Title Organisers

1. Genetic Improvement 2015
more info

- W. B. Langdon (University College, London, UK)
- David R. White (University of Glasgow, UK)
- Justyna Petke (University College, London, UK)

2. SecDef'2015 - Workshop on genetic and evolutionary computation in defense, security and risk management
more info

- Frank W. Moore (University of Alaska Anchorage, USA
- Nur Zincir-Heywood (Dalhousie University, Canada)

3. Workshop on Evolutionary Computation in Computational Structural Biology
more info

- José Santos (University of A Coruña, Spain)
- Julia Handl (University of Manchester, UK)
- Amarda Shehu (Georgia Mason University, US)-

4. 6th Workshop on Visualisation Methods in Genetic and Evolutionary Computation (VizGEC 2015)
more info

- David Walker (University of Exeter, UK)
- Richard Everson (University of Exeter, UK)
- Jonathan Fieldsend (University of Exeter, UK)

5. Evolutionary Rule-based Machine Learning
(former Int. Workshop on Leaning Classifier Systems)
more info

- Karthik Kuber (Microsoft, Redmond, US
- Masaya Nakata (The University of Electro-Communications, Japan)
- Kamran Shafi (University of New South Wales, Australia)

6. 5th Workshop on Evolutionary Computation for the Automated Design of Algorithms (ECADA)
more info

- John Woodward (University of Stirling, UK)
- Daniel Tauritz (Missouri University of Science and Technology, US)
- Manuel López-Ibáñez

7. Workshop on Evolutionary Computation Software Systems (EvoSoft)
more info

- Dr. Stefan Wagner (University of Applied Sciences Upper, Austria)
- Dr. Michael Affenzeller (University of Applied Sciences Upper, Austria)

8. Black Box Optimization Benchmarking 2015 (BBOB 2015)
more info

- Youhei Akimoto (Shinshu University, Japan)
- Anne Auger (INRIA Saclay, France)
- Dimo Brockhoff  (INRIA Lille, France)
- Nikolaus Hansen (INRIA Saclay, France)
- Olaf Mersmann (Technische Universitaet Dortmund, Germany)
- Petr Pošik (Czech Technical University, Prague)

9. GECCO Student workshop
more info

- Tea Tušar (Jozef Stefan Institute, Slovenia)
- Boris Naujoks (Cologne University of Applied Sciences, Germany)

10. Evolving Collective Behaviors in Robotics
more info

- Abraham Prieto (University of A Coruña, Spain)
- Nicolas Bredeche (Universite Pierre et Marie Curie, France)
- Evert Haasdijk (Vrije University, Amsterdam)

11. Women@GECCO
more info

- Carola Doerr (CNRS & Universite Pierre et Marie Curie (Paris 6), France)
- Anna Esparcia (Universitat Politècnica de València, Spain)
- Gabriela Ochoa (University of Stirling, UK)
- Una-May O'Reilly (MIT, USA)
- Dr. Nur Zincir-Heywood (Dalhousie University, Canada)
- Emma Hart (Edinburgh Napier University )
- Christine Zarges (University of Birmingham, UK)

12. 2nd Workshop on Metaheuristic Design Patterns (MetaDeeP)
more info

- Chris Simons (University of the West of England, UK)
- Jerry Swan (University of Stirling, UK)
- Krzysztof Krawiec (Poznan University of Technology, Poland)
- Daniel Tauritz (Missouri University of Science and Technology, US)
- Jim Smith (University of the West of England, UK)

13. Automatically Configurable Algorithmic Frameworks


14. Semantic Methods in Genetic Programming (SMGP)
more info

- Colin Johnson (University of Kent, UK)
- Krzysztof Krawiec (Poznan University of Technology, Poland)
- Alberto Moraglio (University of Exeter, UK)
- Michael O’Neill (University College Dublin, Ireland)

15. Evolutionary Computation for Big Data and Big Learning


16. Medical Applications of Genetic and Evolutionary Computation (MedGEC)
more info

- Stephen L. Smith (University of York, UK)
- Stefano Cagnoni (Universita' degli Studi di Parma, Italy)
- Robert M. Patton, (Oak Ridge National Laboratory, USA)

17. 9th Workshop on Evolutionary Computation and Multi-Agent Systems and Simulation (ECoMASS)




1.-Genetic Improvement 2015


Lately there has been enormous interest in the use of evolutionary and genetic search in optimising aspects of software engineering. For example, since 2002 there has been an SBSE track at GECCO. More recently there is a dedicated SSBSE conference. Indeed we now see regional conferences and workshops featuring or even dedicated to Search Based Software Engineering starting (in China, Brazil and now the USA). Including to appear, since 2000, there have been more than 70 papers in this area and interest is growing. Since 2009 there have been three human competitive awards (Gold, Silver and Bronze) presented at GECCO and two best papers, including the International Conference on Software Engineering and GECCO.
Whilst SBSE has traditionally been applied to software engineering problems there has been great interest in using it, particularly genetic programming, on software itself.
Genetic Improvement (GI) is the application of evolutionary and search-based optimisation methods to the improvement of existing software. The technique was first applied to optimise and find compromises between non-functional properties of software, such as execution time and power consumption. This work lead on to automated bug fixing in commercial software. More recently, it has been shown that GP can use human written software as a feed stock for GP and is able to evolve mutant software dedicated to solving particular problems. Another interesting area is grow and graft GP, where software is incubated outside its target human written code and subsequently grafted into it via GP. 


William B. Langdon
William B. Langdon has been working with genetic programming since 1993. His current research uses GP to genetically improve existing software, CUDA, search based software engineering and Bioinformatics. Indeed GI has been used to significantly improve a widely used bioinformatics tool, nVidia software running on graphics hardware and a GPU kernel for NMR medical imaging registration. He co-organised the computational intelligence on GPUs (CIGPU) series of workshops, the first EvoPAR track in the European conference on applications of evolutionary computation and last year was co-chair of the GECCO genetic programming track. 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.


David R. White
He is a researcher in the School of Computing Science at the University of Glasgow. He published some of the seminal papers on both creating new and improving existing software with respect to non-functional improvement, and his subsequent thesis was nominated for a BCS distinguished thesis award. He then worked as a SICSA Research Fellow at the University of Glasgow, before joining the EPSRC AnyScale project. He is on the steering committee of SSBSE and has won two best paper awards for work in evolutionary search.


Justyna Petke
Dr. Petke has a DPhil in Computer Science from University of Oxford and is now at the Centre for Research on Evolution, Search and Testing (CREST) in University College, London. She has published applications of genetic improvement. One of her recent papers was awarded a HUMIE at this year's GECCO in Vancouver. Dr. Petke is co-organising the First North American Search Based Software Engineering Symposium (to be held in February). 


