Pietro S. Oliveto

Professor of Computer Science

• Department of Computer Science and Engineering,
• Southern University of Science and Technology,
• College of Engineering, South Tower
• Shenzhen, China

• Office: 113
• Theory of AI Lab: 348B
• Phone: +86 88011211
• Email: olivetop@sustech.edu.cn

Research Interests

My main research interests are in bio-inspired computation, randomised search heuristics and randomised algorithms in general, with strong emphasis on runtime analysis and computational complexity.

Theory of AI Lab - Vacancies

I am in the process of setting up a Theory of AI Lab @SUSTech. I have the following doctoral and post-doctoral positions available in Theory of Evolutionary Computation, Randomised Search Heuristics and Theory of AI:

• • Postdoc in Time complexity Analysis of Bio-Inspired Computation. ( Available now until position filled).
• • PhD Position: Time complexity Analysis of Bio-Inspired Computation. ( Available now until position filled).
• • PhD position: Analysis and Design of Bio-Inspired Algorithms. ( Available now until position filled).
To express interest in the PhD positions contact me via email in the first instance.

Current Activities

• • I am Theory Track co-Chair together with Benjamin Doerr of the 2023 Genetic and Evolutionary Computation Conference (GECCO 2023), taking place in Lisbon, Portugal from the 15th to the 19th of July 2023.
• • I am Tutorial Speaker at (GECCO 2023) with Per Kristian Lehre, for a tutorial lecture entitled 'Runtime Analysis of Population-based Evolutionary Algorithms'. The tutorial introduces the mathematical techniques used in the analyses of realistic (not simplified) evolutionary and genetic algorithms.
• • I am co-organiser together with Nelishia Pillay and Ivan Mauricio Amaya of the IEEE CIS Student and Early Career Mentoring Program at the 2023 IEEE Congress on Evolutionary Computation (CEC 2023), taking place in Chicago, USA from 1st to the 5th of July 2021.
• • I am co-guest editor together with Benjamin Doerr of an Algorithmica journal Special Issue on the best papers of the GECCO 2023 Theory Track.
• • I am Associate Editor of the IEEE Transactions on Evolutionary Computation (IEEE TEVC) journal.
• • I have completed my term (2018-2019) as Chair of the IEEE CIS Technical Committee on Evolutionary Computation (ECTC). I have since been serving the committee as Vice-Chair (Chair: Bing Xue).
• • I am member of the IEEE CIS Intelligent System Applications Technical Committee and member of the Task Force on Theoretical Foundations of Bio-Inspired Computation of which I was the Founding Chair (2012-2017).
• • I am member of the IEEE CIS Nominations Committee (2022-2023).

Editorial Work

 
• • P.S. Oliveto, A. Auger, F. Chicano, C. M. Fonseca
  • Special Issue on Theoretical Foundations of Evolutionary Computation - Guest Editorial
  • IEEE Transactions on Evolutionary Computation.
  • Vol.24(6):993-994, 2020, IEEE Press.
• • P.S. Oliveto, A. Sutton
  • Special Issue on Theory of Evolutionary Computation - Guest Editorial
  • Theoretical Computer Science.
  • Vol 832:1-2, September 2020, Elsevier. Link
• • P.S. Oliveto, A. Sutton
  • Special Issue on Theory of Evolutionary Algorithms 2014 - Guest Editorial
  • Evolutionary Computation.
  • Vol 23(4):509-511, 2015, MIT Press.
• • P.S. Oliveto, X. Yao
  • Special Issue on Evolutionary Computation - Guest Editorial
  • Journal of Computer Science and Technology.
  • Springer, 2012

