Evolutionary Algorithms, which unifies Evolutionary Algorithms across representations and has been used for the principled design of new successful search algorithms and for their rigorous theoretical analysis. He was co-chair of the Theory Track, the Genetic Programming Track and the Genetic Algorithms Track in past editions of GECCO, co-chair of the European Conference on Genetic Programming, and has regular tutorials at GECCO and IEEE CEC.

Jim Smith

Jim Smith is Professor of Interactive Artificial Intelligence at University of the West of England, from where he received his PhD. in 1998. He has been researching meta­heuristics since 1994, publishing over 100 papers and authoring a best-selling text book on Evolutionary Computation. His research interests include; the theory and application of adaptive and self­ adaptive evolutionary and memetic systems; hybrid algorithms; and the use of interactive artificial intelligence in optimisation and machine learning.
He is a member of the editorial board of the journals including Evolutionary Computation, Applied Soft Computing and Memetic Computing. He has acted as track chair for GECCO in 2011, 2016 and 2017 and was programme chair for Parallel Problem Solving from Nature (PPSN) in 2003 and 2014.

Jürgen Branke

Jürgen Branke is Professor of Operational Research and Systems at Warwick Business School, University of Warwick, UK. He has been an active researcher in the field of Evolutionary Computation for over 20 years, has published over 150 papers in peer-reviewed journals and conferences, resulting in an H-Index of 46 (Google Scholar). His main research interests include optimization under uncertainty, simulation-based optimization and multi-objective optimization. Jürgen is Area Editor for the Journal of Heuristics, and Associate Editor for the Evolutionary Computation Journal and IEEE Transactions on Evolutionary Computation.

Sara Silva

Sara Silva obtained a BSc and MSc in Informatics at the University of Lisbon, and a PhD (2008) in Informatics Engineering at the University of Coimbra, Portugal. Her main research interests are bio-inspired machine learning methods for data mining, like neural networks, genetic algorithms, and particularly genetic programming, which she has applied in several interdisciplinary projects ranging from remote sensing and forest science to epidemiology and medical informatics.

Sara Silva has around 60 peer-reviewed scientific publications, 10 of which distinguished with nominations and international awards. She is a member of the editorial board of the Genetic Programming and Evolvable Machines journal, has been program chair on several international conferences on Evolutionary Computation, and Editor-in-Chief of GECCO in 2015. She is the creator and developer of GPLAB - A Genetic Programming Toolbox for MATLAB.

Zdenek Vasicek

Zdeněk Vašíček is an Assistant Professor and member of Evolvable Hardware Group at Faculty of Information Technology, Brno University of Technology, Czech Republic. His primary research is focused on applications of evolutionary approaches (mainly genetic programming) in areas related to the optimization and synthesis of digital circuits. He (co) authored over 40 papers mainly on evolutionary circuit design and evolvable hardware in FPGAs. His work was awarded with Silver (2011) and Gold (2015) medal at HUMIES.

Anna I Esparcia-Alcázar

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 is a researcher at the PROS Centre of the UPV and an associate lecturer at the Control Department of the same university. She has ample experience both in industry and academia. For the past 10 years she has been actively involved in the organization of the two main conferences in the field of Evolutionary Computation, evostar and GECCO. She is Senior Member of the IEEE and Member of the ACM and was elect member of the Executive Committee of SIGEVO in the period 2009-2015.
In 2015 she was awarded the evo* Award for Outstanding Contribution to Evolutionary Computation in Europe.

Boris Naujoks

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.

Simon Poulding

Simon is an assistant professor in the Software Engineering Research Lab at the Blekinge Institute of Technology in Sweden. His core research interests are search-based software engineering (SBSE), software testing, and the use of principled statistical methods for research in both these areas. Simon has been involved with the SBSE track at GECCO since 2007, and previously chaired the track in 2011. He has also served as both general and program co-chair for the International Symposium on Search-Based Software Engineering (SSBSE), and program co-chair of the International Workshop on Search-Based Software Testing (SBST).

Federica Sarro

Federica is a Senior Research Associate in the CREST centre at University College London, Computer Science Department.
Her main research areas are Empirical Software Engineering and Search Based Software Engineering (SBSE), with a particular interest in predictive modelling for software engineering, software project management, and software quality. She has published over 60 scholarly papers and served more than 40 program committees over the last 6 years. She has also won four international awards for her research in these areas, including the HUMIES-GECCO award in 2016 for her recent work on “Multi-objective Effort Estimation”. She has been member of the Program Committee of the SBSE track at GECCO and of the International Symposium on Search-Based Software Engineering (SSBSE) since 2013. In 2015 she has been elected as member of the Steering Committee for SSBSE and she has also been Program Chair of SSBSE 2016.

Carola Doerr

Carola Doerr (Carola.Doerr@mpi-inf.mpg.de, http://www-ia.lip6.fr/~doerr/) is a CNRS researcher at the Université Pierre et Marie Curie (Paris 6). She studied mathematics at Kiel University (Germany, Diploma in 2007) and computer science at the Max Planck Institute for Informatics and Saarland University (Germany, PhD in 2011). From Dec. 2007 to Nov. 2009, Carola Doerr has worked as a business consultant for McKinsey & Company, mainly in the area of network optimization, where she has used randomized search heuristics to compute more efficient network layouts and schedules. Before joining the CNRS she was a post-doc at the Université Diderot (Paris 7) and the Max Planck Institute for Informatics.

Carola Doerr's research interest is in the theory of randomized algorithms---both in the design of efficient algorithms as well as in finding a suitable complexity theory for randomized search heuristics. After contributing to the revival of black-box complexity, a theory-guided approach to explore the limitations of heuristic search algorithms, she recently started a series of works aimed at exploiting insights from the theory of evolutionary computation to design more efficient EAs, in particular such with a dynamic choice of parameters.

Dirk Sudholt

Dirk obtained his Diplom (Master's) degree in 2004 and his PhD in computer science in 2008 from the Technische Universitaet Dortmund, Germany, under the supervision of Prof. Ingo Wegener. He has held postdoc positions at the International Computer Science Institute in Berkeley, California, working in the Algorithms group led by Prof. Richard M. Karp and at the University of Birmingham, UK, working with Prof. Xin Yao. Since January 2012 he is a Lecturer at the University of Sheffield, UK, leading the newly established Algorithms research group.

His research focuses on the computational complexity of randomized search heuristics such as evolutionary algorithms and swarm intelligence algorithms like ant colony optimization and particle swarm optimization. He is an editorial board member of Evolutionary Computation and Natural Computing and receives funding from the EU's Future and Emerging Technologies scheme (SAGE project). He has more than 70 refereed publications in international journals and conferences, including 8 best paper awards at leading conferences, GECCO and PPSN. He has given 9 tutorials at ThRaSH, WCCI/CEC, GECCO, and PPSN.