2- SecDef'2015 - Workshop on genetic and evolutionary computation in defense, security and risk management

With the constant appearance of new threats, research in the areas of defense, security and risk management has acquired an increasing importance over the past few years. These new challenges often require innovative solutions and Computational Intelligence techniques can play a significant role in finding them. The workshop invites completed or ongoing work, with the aim to encourage communication between active researchers and practitioners to better understand the current scope of efforts within this domain. The ultimate goal is to understand, discuss, and help set future directions for computational intelligence in security and defense problems.

We seek both theoretical developments and applications of Genetic and Evolutionary Computation and their hybrids to the following (and other related) topics:

  • Cyber crime and cyberdefense : anomaly detection systems, attack prevention and defense, threat forecasting systems, anti spam, antivirus systems, cyber warfare, cyber fraud  
  • IT Security: Intrusion detection, behavior monitoring, network traffic analysis
  • Corporate security, with special focus on BYOD policies and usability of security
  • Risk management: identification, prevention, monitoring and handling of risks, risk impact and probability estimation systems, contingency plans, real time risk management
  • Critical Infrastructure Protection (CIP)
  • Advanced Persistent Threats (APTs)
  • Design of military systems and sub-systems.
  • Logistics and scheduling of military operations.
  • Strategic planning and tactical decision making. 
  • Multiobjective techniques for examining tradeoffs in military, security, and counter-terrorism procedures.
  • Automated discovery of tactics and procedures for site security, force protection, and consequence management.
  • Other computational intelligence techniques for applications in the areas listed above.

Frank Moore
He is Professor and Chair of the Computer Science & Engineering at the University of Alaska Anchorage. He has taught computer science and engineering for the past 17 years. He also has over six years of industry experience developing software for a wide range of military projects. His recent NASA-funded research (patent pending) used evolutionary computation to optimize transforms that outperform wavelets for lossy image compression and reconstruction. He has received over $750,000 in research funding and has published over 80 technical papers and reports. Dr. Moore is a Senior Member of ACM and a Member of IEEE.


Nur Zincir-Heywood
Dr. Nur Zincir-Heywood is a Professor of Computer Science at Dalhousie University, Canada. She received her PhD in 1998 in Computer Science and Engineering from Ege University, Turkey. Prior to moving to Dalhousie in 2000, Dr. Zincir-Heywood had been a researcher at Sussex University, UK and Karlsruhe University, Germany as well as working as an instructor at the Internet Society Network Management workshops. She has published over 150 papers in network management, security , information systems and computational intelligence fields. She has substantial experience of industrial research in systems security and network management related topics with Raytheon, RUAG, Gtech, Palomino, Genieknows, and Public Safety Canada. Dr. Zincir-Heywood is a member of the IEEE and ACM.



3- Workshop on Evolutionary Computation in Computational Structural Biology


In the last two decades, many computer scientists in Artificial Intelligence have made significant contributions to modeling biological systems as a means of understanding the molecular basis of mechanisms in the healthy and diseased cell. In particular, the field of computational structural biology is now highly populated by researchers in evolutionary computation. Great progress is being made by these researchers on novel and powerful algorithms to solve exceptionally challenging computational structural biology problems at the heart of molecular biology, such as structure prediction, analysis, and design of biological macromolecules (proteins, RNA). These problems pose difficult search and optimization tasks on modular systems with vast, high-dimensional, continuous search spaces often underlined by non-linear multimodal energy surfaces.
The focus of this workshop is the use of nature-inspired approaches to central problems in computational structural biology, including optimization methods under the umbrella of evolutionary computation. A particular emphasis will be on progress in the application of evolutionary computation to problems related to any aspects of protein structure modeling, characterization, and analysis. The workshop will allow for a broader focus on all structure-related problems that necessitate the design of novel evolutionary computation approaches. These may include broader structure modeling settings beyond de novo structure prediction, such as mapping of protein and peptide energy landscapes, structure analysis, design, docking, and other emerging problems in computational structural biology.
One of the objectives of this workshop is to aid evolutionary computation researchers to disseminate recent findings and progress. The workshop will provide a meeting point for authors and attendants of the GECCO conference who have a current or developing interest in computational biology. We believe the workshop will additionally attract computational biology researchers that will further add to the attendance and GECCO community and possibly spur novel collaborations. We hope this workshop will stimulate the free exchange and discussion of novel ideas and results related to structure-central problems bridging computational biology and evolutionary computation.

Areas of interest include (but are not restricted to):

  • Use of artificial life models like cellular automata or Lindenmayer systems in the modeling of biological problems.
  • Study and analysis of properties of biological systems like self-organization, emergent behavior or morphogenesis.
  • Multi-objective approaches in the modeling of computational biology problems.
  • Use of natural and evolutionary computation algorithms in protein structure classification and prediction (secondary and tertiary).
  • Mapping of protein and peptide energy landscapes.
  • Modeling of temporal folding of proteins.
  • Protein design
  • Protein-ligand and protein-protein docking.

José Santos
He obtained an MS degree in Physics (specialization in Electronics) from the University of Santiago de Compostela, Spain, in 1989, and a Ph.D. from the same University in 1996 (specialization in Artificial Intelligence). He is currently an Associate Professor, accredited as Full Professor, in the Department of Computer Science at the University of A Coruña (Spain). His research interests include artificial life, neural computation, evolutionary computation, autonomous robotics and computational biology. In the last years his research was focused on computational biology, applying all the knowledge acquired in the other research lines to the computational modeling of biological problems.

Julia Handl
She obtained a Bsc (Hons) in Computer Science from Monash University in 2001, an MSc degree in Computer Science from the University of Erlangen-Nuremberg in 2003, and a PhD in Bioinformatics from the University of Manchester in 2006. From 2007 to 2011, she held an MRC Special Training Fellowship at the University of Manchester, and she is now a Lecturer in the Decision and Cognitive Sciences Group at the Manchester Business School. Her research includes theoretical and empirical work related to the development and use of data-mining and optimization approaches in a variety of application areas including computational biology. She has a particular interest in improving the optimization approaches employed in fragment-assembly approaches to protein structure.

Amarda Shehu
Dr. Shehu is an Associate Professor in the Department of Computer Science at George Mason University. She holds affiliated appointments in the School of Systems Biology and the Department of Bioengineering. She received her B.S. in Computer Science and Mathematics from Clarkson University in Potsdam, NY in 2002 and her Ph.D. in Computer Science from Rice University in Houston, TX in 2008, where she was an NIH fellow of the Nanobiology Training Program of the Gulf Coast Consortia. Shehu's research contributions are in computational structural biology, biophysics, and bioinformatics with a focus on issues concerning the relationship between biomolecular sequence, structure, dynamics, and function. Her research on probabilistic search and optimization algorithms for protein structure modeling is supported by various NSF programs, including Intelligent Information Systems, Computing Core Foundations, and Software Infrastructure. Shehu is also the recipient of an NSF CAREER award in 2012.