Book Chapters

 
• • P.S. Oliveto.
  • Rigorous Performance Analysis of Hyper-Heuristics.
  • Automated Machine Learning and Search Algorithms.
  • Nelishia Pillay, Rong Qu editors, Springer, 2021.
• • A. Lissovoi, P.S. Oliveto.
  • Computational Complexity Analysis of Genetic Programming.
  • Theory of Evolutionary Computation - Recent Developments in Discrete Optimization.
  • Benjamin Doerr, Frank Neumann editors, Springer, 2020 (Arxiv Version).
• • P.K. Lehre, P.S. Oliveto.
  • Theoretical Analysis of Stochastic Search Algorithms.
  • In Handbook of Heuristics.
  • Mauricio G.C. Resende, Rafael Marti and Panos M. Pardalos editors, Springer, 2018.
  • DOI: 10.1007/978-3-319-07153-4_35-1.
• • P.S. Oliveto, X. Yao.
  • Runtime Analysis of Evolutionary Algorithms for Discrete Optimization.
  • In Theory of Randomized Search Heuristics~Foundations and Recent Developments, pp. 21-52.
  • B. Doerr and A. Auger editors, World Scientific, February 2011. (World Scientific)
• • A. Athanasiou, M. De Felice, G. Oliveto, P. S. Oliveto.
  • Dynamical Modeling and Parameter Identification of Seismic Isolation Systems by Evolution Strategies.
  • In Computational Intelligence, Studies in Computational Intelligence series N.465, pp. 101-118.
  • K. Madani, A. Dourado, A. Rosa, J. Felipe (Eds), Springer-Verlag, 2013.

Refereed Journal Papers

• • B. Doerr, A, Lissovoi, P. S. Oliveto
  • (1+ 1) genetic programming with functionally complete instruction sets can evolve Boolean conjunctions and disjunctions with arbitrarily small error
  • Artificial Intelligence,
  • Vol 319, 2023. [DOI]
• • A, Lissovoi, P. S. Oliveto, J.A. Warwicker
  • When Move Acceptance Hyper-heuristics Outperform Metropolis and Elitist Evolutionary Algorithms and When Not
  • Artificial Intelligence,
  • Vol 314, 2023. [DOI]
• • G. T. Hall, P. S. Oliveto, D. Sudholt
  • On the impact of the performance metric on efficient algorithm configuration
  • Artificial Intelligence,
  • Vol 303, 2022. [DOI]
• • P. S. Oliveto, D. Sudholt, C. Witt
  • Tight Bounds on the Expected Runtime of a Standard Steady State Genetic Algorithm
  • Algorithmica,
  • 2022. [pdf]
• • D, Corus, P. S. Oliveto, D. Yazdani
  • Fast Immune System-Inspired Hypermutation Operators for Combinatorial Optimization
  • IEEE Transactions on Evolutionary Computation,
  • 25(5):956-970, 2021. [pdf]
• • D. Corus, A. Lissovoi, P. S. Oliveto, C. Witt
  • On Steady-State Evolutionary Algorithms and Selective Pressure: Why Inverse Rank-Based Allocation of Reproductive Trials is Best
  • ACM Transactions on Evolutionary Learning and Optimization,
  • 1(1):1-38, 2021. [pdf]
• • D. Corus, P. S. Oliveto
  • On the Benefits of Populations for the Exploitation Speed of Standard Steady-State Genetic Algorithms
  • Algorithmica,
  • 2020. DOI: 10.1007/s00453-020-00743-1
• • A. Lissovoi, P. S. Oliveto, J. A. Warwicker
  • Simple Hyper-heuristics Control the Neighbourhood Size of Randomised Local Search Optimally for Leading ones. [Posted Online May 23, 2019]
  • Evolutionary Computation (ECJ),
  • 2019.
• • A. Lissovoi, P. S. Oliveto
  • On the Time and Space Complexity of Genetic Programming for Evolving Boolean Conjunctions [Download] .
  • Journal of Artificial Intelligence Research (JAIR),
  • 2019.
• • D. Corus, P. S. Oliveto, D. Yazdani
  • Artificial Immune Systems Can Find Arbitrarily Good Approximations for the NP-Hard Number Partitioning Problem.
  • Artificial Intelligence,
  • 2019.
  • DOI: 10.1016/j.artint.2019.03.001
• • D. Corus, P. S. Oliveto, D. Yazdani
  • When Hypermutations and Ageing Enable Artificial Immune Systems to Outperform Evolutionary Algorithms.
  • Theoretical Computer Science,
  • 2019.
  • DOI: 10.1016/j.tcs.2019.03.002
• • P. S. Oliveto, D. Sudholt, C. Zarges
  • On the Benefits and Risks of Using Fitness Sharing for Multimodal Optimisation. [Download]
  • Theoretical Computer Science,
  • 2018.
• • S. Nallaperuma, P. S. Oliveto, J. Perez Heredia, D. Sudholt.
  • On the Analysis of Trajectory-Based Search Algorithms: When is it Beneficial to Reject Improvements? [Download]
  • Algorithmica,
  • Vol 81 (2) 858-885, 2019.
• • P. S. Oliveto, T. Paixão, J. Pérez Heredia, D. Sudholt, B. Trubenová.
  • How to Escape Local Optima in Black Box Optimisation: When Non-Elitism Outperforms Elitism. [Download]
  • Algorithmica,
  • Vol 80 (5), 1604-1633, 2018.
• • D.Corus, P. S. Oliveto.
  • Standard Steady State Genetic Algorithms can Hillclimb Faster than Mutation-only Evolutionary Algorithms. [Download]
  • IEEE Transactions on Evolutionary Computation,
  • Vol. 22 (5), 720-732, 2018.
• • D.-C. Dang, T. Friedrich, T. Kötzing, M. S. Krejca, P. K. Lehre, P. S. Oliveto, D. Sudholt, A. M. Sutton.
  • Escaping Local Optima Using Crossover with Emergent Diversity. [Download]
  • IEEE Transactions on Evolutionary Computation,
  • Vol. 22 (3), 484-497, 2018.
• • D. Corus, J. He, T. Jansen, P. S. Oliveto, D. Sudholt, C. Zarges.
  • On Easiest Functions for Mutation Operators in Bio-Inspired Optimisation. [Download]
  • Algorithmica,
  • Vol. 78 (2), 714-740, 2017.
  • DOI: 10.1007/s00453-016-0201-4
• • P.S.Oliveto, C.Witt.
  • Improved Time Complexity Analysis of the Simple Genetic Algorithm.
  • Theoretical Computer Science, (Elsevier)
  • Vol. 605, 21-41, 2015.
  • DOI: 10.1016/j.tcs.2015.01.002
• • P.S.Oliveto, C.Zarges.
  • Analysis of Diversity Mechanisms for Optimisation in Dynamic Environments with Low Frequencies of Change.
  • Theoretical Computer Science (Elsevier),
  • Vol. 561, 37-56, 2015.
  • DOI: 10.1016/j.tcs.2014.10.028
• • P.S.Oliveto, C.Witt.
  • On the Runtime Analysis of the Simple Genetic Algorithm.
  • Theoretical Computer Science (Elsevier),
  • Vol. 545, 2-19, 2014.
  • DOI: 10.1016/j.tcs.2013.06.015
• • P.S.Oliveto, C.Witt.
  • Simplified Drift Analysis for Proving Lower Bounds in Evolutionary Computation.
  • Algorithmica (Springer),
  • Vol. 59 (3), 369-386, 2011.
• • T.Friedrich, P.S.Oliveto, D.Sudholt, C.Witt.
  • Analysis of Diversity-Preserving Mechanisms for Global Exploration.
  • Evolutionary Computation, (ECJ),
  • Vol. 17 (4), 455-476, 2009.
• • P.S.Oliveto, J.He, X.Yao.
  • Analysis of the (1+1)-EA for Finding Approximate Solutions to Vertex Cover Problems.
  • IEEE Transactions on Evolutionary Computation (IEEE TEVC),
  • Vol. 13 (5), 1006-1029, 2009.
• • P.S.Oliveto, J.He, X.Yao.
  • Time Complexity of Evolutionary Algorithms for Combinatorial Optimization: A Decade of Results.
  • International Journal of Automation and Computing (IJAC)
  • Vol. 4 (3), 281-293, 2007.