4- 6th Workshop on Visualisation Methods in Genetic and Evolutionary Computation (VizGEC 2015)

VizGEC is intended to explore, evaluate and promote current visualisation developments in the area of genetic and evolutionary computation (GEC). Visualisation is a crucial tool in this area, providing vital insight and understanding into algorithm operation and problem landscapes as well as enabling the use of GEC methods on data mining tasks. As well as allowing us to observe how individuals interact, visualising the evolution of a synthetic genetic population over time facilitates the analysis of how individuals change during evolution, allowing the observation of undesirable traits such as premature convergence and stagnation within the population. 

In addition to visualising the solutions generated by a GEC process, we can also visualise the processes themselves. It can be useful, for example, to investigate which evolutionary operators are most commonly applied by an algorithm, as well as how they are applied, in order to gain an understanding of how the process can be most effectively tuned to solve the problem at hand.  Advances in animation and the prevalence of digital display, rather than relying on the paper-based presentation of a visualisation, mean that it is possible to use visualisation methods so that aspects of an algorithm's performance can be evaluated online.


David Walker            
He is an Associate Research Fellow with the College of Engineering, Mathematics and Physical Sciences at the University of Exeter.  The focus of his PhD was the understanding of many-objective populations.  A principal component of his thesis involved visualising such populations and he is particularly interested in how evolutionary algorithms can be used to enhance visualisation methods.  More recently, his research has investigated evolutionary methods for the data mining of many-objective populations, as well as for training artificial neural networks and designing novel nanomaterials.  His general research interests include visualisation, evolutionary problem solving, particularly machine learning problems, techniques for identifying preference information in data and visualisation methods.

Richard Everson
He is Professor of Machine Learning at the University of Exeter.   He has a degree in Physics from Cambridge University and a PhD in Applied Mathematics from Leeds University.  He worked at Brown and Yale Universities on fluid mechanics and data analysis problems until moving to Rockefeller University, New York, to work on optical imaging and modelling of the visual cortex. After working at Imperial College, London, he joined the Computer Science department at Exeter University. His research interests lie in statistical pattern recognition, multi-objective optimisation and the links between them.  Recent interests include the optimisation of the performance of classifiers, which can be viewed as a many-objective optimisation problem requiring novel methods for visualisation. Research on the construction of league tables has led to publications exploring the multi-objective nature and methods of visualising league tables.

Jonathan Fieldsend
He is Senior Lecturer in Computer Science 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 held postdoctoral positions as a research fellow (working on the interface of Bayesian modelling and optimisation) and as a business fellow (focusing on knowledge transfer to industry) prior to his appointment to an academic position at Exeter. His research interests include multi- and many-objective optimisation, machine learning and statistical pattern recognition and the interface between these areas. Work in these fields has led to an interest in visualisation, which in turn has led to peer reviewed work on the application and comparison of existing visualisation techniques to new domains, and the investigation of novel visualisation techniques. He has been active within the evolutionary computation community as a reviewer and program committee member since 2003.


5- Evolutionary Rule-based Machine Learning
(former Int. Workshop on Leaning Classifier Systems)

Learning Classifier Systems (LCSs), introduced by John Holland [1] as a way of combining evolutionary computation with machine learning, have been widely applied from data mining to automated innovation and on-line control. LCSs have been an integral part of the field of evolutionary computation almost since its very beginnings, and so this workshop is very interesting not only for the Genetic and Evolutionary Computation (GEC) community, but also because it shares many common research topics with the broader GEC field such as linkage learning, niching techniques, variable-length representations, etc.

Scopes of interests include but are not limited to:

  • Paradigms of LCS (Michigan, Pittsburgh, ...)
  • Theoretical developments (behavior, scalability and learning bounds, ...)
  • Representations (binary, real-valued, oblique, non-linear, fuzzy, ...)
  • Types of target problems (single-step, multiple-step, regression/function 
approximation, ...)
  • System enhancements (competent operators, problem structure 
identification and linkage learning, ...)
  • LCS for Cognitive Control (architectures, emergent behaviors, ...)
  • Applications (data mining, medical domains, bioinformatics, intelligence in 
games ...)
  • Optimizations and parallel implementations (GPU, matching algorithms, ...)

Karthik Kuber
He received his PhD in 2014 from Syracuse
University in Computer Science. His dissertation research was
on studying evolutionary algorithms from a network perspective, mainly focusing on Genetic Algorithms, Particle Swarms, and Learning Classifier Systems. He worked on information theoretic fitness measures for Learning Classifier Systems during his MS thesis, also at Syracuse. Prior to graduate school, he worked at Tata Consultancy Services in Bangalore, and received a BE in Electronics and Communication Engineering from Visvesvaraya Technological University. He is currently working at Microsoft where his interests are in exploring and applying various machine learning, analysis and modelling techniques in the context of large-scale engineering systems.


Masaya Nakata
Mr. Nakata received the B.A. and M.Sc. degrees in informatics from the University of Electro- Communications, Chofu, Tokyo, Japan, in 2011 and 2013 respectively. He is the Ph.D. candidate in the University of Electro- Communications, the research fellow of Japan Society for the Promotion of Science, Chiyoda-ku, Tokyo, Japan, and a visiting student of the School of Engineering and Computer Science in Victoria University of Wellington from 2014. He was a visiting student of the Department of Electronics and Information, Politecnico di Milano, Milan, Italy, in 2013, and of the Department of Computer Science, University of Bristol, Bristol, UK, in 2014. His research interests are in evolutionary computation, reinforcement learning, data mining, more specifically, in learning classifier systems. He has received the best paper award and the IEEE Computational Intelligence Society Japan Chapter Young Researcher Award from the Japanese Symposium of Evolutionary Computation 2012. He is a co-organizer of International Workshop on Learning Classifier Systems (IWLCS) for 2015-2016.

Kamran Shafi
Dr. Shafi holds a PhD in computer science, a M.Sc. in telecoms engineering and a B.Sc. in electrical engineering. Dr. Shafi is the organising member (elected) for the International Workshop on Learning Classifier Systems (IWLCS) 2013-14 and 2015-16. He was the chair of Computational Intelligence Day workshop held at the University of New South Wales (UNSW-Canberra) Australia in September 2013. He was the publicity chair for the 2012 World Congress on Computational Intelligence (WCCI 2012). He has been a program committee member and chair/co-chair of several workshops at GECCO and IEEE CEC conferences since 2005. His PhD thesis “An online and adaptive signature-based approach for intrusion detection using learning classifier systems (LCS)” received the Stephen Fester Award for the most outstanding thesis on an information technology topic by a postgraduate research student in the School of ITEE at UNSW Canberra. His other major research achievements in the field of LCS research include the development of an LCS based scenario mining approach in the context of free- flight air traffic control concept and development of an LCS based multi-objective hyper-heuristic framework for the defence logistics problem.