Recent Refereed Conference Publications

• • D. Corus, P. S. Oliveto, D. Yazdani
  • Automatic adaptation of hypermutation rates for multimodal optimisation.
  • In Proceedings of the 16th ACM/SIGEVO Conference on Foundations of Genetic Algorithms (FOGA 2021)
  • 6-8 September 2021. (online)
• • George T. Hall, Pietro S. Oliveto and Dirk Sudholt
  • Fast Perturbative Algorithm Configurators. [Download Arxiv Version]
  • In Proceedings of the 16th conference on Parallel Problem Solving from Nature ( PPSN XVI),
  • Leiden, The Netherlands, September 5-9, 2020.
• • George T. Hall, Pietro S. Oliveto, Dirk Sudholt
  • Analysis of the Performance of Algorithm Configurators for Search Heuristics with Global Mutation Operators. (Best paper nomination)
  • In Proceedings of the 2020 Genetic and Evolutionary Computation Conference (GECCO '20)
  • Cancun, Mexico, pp. 823--831, ACM Press 2020. [Download]
• • Pietro S. Oliveto, Dirk Sudholt, Carsten Witt
  • A Tight Lower Bound on the Expected Runtime of Standard Steady State Genetic Algorithms.
  • In Proceedings of the 2020 Genetic and Evolutionary Computation Conference (GECCO '20)
  • Cancun, Mexico, pp. 1323--1331, ACM Press 2020. [Download]
• • Michael Foster, Matthew Hughes, George O'Brien, Pietro S. Oliveto, James Pyle, Dirk Sudholt, James Williams
  • Do Sophisticated Evolutionary Algorithms Perform Better than Simple Ones?
  • In Proceedings of the 2020 Genetic and Evolutionary Computation Conference (GECCO '20)
  • Cancun, Mexico, pp. 184--192, ACM Press 2020. [Download]
• • A. Lissovoi, P. S. Oliveto, J. A. Warwicker
  • How the Duration of the Learning Period Affects the Performance of Random Gradient Selection Hyper-Heuristics.
  • In Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence (AAAI-20),
  • New York, USA, February 7-12, pp. 2376-2383, AAAI Press 2020.
• • D. Corus, P. S. Oliveto, D. Yazdani
  • On Inversely Proportional Hypermutations with Mutation Potential.
  • In Proceedings of the 2019 Genetic and Evolutionary Computation Conference (GECCO '19)
  • Prague, Czech Republic, July 2019.
• • B.Doerr, A. Lissovoi, P. S. Oliveto
  • Evolving Boolean Functions with Conjunctions and Disjunctions via Genetic Programming.
  • In Proceedings of the 2019 Genetic and Evolutionary Computation Conference (GECCO '19)
  • Prague, Czech Republic, July 2019.
• • D. Corus, P. S. Oliveto
  • On the Benefits of Populations on the Exploitation Speed of Standard Steady-State Genetic Algorithms.
  • In Proceedings of the 2019 Genetic and Evolutionary Computation Conference (GECCO '19)
  • Prague, Czech Republic, July 2019.
• • G. Hall, P. S. Oliveto, D. Sudholt
  • On the Impact of the Cutoff Time on the Performance of Algorithm Configurators.
  • In Proceedings of the 2019 Genetic and Evolutionary Computation Conference (GECCO '19)
  • Prague, Czech Republic, July 2019.
• • A. Lissovoi, P. S. Oliveto, J. A. Warwicker
  • On the Time Complexity of Algorithm Selection Hyper-Heuristics for Multimodal Optimisation. [Download]
  • In Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence ( AAAI-19),
  • Honolulu, Hawaii, USA, January 27 - February 1, 2019.
• • D. Corus, P. S. Oliveto, D. Yazdani
  • Fast Artificial Immune Systems. [Download Arxiv Version]
  • In Proceedings of the 15th conference on Parallel Problem Solving from Nature ( PPSN XV),
  • Coimbra, Portugal, September 8-12, 2018.
• • D. Corus, P. S. Oliveto, D. Yazdani
  • Artificial Immune Systems Can Find Arbitrarily Good Approximations for the NP-Hard Partition Problem. [Download Arxiv Version]
  • In Proceedings of the 15th conference on Parallel Problem Solving from Nature ( PPSN XV),
  • Coimbra, Portugal, September 8-12, 2018.
• • B. Doerr, A. Lissovoi, P. S. Oliveto, J.A. Warwicker