6- 5th Workshop on Evolutionary Computation for the Automated Design of Algorithms (ECADA)

How can we automatically generate algorithms on demand? While this was one of the original aims of Machine Learning and Artificial Intelligence in the early 1950s, and more recently Genetic Programming in the early 1990s, existing techniques have fallen-short of this elusive goal. This workshop will outline a number of steps in the right direction on the path to achieving this goal. In particular, this workshop will focus on the burgeoning field of hyper-heuristics which are meta-heuristics applied to a space of algorithms; i.e., any method of sampling a set of candidate algorithms. Genetic Programming has most famously been employed to this end, but random search and iterative hill-climbing have both also successfully been employed to automatically design novel (components of) algorithms. 

The main objective of this workshop is to discuss hyper-heuristics employing evolutionary computation methods for generating algorithms. These methods have the advantage of producing solutions that are applicable to any instance of a problem domain, instead of a solution specifically produced to a single instance of the problem. The areas of application of these methods include, for instance, data mining, machine learning, and optimization.


John R. Woodward
He is a lecturer at the University of Stirling, within the CHORDS group ( and is employed on the DAASE project (, and for the previous four years was a lecturer with the University of Nottingham. He holds a BSc in Theoretical Physics, an MSc in Cognitive Science and a PhD in Computer Science, all from the University of Birmingham. His research interests include Automated Software Engineering, particularly Search Based Software Engineering, Artificial Intelligence/Machine Learning and in particular Genetic Programming.  He has over 50 publications in Computer Science, Operations Research and Engineering which include both theoretical and empirical contributions, and given over 100 talks at International Conferences and as an invited speaker at Universities. He has worked in industrial, military, educational and academic settings, and been employed by EDS, CERN and RAF and three UK Universities.


Daniel R. Tauritz
He is an Associate Professor in the Department of Computer Science at the Missouri University of Science and Technology (S&T), on sabbatical at Sandia National Laboratories for the 2014-2015 academic year, a former Guest Scientist at Los Alamos National Laboratory (LANL), the founding director of S&T's Natural Computation Laboratory (, and founding academic director of the LANL/S&T Cyber Security Sciences Institute. He received his Ph.D. in 2002 from Leiden University for Adaptive Information Filtering employing a novel type of evolutionary algorithm. He served previously as GECCO 2010 Late Breaking Papers Chair, COMPSAC 2011 Doctoral Symposium Chair, GECCO 2012 GA Track Co-Chair, and GECCO 2013 GA Track Co-Chair. For several years he has served on the GECCO GA track program committee, the Congress on Evolutionary Computation program committee, and a variety of other international conference program committees. His research interests include the design of hyper-heuristics and self-configuring evolutionary algorithms and the application of computational intelligence techniques in cyber security, critical infrastructure protection, and search-based software engineering. He was granted a US patent for an artificially intelligent rule-based system to assist teams in becoming more effective by improving the communication process between team members.


Manuel López-Ibáñez
Dr. López-Ibáñez is a postdoctoral researcher (Chargé de recherche) of the Belgian Fund for Scientific Research (F.R.S.-FNRS) working at the IRIDIA laboratory of Université libre de Bruxelles, Brussels, Belgium. He received the M.S. degree in computer science from the University of Granada, Granada, Spain, in 2004, and the Ph.D. degree from Edinburgh Napier University, U.K., in 2009. He has published 13 journal papers, 6 book chapters and 33 papers in peer-reviewed proceedings of international conferences on diverse topics such as evolutionary algorithms, ant colony optimisation, multi-objective optimisation, and various combinatorial and real-world optimisation problems. His current research interests are experimental analysis, automatic configuration and automatic design of optimisation algorithms, for single and multi-objective optimisation. He is the lead developer and current maintainer of the irace automatic configuration method (



7- Workshop on Evolutionary Computation Software Systems (EvoSoft)

Evolutionary computation (EC) methods are applied in many different domains. Therefore soundly engineered, reusable, flexible, user-friendly, and interoperable software systems are more than ever required to bridge the gap between theoretical research and practical application. However, due to the heterogeneity of the application domains and the large number of EC methods, the development of such systems is both, time consuming and complex. Consequently many EC researchers still implement individual and highly specialized software which is often developed from scratch, concentrates on a specific research question, and does not follow state of the art software engineering practices. By this means the chance to reuse existing systems and to provide systems for others to build their work on is not sufficiently seized within the EC community. In many cases the developed systems are not even publicly released, which makes the comparability and traceability of research results very hard.

This workshop enables EC researchers to exchange their ideas on how to develop and apply generic and reusable EC software systems and to present open and freely available solutions on which others can build their work on. Furthermore, the workshop should help to identify common efforts in the development of EC software systems and should highlight cooperation potentials and synergies between different research groups. It concentrates on the importance of high-quality software systems and professional software engineering in the field of EC and provides a platform for EC researchers to discuss the following and other related topics:

  • development and application of generic and reusable EC software systems
  • architectural and design patterns for EC software systems
  • software modeling of EC algorithms and problems
  • open-source EC software systems
  • expandability, interoperability, and standardization
  • comparability and traceability of research results
  • graphical user interfaces and visualization
  • comprehensive statistical and graphical results analysis
  • parallelism and performance
  • usability and automation
  • comparison and evaluation of EC software systems

Stefan Wagner
He received his MSc in computer science in 2004 and his PhD in technical sciences in 2009, both from the Johannes Kepler University Linz, Austria. From 2005 to 2009 he worked as an associate professor for software project engineering and since 2009 as a full professor for complex software systems at the University of Applied Sciences Upper Austria, Campus Hagenberg, Austria. Dr. Wagner is one of the founders of the research group Heuristic and Evolutionary Algorithms Laboratory (HEAL) and is the project manager and head developer of the HeuristicLab optimization environment.


Michael Affenzeller
He has published several papers, journal articles and books dealing with theoretical and practical aspects of evolutionary computation, genetic algorithms, and meta-heuristics in general. In 2001 he received his PhD in engineering sciences and in 2004 he received his habilitation in applied systems engineering, both from the Johannes Kepler University Linz, Austria. Michael Affenzeller is professor at the University of Applied Sciences Upper Austria, Campus Hagenberg, and head of the research group Heuristic and Evolutionary Algorithms Laboratory (HEAL).