  • On the Runtime Analysis of Selection Hyper-Heuristics with Adaptive Learning Periods. [Download]
  • In Proceedings of the 2018 Genetic and Evolutionary Computation Conference (GECCO '18)
  • Kyoto, Japan, July 15-19, 2018.
• • A. Lissovoi, P. S. Oliveto
  • On the Time and Space Complexity of Genetic Programming for Evolving Boolean Conjunctions. [Download]
  • In Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence (AAAI-18),
  • New Orleans, Louisiana, US February 2-7, 2018.
• • A. Lissovoi, P. S. Oliveto, J.A. Warwicker
  • On the Runtime Analysis of Generalised Selection Hyper-heuristics for Pseudo-Boolean Optimisation. [Download]
  • In Proceedings of the 2017 Genetic and Evolutionary Computation Conference (GECCO '17)
  • Berlin, Germany, July 15-19, 2017.
• • D. Corus, P. S. Oliveto, D. Yazdani
  • On the Runtime Analysis of the Opt-IA Artificial Immune System. [Download]
  • In Proceedings of the 2017 Genetic and Evolutionary Computation Conference (GECCO '17),
  • Berlin, Germany, July 15-19, 2017.
• • S. Nallaperuma, P. S. Oliveto, J. Perez Heredia, D. Sudholt
  • When is it Beneficial to Reject Improvements? [Download]
  • In Proceedings of the 2017 Genetic and Evolutionary Computation Conference (GECCO '17),
  • Berlin, Germany, July 15-19, 2017.
• • D.-C. Dang, T. Friedrich, T. Kötzing, M. S. Krejca, P. K. Lehre, P. S. Oliveto, D. Sudholt, A. M. Sutton
  • Emergence of Diversity and its Benefits for Crossover in Genetic Algorithms. [Download]
  • In Proceedings of the 14th Parallel Problem solving from Nature Conference (PPSN 2016),
  • Edinburgh, Scotland, September 17-21, 2016. (Best paper nomination)
• • D.-C. Dang, T. Friedrich, T. Kötzing, M. S. Krejca, P. K. Lehre, P. S. Oliveto, D. Sudholt, A. M. Sutton
  • Escaping Local Optima with Diversity Mechanisms and Crossover. [Download]
  • In Proceedings of the 2016 Genetic and Evolutionary Computation Conference (GECCO '16),
  • Colorado, USA, July 20-24, 2016.
• • P. S. Oliveto, T. Paixão, J. Pérez Heredia, D. Sudholt, B. Trubenová
  • When Non-Elitism Outperforms Elitism for Crossing Fitness Valleys. [Download]
  • In Proceedings of the 2016 Genetic and Evolutionary Computation Conference (GECCO '16),
  • Colorado, USA, July 20-24, 2016.
• • A. Mambrini, P.S. Oliveto
  • On the Analysis of Simple Genetic Programming for Evolving Boolean Functions. [Download]
  • In Proceedings of the 2016 European Conference on Genetic Programming, (EuroGP '16), pp. 99-114,
  • Porto, Portugal, March 30-April 1, 2016.(Best paper nomination)
• • D. Corus, J. He, T. Jansen, P.S.Oliveto, D. Sudholt, C.Zarges
  • On Easiest Functions for Somatic Contiguous Hypermutations And Standard Bit Mutations.
  • In Proceedings of the 2015 Genetic and Evolutionary Computation Conference (GECCO '15),
  • Madrid, Spain, July 11-15, 2015.
• • P.S.Oliveto, D. Sudholt, C.Zarges
  • On the Runtime Analysis of Fitness Sharing Mechanisms.
  • In Proceedings of the 13th Parallel Problem solving from Nature Conference (PPSN 2014),
  • Ljubljana, Slovenia, September 13-17, 2014.
• • P.S.Oliveto, D. Sudholt.
  • On the Runtime Analysis of Stochastic Ageing Mechanisms.
  • In Proceedings of the 2014 Genetic and Evolutionary Computation Conference (GECCO '14),
  • Vancouver, Canada, July 12-16, 2014. (Best paper award)
• • P.S.Oliveto, C. Zarges.
  • Analysis of Diversity Mechanisms for Robust Optimisation in Dynamic Environments with Low Frequencies of Change.
  • In Proceedings of the 2013 Genetic and Evolutionary Computation Conference (GECCO'13),
  • Amsterdam, the Netherlands, July 6-10, 2013.
• • P.S.Oliveto, C. Witt.
  • Improved Runtime Analysis of the Simple Genetic Algorithm.
  • In Proceedings of the 2013 Genetic and Evolutionary Computation Conference (GECCO'13),