8- Black Box Optimization Benchmarking 2015 (BBOB 2015)

Benchmarking of optimization algorithms is crucial to assess performance of optimizers quantitatively, understand weaknesses and strengths of each algorithm and is the compulsory path to test new algorithm designs. The black-box-optimization benchmarking workshop aims at benchmarking both stochastic and deterministic continuous optimization algorithms in an anytime scenario for (i) unconstrained optimization problems and (ii) possibly in expensive settings where only a limited budget is affordable (e.g. (meta-)model assisted algorithms).


Youhei Akimoto
He is an assistant professor at Shinshu University, Japan. He received his diploma (2007) in computer science and his master degree (2008) and PhD (2011) in computational intelligence and systems science from Tokyo Institute of Technology, Japan. He was a research fellow of Japan Society for the Promotion of Science for one year (2010-2011) at Tokyo Institute of Technology. Afterwords, he was a post-doctoral research fellow at INRIA Saclay Ile-de-France (2011-2013) and started working at Shinshu University in April 2013. His research interests include design principles and theoretical analysis of stochastic search heuristics, especially the Covariance Matrix Adaptation Evolution Strategy.


Anne Auger
She is a permanent researcher at the French National Institute for Research in Computer Science and Control (INRIA). 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 and algorithm designs. She is a member of ACM-SIGECO executive committee and of the editorial board of Evolutionary Computation. She has been organizing the biannual Dagstuhl seminar "Theory of Evolutionary Algorithms" in 2008 and 2010 and the BBOB workshops in 2009, 2010, 2012, and 2013.


Dimo Brockhoff
He received his diploma in computer science from University of Dortmund, Germany in 2005 and his PhD (Dr. sc. ETH) from ETH Zurich, Switzerland in 2009. Afterwards, he held two postdoctoral research positions in France at INRIA Saclay Ile-de-France (2009-2010) and at Ecole Polytechnique (2010-2011). Since November 2011, he has been a permanent researcher at INRIA Lille - Nord Europe, France. His research interests are focused on evolutionary multiobjective optimization (EMO), in particular on theoretical aspects of indicator-based search and on the benchmarking of blackbox algorithms in general. Dimo already served as co-organizer of the BBOB workshop in 2013.


Nikolaus Hansen
He 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).


Olaf Mersmann
He recieved his BSc and MSc in Statistics from the TU Dortmund. He is currently pursuing a PhD in Statistics (expected in early 2015) with work based on his Bachelor Thesis on the design and analysis of benchmark experiments. Part of this work has been presented at conferences and is currently under review for publication. Using statistical and machine learning methods on large benchmark databases to gain insight into the structure of the algorithm choice problem is one of his current research interests. Olaf already co-organized the BBOB workshop in 2010 and 2012.

Petr Pošik
He received his Diploma degree in Technical Cybernetics in 2001 and Ph.D. in Artificial Intelligence and Biocybernetics in 2007, both from the Czech Technical University in Prague, Czech Republic. From 2001 to 2004 he also worked as statistician, analyst and lecturer for StatSoft, Czech Republic. Since 2005 he works as a researcher in the Intelligent Data Analysis Lab, Department of Cybernetics at the Czech Technical University. Being on the boundary of optimization, statistics and machine learning, his research interests are aimed at improving the characteristics of evolutionary algorithms with techniques of statistical machine learning. He also serves as a reviewer for several journals and conferences in the evolutionary-computation field.


9- GECCO Student workshop

The goal of the Student Workshop is to support students’ first research and facilitate their inclusion in the field of Evolutionary Computation. Students will receive valuable feedback on the quality of their work and their presentation style. This will be assured by constructive discussions after each talk led by a mentor panel of established researchers. Students are encouraged to use this opportunity also to get guidance regarding future research directions. In addition, the contributing students are invited to present their work as a poster at the GECCO 2015 Poster Session - an excellent opportunity to discuss their work with a broader audience and to network with academic as well as industrial members of the community. Last, but not least, the best contributions will compete for a Best Student Paper Award.


Tea Tušar
She is a research assistant at the Department of Intelligent Systems at the Jožef Stefan Institute in Ljubljana, Slovenia. She received her PhD degree from the Jožef Stefan International Postgraduate School in 2014. Her research interests include evolutionary algorithms for singleobjective and multiobjective optimization with applications in optimization of metallurgical production processes and design of alternative energy supply systems, and machine learning methods for text processing and outlier detection. Recently, she has been researching visualization techniques for viewing multidimensional Pareto front approximations found by multiobjective optimizers.


Boris Naujoks
He is a professor for Applied Mathematics at 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 focused on multiobjective (evolutionary) optimization, in particular hypervolume based algorithms, and the (industrial) applicability of the explored methods.



10- Evolving Collective Behaviors in Robotics

This workshop brings together researchers interested in the automatic design of coordinated behaviors in decentralized collective systems, putting the emphasis on evolutionary robotics techniques. The goal of this workshop is to provide an updated perspective of this field, both from a theoretical and practical perspective, and to consider different areas of applicability for such techniques including design for engineering and modelling for biology. Moreover, this workshop will encourage collaboration between researchers already present at GECCO, or in other similar venues such as the Artificial Life conferences, which are not always present at the same conference.


Abraham Prieto Garcia
He is an Associate Professor at the University of A Coruña, Spain. He is a member of the Integrated Group for Engineering Research (GII) of the same university and leads the Collective Systems Section within the GII. He graduated in 2002 and obtained his Master Degree in 2004 in Industrial Engineering. In 2009 he obtained a Magna Cum Laude for his PhD Thesis in the field of optimization techniques for distributed problems in engineering. He started his collaboration with the GII in 2004 developing projects related with Intelligent Processing of images and signals and with the optimization of distributed systems. In 2005 he became Assistant Professor and then in 2010 he gained the Associate Professor position. Regarding his research work he is author of several papers in journals, international conferences and book chapters. He has participated in numerous national and regional research projects from public calls, many of them in collaboration with private companies. His research covers the following fields: bio-inspired techniques for distributed problems, evolutionary robotics and image and signal intelligent processing.

Nicolas Bredeche
He is Professeur des Universites (Professor) at Universite Pierre et Marie Curie (UPMC, Paris, France), His research is done in the team Architectures and Models for Adaptation and Cognition, within the Institute of Intelligent Systems and Robotics (ISIR, CNRS). His field of research is mostly concerned with Evolutionary Computation and Complex Systems (self-adaptive collective robotic systems, generative and developmental systems, evolutionary robotics). In particular, part of his work is about (a) evolutionary design and/or adaptation of group of embodied agents and (b) artificial ontogeny such as multi-cellular developmental systems and self-regulated networks.

Nicolas Bredeche is author of more than 30 papers in journals and major conferences in the field. He has (or currently is) advisor or co-advisor of six PhD students and has served in program committees and/or as track chair of the major conferences in the field of Evolutionary Computation (incl. GECCO track chair for the Artificial Life and Robotics track 2012/2013). He is also a member of the french Evolution Artificielle association and has been regularly co-organizing the french Artificial Evolution one-day seminar (JET) since 2009. He has also organized several international workshops in Evolution, Robotics, and Development of Artificial Neural Networks.


Evert Haasdijk
He is assistant professor in the Computational Intelligence group at VU. He has been with the computational intelligence group at VU since 2008, researching on-line evolution in robots. Before that, he was research assistant at Tilburg University, researching social learning in populations of software agents. Dr Haasdijk has ample experience in evolutionary computation, stretching back to the successful PAPAGENA project in 1992, where he participated as an industry partner. He has served as member of program committees of well-established conferences in the field of evolutionary computation (CEC, GECCO), was local chair for GECCO 2013 and (co-)organised various workshops and track such as the EvoROBOT track at EvoSTAR conferences and the International Workshop on the Evolution of Physical Systems at ECAL and ALIFE conferences. Dr Haasdijk was guest editor for the Special Issue on Evolutionary Robotics of the Evolutionary Intelligence journal and invited speaker at the PPSN XIII Workshop on Nature-Inspired Techniques for Robotics.


11- Women@GECCO

Workshop: Sunday July 12, 16:10-18:00
Panel:  Sunday July 12, 18:00 - 19:30

Women form an under-represented cohort in evolutionary computation, whether the cohort is examined in industry, academics or both. The broad objective of this workshop is bring women attending GECCO together to share ways that will generate, encourage and support academic, professional and social opportunities for women in evolutionary computation.  The workshop will foster, sustain and impart role models and offer the opportunity to interact with others “in the same boat”. We encourage all faculty, professional and students interested in Evolutionary Computation who identify as female, who consider themselves underrepresented minorities with similar issues, or are male and supportive of the issues to attend.


  • Introduction of Workshop and Participants
  • Invited talk by Emma Hart on "Lifelong Learning: An Academic & Personal Perspective" (please find details below)
  • Open Discussion
  • Science Slam: short performances of our 5 selected speakers: Tea Tusar, Madalina Drugan, Julia Handl, Amarda Shehu, and Arina Buzdalova
  • "Poster Session" (please find details below)

*Invited Talk*

Title:  Lifelong Learning: An Academic &  Personal Perspective  -  Emma Hart

My current research focuses on  developing algorithms that continuously learn and improve through  the experience gained from solving many problems over time. In this talk, I will discuss some of the scientific ideas behind this research, but also describe the process of arriving at this point in my academic life, through a journey that has involved life-long learning on my own part, moving from Chemistry to Evolutionary Computing to Artificial Immune Systems to something that brings together all three fields in naby  respects.

Emma Hart gained a 1st Class Honours Degree in Chemistry from the University of Oxford, followed by an MSc in Artificial Intelligence from the University of Edinburgh in 1996. Her PhD, also from the University of Edinburgh, explored the use of immunology as an inspiration for computing, examining a range of techniques applied to optimisation and data classification problems.

She moved to Edinburgh Napier University in 2000 as a lecturer, and was promoted to a Chair in 2008 in Natural Computation. She leads the Centre for Algorithms, Visualisation and Evolving Systems with the Institute for Informatics&  Digital Innovation at Edinburgh Napier. Her research focuses on the development of novel bio-inspired techniques for solving a range of real-world optimisation and classification problems, as well as exploring the fundamental properties of immune-inspired computing through modelling and simulation. Her current research interests are focused on systems that can continue learning over their lifetime, with applications in optimisation and robotics. This brings together keys ideas from the AIS and Evolutionary Computing communities. In addition to academic research, she is also involved in Knowledge Transfer and Commercial activities, applying her research to real problems in industry.

* Open Discussion*
Our workshops have recently also included an open discussion on issues reflective of the community, such as:

  • What will help women in evolutionary computation remain in the field long term?
  • What are the different challenges along a career path?
  • What strategies will help women navigate career and family responsibilities?
  • What changes can be adopted by women as a group, by our larger community with respect to our conferences and awards, or by our academic institutions with respect to positions and promotions?
  • Are there experiences and strategies that can be shared which allow senior women to support more junior ones or peers to support each other?
  • What can women in EC do to help each other’s isolation because of under-representation?

*Science Slam*
Short performances of our 5 selected speakers: Tea Tusar, Madalina Drugan, Julia Handl, Amarda Shehu, and Arina Buzdalova, who will talk about their research in a creative and non-standard way.

*Poster Session*
We invite all participants to bring along material to introduce themselves (e.g., a poster or a printout of one or two slides, but feel free to bring other items such as pictures or paintings, the topic is entirely up to you (we suggest to have some details about your research ambitions/future or completed projects/... but feel free to add some comments about your private/personal situation if you are happy to share these things). This interactive session will allow us to get to know each other better. Please do not overload your poster/picture/... as time for the presentation will be limited. Please be aware that the posters might be visible to general GECCO attendees. So you should keep this in mind and only add things you are comfortable sharing.

Use this opportunity to present your work in an open, enthusiastic, and welcoming environment.
Let us know which topics motivate your work and share with us your progress on this journey as well as open questions arising from your work. The poster session is a great opportunity to connect to fellow researchers in evolutionary computation. Take advantage and get useful feedback on your work. More importantly, make yourself and your research topics known!

*Panel Discussion *
Sunday July 12, 18:00 - 19:30
We started a "conversation" on work/life balance at the panel last year. This year, we want to continue that "conversation" and dive into discussing how each one of us work to combine a successful career with a rich private life. Because a balanced life is something that looks different for everyone, we want to hear from you:

  • what makes you feel like your life is in balance or out of balance?
  • what takes up most of your time?
  • do you feel anything is lacking?
  • what are the challenges at work?
  • what would you like to see changing?

This year's work/life balance panel encourages everyone to join us and take a more active role in our panel.  We want to invite everyone at different stages of their career from students, to early career participants, to more senior ones! If you have any topics that you would like to see discussed in this panel, please do not hesitate to contact the organizers Emily Dolson , Anya E. Johnson , and Nur Zincir-Heywood.

*Your Participation*
No submission is required to attend this quarter-day workshop however you should indicate your attendance at GECCO registration. Participants are strongly encouraged to bring along material for the poster session.  For more information, contact including on the subject line: WOMEN@GECCO.

Carola Doerr
Carola is a permanent researcher with the CNRS and the Université Pierre et Marie Curie (Paris 6). She studied mathematics at Kiel University (Diploma in 2007) and computer science at the Max Planck Institute for Informatics and Saarland University (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. She was a post-doc at the Université 7 in Paris and the Max Planck Institute for Informatics in Saarbrücken. Carola Doerr's main research interest is in the theory of randomized algorithms, both in the design of efficient algorithms as well as in randomized query complexities. She has published several papers in the field of evolutionary computation.