  • Amsterdam, the Netherlands, July 6-10, 2013.
• • T. Jansen, P.S.Oliveto, C. Zarges.
  • Approximating Vertex Cover Using Edge-Based Representations.
  • In Proceedings of Foundations of Genetic Algorithms XII (FOGA'13),
  • Adelaide, Australia, January 16-20, 2013.
• • P.S.Oliveto, C. Witt.
  • On the Runtime Analysis of the Simple Genetic Algorithm.
  • In Proceedings of the 2012 Genetic and Evolutionary Computation Conference (GECCO'12),
  • Philadelphia, USA, July 7-11, 2012.
• • A. Athanasiou, M. De Felice, G. Oliveto, P. S. Oliveto
  • Evolutionary Algorithms for the Identification of Structural Systems in Earthquake Engineering.
  • In Proceedings of the International Conference on Evolutionary Computation Theory and Applications (ECTA'11),
  • Paris, france, October 24-26, 2011.(Best paper nomination)
• • T. Jansen, P. S. Oliveto, C. Zarges
  • On the Analysis of the Immune Inspired B-Cell Algorithm for the Vertex Cover Problem.
  • In Proceedings of the 10th International Conference on Artificial Immune Systems (ICARIS'11),
  • Cambridge, UK, July 18-21, 2011. (Best paper award)
• • F. Neumann, P. S. Oliveto, G. Rudolph, D. Sudholt
  • On the Effectiveness of Crossover for Migration in Parallel Evolutionary Algorithms.
  • In Proceedings of the 2011 Genetic and Evolutionary Computation Conference (GECCO'11),
  • Dublin, Ireland, July 12-16, 2011.
• • S. Kratsch, P.K. Lehre, F. Neumann, P.S. Oliveto
  • Fixed Parameter Evolutionary Algorithms and Maximum Leaf Spanning Trees: A Matter of Mutation.
  • In Proceedings of the 11th Conference on Parallel Problem Solving from Nature (PPSN'10),
  • Krakow, Poland, September 11-15, 2010.
• • T. Kötzing, P. K. Lehre, F. Neumann, P. S. Oliveto.
  • Ant colony optimization and the minimum cut problem.
  • In Proceedings of the 2010 Genetic and Evolutionary Computation Conference (GECCO'10),
  • Portland, Oregon, July 7-11, 2010.
• • A. Chandra, P. S. Oliveto, X. Yao.
  • Co-evolution of Optimal Agents for the Alternating Offers Bargaining Game.
  • In Proceedings of the European Conference on the Applications of Evolutionary Computation (EvoApplications 2010),
  • Istanbul Technical University, Istanbul, Turkey, April 7-9, 2010.
• • F.Neumann, P.S.Oliveto, C. Witt.
  • Theoretical Analysis of Fitness-Proportional Selection - Landscapes and Efficiency.
  • In Proceedings of the 2009 Genetic and Evolutionary Computation Conference (GECCO'09),
  • Montreal, Canada, July 8-12, 2009.
• • P.S.Oliveto, P.K.Lehre, F.Neumann.
  • Theoretical Analysis of Rank-based Mutation - Combining Exploration and Exploitation.
  • In Proceedings of the IEEE Congress on Evolutionary Computation 2009(CEC'09),
  • Trondheim, Norway, May 18-21, 2009. (Best student paper nomination)
• • P.S.Oliveto, C.Witt.
  • Simplified Drift Analysis for Proving Lower Bounds in Evolutionary Computation.
  • In Proceedings of the Parallel Problem Solving from Nature (PPSN'08),
  • Dortmund, Germany, September 13-17, 2008.
• • T. Friedrich, P.S.Oliveto, D.Sudholt, C.Witt.
  • Theoretical Analysis of Diversity Mechanisms for Global Exploration.
  • In Proceedings of the Genetic and Evolutionary Computation Conference (GECCO'08),
  • Atlanta, Georgia, USA, July 12-16, 2008. (Best paper award)
• • P.S.Oliveto, J.He, X.Yao.
  • Analysis of Population-based Evolutionary Algorithms for the Vertex Cover Problem.
  • In Proceedings of the IEEE World Congress on Computational Intelligence (WCCI'08),
  • Hong Kong, June 1-6, 2008. Pictures
• • P.S.Oliveto, J.He, X.Yao.
  • Evolutionary Algorithms and the Vertex Cover Problem .
  • In Proceedings of the IEEE Congress on Evolutionary Computation (CEC'07),
  • Singapore, September 25-28, 2007. Pictures