Anna Esparcia

Affiliation: Universitat Politècnica de València, Spain
Anna has the role of vice chair of the Women@GECCO group. She is chair of GECCO 2015 so will take a modest role this year in organizating the meeting.


Gabriela Ochoa

Affiliation: Computing Science and Mathematics, School of Natural Sciences, University of Stirling, Scotland.
Gabriela Ochoa is a Lecturer in Computing Science at the University of Stirling in Scotland. Her research interests lie in the foundations and application of evolutionary algorithms and heuristic search methods, with emphasis on autonomous (self-*) search and fitness landscape analysis. She has published over 70 international peer reviewed papers. She is associate editor of Evolutionary Computation (MIT Press), was involved in founding the Self-* Search track at GECCO, co-chaired EvoCOP 2014 and has organised several special sessions at international conferences. She serves as secretary of the Women@GECCO group.

Una-May O'Reilly

Affiliation: Massachusetts Institute of Technology
Una-May is a Fellow of the International Society of Genetic and Evolutionary Computation, now ACM Sig-EVO.  In 2013 she received the EVO-Star award recognizing her contributions to evolutionary computation. At MIT CSAIL, Una-May leads the AnyScale Learning For All (ALFA) research group.  She has chaired or co-chaired GECCO, EuroGP and GPTP. She serves as vice-chair of ACM SIGEVO, the area editor for Data Analytics and Knowledge Discovery for Genetic Programming and Evolvable Machines, an editorial board member of Evolutionary Computation, and action editor for the Journal of Machine Learning Research. In 2013, with Anna Esparcia, Anniko Ekart and Gabriela Ochoa she inaugurated the Women@GECCO meeting and chairs the group.

Nur Zincir-Heywood
Dr. Nur Zincir-Heywood is a Professor of Computer Science at Dalhousie University, Canada. She received her PhD in 1998 in Computer Science and Engineering from Ege University, Turkey. Prior to moving to Dalhousie in 2000, Dr. Zincir-Heywood was a researcher at Sussex University, UK and Karlsruhe University, Germany as well as working as an instructor at the Internet Society Network Management workshops. She has published over 150 papers in network management, security, information systems and computational intelligence fields. She has substantial experience of industrial research in systems security and network management related topics with Raytheon, RUAG, Gtech, Palomino, Genieknows, and Public Safety Canada. Dr. Zincir-Heywood is a member of the IEEE and ACM.

Christine Zarges 
Christine is a Birmingham Fellow and Lecturer in the School of Computer Science at the University of Birmingham, UK. She 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, UK. Her PhD topic was "Theoretical Foundations of Artificial Immune Systems" and her current research focuses on the theoretical analysis of all kinds of randomised search heuristics. She is also interested in computational and theoretical aspects of immunology. She has given tutorials on "Artificial Immune Systems for Optimisation" at previous GECCOs and was co-chair of the AIS track at GECCO 2014. She is member of the editorial board of Evolutionary Computation (MIT Press) and co-organiser of FOGA 2015.

* Other key contributors are Leigh Sheneman, Amanda Whitlock, and Emilia Tantar.


12- 2nd Workshop on Metaheuristic Design Patterns (MetaDeeP)

Over many decades, Evolutionary Computation (and meta­- and hyper­-heuristics in general) has flourished, spawning an enormous variety of algorithms, operators and representations. However, metaheuristics research now requires a higher-level architectural and unifying perspective. There is a pressing need to: 

  • ground `loosely-specified' (e.g. metaphorically-inspired) approaches in terms of well-defined frameworks and components; 
  • achieve greater automation of metaheuristic and experimental design; and
  • facilitate large-scale knowledge discovery across frameworks and problem domains.

The software industry has already evolved to meet similar challenges, capturing recurring cross-cutting concerns via structured heuristics known as `Design Patterns'. Following the introduction of the seminal design patterns catalogue by the “gang of four” [1], the default level of design discourse among software practitioners significantly increased, and today patterns such as “Factory Method” or “Observer” are software engineers’ lingua franca. The workshop organizers strongly believe that the EC/metaheuristics community needs and deserves a corresponding breakthrough. The vision for framing such Metaheuristic Design Patterns (MDP) has been advocated in a recent lecture [2]; similar desires have also been expressed in [3]. GECCO 2013 saw the highly successful first workshop on MDP where MDPs such as “Template Method Hyper-Heuristics” and “Candidate Solution Repair” were proposed, and the notion of pattern languages was discussed.   

The goal of this second workshop on MDP is to continue to provide a forum for those interested in contributing to the MDP vision and/or willing to demonstrate its usefulness in practical and theoretical studies. We would emphasize that we see the workshop as distinctly bottom­-up, driven by ideas and needs of the community. Suggestions for further MDPs are welcome as we seek to ground old and new ideas and best practices into an emerging catalogue for MDPs. Also, building on pattern languages for software design (e.g. [4],[5]), we welcome proposals for pattern languages suitable for characterising meta-heuristic design patterns. Finally, we would welcome suggestions for ‘executable heuristic’ patterns in an attempt to significantly move the level of meta-heuristic automation forward.

By realizing this vision via the second MDP workshop, we hope to see it adopted by a large part of community and thus help to advance our domain as a whole.

[1]  Erich Gamma, Richard Helm, Ralph Johnson and John Vlissides. Design Patterns: Elements of Reusable Object-Oriented Software, Addison-Wesley, 1995.
[2]  Jerry Swan. Metaheuristic Design Patterns. Invited lecture at the Workshop on Evolutionary Computation for Automatic Design of Algorithms, GECCO’ 2013.
[3] Natalio Krasnogor. Handbook of Natural Computation, chapter “Memetic Algorithms”. Natural Computing. Springer Berlin / Heidelberg, 2009.
[4] Pattern Languages of Programs Conference,

[5] European Conference on Pattern Languages of Programs,


Chris Simons
He spent many years as an industrial software development practitioner in a variety of roles including technical architect, agile development methodology consultant and trainer. Now a senior lecturer, his research interests lie in human-centred bio-inspired metaheuristics and Search-Based Software Engineering (SBSE).


Jerry Swan
Before entering academia, spent 20 years in industry as a systems architect and software company owner. His research include meta- and hyper-heuristics, symbolic computation and machine learning. He has published more than 50 papers in international journals and conferences. Jerry has lectured and presented his research worldwide, and has been running international workshops and tutorials on the automated design of metaheuristics since 2011.


Krzysztof Krawiec
Krzysztof (Chris) Krawiec is an associate professor at Poznan University of Technology, Poland. He published over 70 papers on genetic programming, semantics in GP, modularity and coevolution, co-chaired EuroGP’13 and EuroGP'14, and is an associate editor of Genetic Programming and Evolvable Machines journal.


Daniel Tauritz
He is an Associate Professor of Computer Science at the Missouri University of Science and Technology (S&T). He served previously as GECCO 2010 Late Breaking Papers Chair and GECCO 2012 & 2013 GA Track Co-Chair. His research interests include the design of hyper-heuristics and self-configuring evolutionary algorithms and the application of computational intelligence techniques in cyber security, critical infrastructure protection, and search-based software engineering.

Jim Smith
He has been researching meta-heuristics since 1994.  He has published extensively on formalisms of metaheuristic components and design patterns, especially for adaptive and self-adaptive evolutionary and memetic systems.


14- Semantic Methods in Genetic Programming (SMGP)

Genetic programming (GP) — the application of evolutionary computing techniques to the creation of computer programs — has been a key topic in computational intelligence in the last couple of decades. In the last few years a rising topic in GP has been the use of semantic methods. The aim of this is to provide a way of exploring the input-output behaviour of programs, which is ultimately what matters for problem solving. This new approach has produced substantially better results on a number of problems, both benchmark problems and real-world applications and, has been grounded in a body of theory, which also informs algorithm design and builds interesting links with theoretical computer science and search-based software engineering. There are a number of research groups that are active in this area around the world. This is a growing research area, with an increasing number of publications each year.

This workshop is the second edition after the highly successful event we organized at PPSN’14, which attracted 30+ participants for an entire day. It provides both an opportunity to consolidate and extend work in this growing area, and to inform a wider group of people about this growing area of work. We can see these semantic methods being important in other areas of computational intelligence and machine learning, and so this provides a good opportunity for a broader set of conference participants to learn about this growth area.

More information:


Colin Johnson
He is a Reader in the School of Computing at the University of Kent. He has been active in bio-inspired computing research for the last 15 years, and in recent years has been particularly focused on genetic programming, with a substantial publication record in the area.  He has been active in conferences within the computational intelligence area, including membership of the programme committee for a number of conferences in the area, and would bring this experience to the organisation of this workshop.


Krzysztof Krawiec
He is an associate professor in the Institute of Computing Science, Poznan University of Technology, Poland, pursuing research in several branches of computational intelligence, primarily evolutionary computation, machine learning, and pattern recognition. He has been publishing in the GP field for about 13 years, and since 2008 he is actively developing various GP methods that involve program semantics. He served as a co-chair of the European Conference of Genetic Programing (EuroGP) in 2012 and 2013, and is an associate editor of Genetic Programming and Evolvable Machines journal.


Alberto Moraglio
He 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 bio-inspired computing and genetic programming 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, including a new form of Genetic Programming based on semantics, and for their rigorous theoretical analysis. He was co-chair of the European Conference on Genetic Programming 2012 and 2013, and has regular tutorials at GECCO and IEEE CEC. He is a member of the editorial board for Genetic Programming and Evolvable Machines (Springer).


Michael O’Neill
He is the ICON Chair of Business Analytics in the UCD School of Business, is a founding Director of the UCD Natural Computing Research & Applications group, and is Director of the UCD Complex & Adaptive Systems Laboratory (The CASL Institute). He has published in excess of 250 peer-reviewed publications. Michael was Local Chair of GECCO 2011, which was held in Dublin.  In the past he has served as Chair of the Genetic Programming Track (GECCO 2010), Chair of the Real World Applications Track (GECCO 2009), and was also Chair of the Grammatical Evolution Workshops (GEWS 2002-2004), and Chair of the SIGEVO Graduate Student Workshop 2005. He has co-authored a number of successful funding applications with a total value over €9 Million. In recent years his team has conducted research focusing on syntax and semantics in genetic programming.


16- Medical Applications of Genetic and Evolutionary Computation (MedGEC)

MedGEC is the GECCO Workshop on the application of genetic and evolutionary computation (GEC) to problems in medicine and healthcare. A dedicated workshop at GECCO provides a much needed focus for medical related applications of EC, not only providing a clear definition of the state of the art, but also support to practitioners for whom GEC might not be their main area of expertise or experience.


Stephen L. Smith
He received a BSc in Computer Science and then an MSc and PhD in Electronic Engineering from the University of Kent, UK. He is currently a reader in the Department of Electronics at the University of York, UK. Stephen's main research interests are in developing novel representations of evolutionary algorithms particularly with application to problems in medicine. Stephen is associate editor for the journal Genetic Programming and Evolvable Machines and a member of the editorial board for the International Journal of Computers in Healthcare and Neural Computing and Applications. He has some 75 refereed publications, is a Chartered Engineer and a fellow of the British Computer Society.


Stefano Cagnoni
He graduated in Electronic Engineering at the University of Florence in 1988 where he has been a PhD student and a post-doc until 1997. In 1994 he was a visiting scientist at the Whitaker College Biomedical Imaging and Computation Laboratory at the Massachusetts Institute of Technology. Since 1997 he has been with the University of Parma, where he has been Associate Professor since 2004. He has been Editor-in-chief of the "Journal of Artificial Evolution and Applications" from 2007 to 2010. Since 1999, he has been chairman of EvoIASP, an event dedicated to evolutionary computation for image analysis, signal processing and pattern recognition, presently a track of the EvoApplications Conference held yearly as part of Evostar.  In 2009 he was presented with the "Evostar Award", in recognition of the most outstanding contribution to Evolutionary Computation.  Since 2005, he has co-chaired MedGEC, workshop on medical applications of evolutionary computation at GECCO.  Co-editor of special issues of journals dedicated to Evolutionary Computation for Image Analysis and Signal Processing. He has been reviewer for international journals and member of the committees of several conferences. He has been member of the Advisory Board of Perada, the UE Coordination Action on Pervasive Adaptation. 


Dr. Robert M. Patton
He received his Ph.D. in Computer Engineering with emphasis on Software Engineering from the University of Central Florida in 2002. In 2003, he joined the Applied Software Engineering Research group of Oak Ridge National Laboratory as a researcher.  Dr. Patton primary research interests include data and event analytics, intelligent agents, computational intelligence, and nature-inspired computing. He currently is investigating novel approaches of evolutionary computation to the analysis of mammograms, abdominal aortic aneurysms, and traumatic brain injuries.  In 2005, he served as a member of the organizing committee for the workshop on Ambient Intelligence - Agents for Ubiquitous Environments in conjunction with the 2005 Conference on Autonomous Agents and Multiagent Systems (AAMAS 2005).




Important Dates:
Submission deadline: April 8, 2015
Authors notification: April 25, 2015
Camera-ready submissions: May 10, 2015
Conference: July 11-15, 2015


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