• • Co-Chair of the 2019 Foundations of Computational Intelligence (IEEE FOCI 2019) Symposium
  • Xiamen, China, December 2019.
• • Co-Chair of the 2018 Foundations of Computational Intelligence (IEEE FOCI 2018) Symposium
  • Bengaluru, India, November 2018.
• • Co-Chair of the 2017 Foundations of Computational Intelligence (IEEE FOCI 2017) Symposium
  • November 27 - December 1, 2017, Honolulu, Hawaii, USA.
• • Co-Chair of the 2016 Foundations of Computational Intelligence (IEEE FOCI 2016) Symposium
  • December 6 - 9, 2016, Athens, Greece.
• • Co-Chair of the 2015 IEEE Symposium on Foundations of Computational Intelligence (IEEE FOCI 2015)
  • December 7 - 10, 2015, Capetown, South Africa.

• Co-Chair of the IEEE WCCI 2016 Special Session on "Theoretical Foundations of Bio-inspired Computation"

• Co-Chair of the IEEE CEC 2015 Special Session on "Theoretical Foundations of Bio-inspired Computation"

• Co-Chair of the IEEE WCCI 2014 Special Session on "Theoretical Foundations of Bio-inspired Computation"

• Co-Chair of the IEEE CEC 2013 Special Session on "Theoretical Foundations of Bio-inspired Computation"

Programme Committees

• AAAI Conference on Artificial Intelligence: since AAAI-19.
• International Joint Conference on Artificial Intelligence: IJCAI'15, and since IJCAI-19.
• ACM Genetic and Evolutionary Computation Conference: since GECCO'08.
• IEEE Congress on Evolutionary Computation: since CEC'07
• ACM Foundations Of Genetic Algorithms: since FOGA'09
• International Conference in Parallel Problem Solving from Nature: Since PPSN 2010.
• European Conference on Evolutionary Computation in Combinatorial Optimisation: Since EvoCOP'18

Grants & Fellowships

• COST Action CA15140: Improving Applicability of Nature-Inspired Optimisation by Joining Theory and Practice (ImAppNIO)
• EPSRC Early Career Fellowship (2015-2020) Rigorous Runtime Analysis of Bio-inspired Computing ( EP/M004252/1 )
• Vice Chancellor Fellowship, University of Sheffield (2013-2016).
• EPSRC Postdoctoral Fellowship in Theoretical Computer Science grant (2010-2013), "Rigorous Runtime Analysis of Nature Inspired Meta-heuristics" ( EP/H028900/1 )
• EPSRC PhD+ Postdoctoral Fellowship grant (2009). ( EP/P502322/1)
• IEEE student travel grant for the CEC'09 conference attendance.
• IEEE student travel grant for the FOCI'07 conference attendance.