Department of Computer Science
University of Wyoming
Dept 3315, 1000 E University Ave
Laramie, WY 82071-2000
My research combines artificial intelligence and machine learning to build robust systems with state-of-the-art performance. I develop techniques to induce models of how algorithms for solving computationally difficult problems behave in practice. Such models allow to select the best algorithm and choose the best parameter configuration for solving a given problem. I lead the Meta-Algorithmics, Learning and Large-scale Empirical Testing (MALLET) lab and have acquired more than $400K in external funding to date. I am directing the Artificially Intelligent Manufacturing center (AIM) at the University of Wyoming.
More broadly, I am interested in innovative ways of modelling and solving challenging problems and applying such approaches to the real world. Part of this is making cutting edge research available to and usable by non-experts. Machine learning often plays a crucial role in this, and I am also working on making machine learning more accessible and easier to use.
Interested in coming to beautiful Wyoming and joining MALLET? There are several funded PhD positions available. Please drop me an email or, if you are already here, come by my office. I also have Master's projects and projects for undergraduates seeking research experience available. There are usually several of them posted on the board opposite of my office.
Follow me on Twitter.
I gave a talk at NCAR CISL on algorithm selection and configuration (PDF slides, video).
Joeran Beel and I are organizing the First Workshop on Algorithm Selection and Meta-Learning in Information Retrieval.
I attended Dagstuhl Seminar 18401: “Automating Data Science”.
Giving a talk on automatic machine learning at the AutoML workshop at the Pacific Rim Conference on AI 2018 (PDF slides).
Our research center on Artificially Intelligent Manufacturing (AIM) was funded by the Engineering Initiative.
I gave a talk at the University of St Andrews on algorithm selection and configuration (PDF slides).
I gave the invited talk at the IDIR summer workshop on mlr (PDF slides).
I gave a talk at the University of Glasgow on algorithm selection and configuration (PDF slides).
I presented our paper on the Temporal Shapley Value at IJCAI 2018 (slides).
I gave a talk at LIACS on the Shapley Value and its temporal cousin for analysing algorithm performance (PDF slides).
I gave a talk at TU Eindhoven on algorithm selection and configuration (PDF slides).
My project proposal for more robust performance models has been funded by the NSF ($412,000).
I will be at ISMP 2018 in Bordeaux, giving an invited talk on our work on the Shapley value to evalute the contribution of algorithms (PDF slides).
Co-organizing the Second Workshop on Progress Towards the Holy Grail, co-located with CP 2018.
I have secured €3,000 funding from Artificial Intelligence Journal for the ACP summer school 2018.
Our paper “Quantifying Algorithmic Improvements over Time” has been accepted to the IJCAI/ECAI 2018 special track on the evolution of the contours of AI (23% acceptance rate).
Giving a talk at Tech Talk Laramie on April 19th 6pm: https://www.meetup.com/TechTalkLaramie/events/sdksvnyxgbzb/
I was awarded a University of Wyoming Global Engagement Office travel grant worth $2000.
I am featured on the University of Wyoming new faculty profile for March.
Attended the 2018 CRA career mentoring workshop.
I’m organizing the ACP summer school 2018.
I’m very honored to have been named outstanding PC member at AAAI 2018.
Looking forward to AAAI 2018 in New Orleans!
The proceedings for the 2017 Algorithm Selection Challenge are online!
The results of the 2017 Algorithm Selection Challenge are in. Congratulations to the winner!
I’ll be at the Wyoming Global Technology Summit.
Looking forward to the COSEAL meeting 2017 in Brussels!
Giving an invited talk “Intelligent Constraint Programming: Algorithm Selection for fun and profit” at the Workshop on Progress Towards the Holy Grail (which I am co-organizing), co-located with CP 2017, ICLP 2017, and SAT 2017. I am also on the programme committee for the joint doctoral consortium.
Will be at IJCAI 2017. See you there!
For citation numbers, please see my Google Scholar page.
Schwarz, Hannes, Lars Kotthoff, Holger Hoos, Wolf Fichtner, and Valentin Bertsch. “Improving the Computational Efficiency of Stochastic Programs Using Automated Algorithm Configuration: an Application to Decentralized Energy Systems.” Annals of Operations Research, January 2019. https://doi.org/10.1007/s10479-018-3122-6. preprint PDF bibTeX abstract
Lindauer, Marius, Jan N. van Rijn, and Lars Kotthoff. “The Algorithm Selection Competitions 2015 and 2017.” Artificial Intelligence 272 (2019): 86–100. https://doi.org/https://doi.org/10.1016/j.artint.2018.10.004. preprint PDF bibTeX abstract
Kotthoff, Lars, Alexandre Fréchette, Tomasz P. Michalak, Talal Rahwan, Holger H. Hoos, and Kevin Leyton-Brown. “Quantifying Algorithmic Improvements over Time.” In 27th International Joint Conference on Artificial Intelligence (IJCAI) Special Track on the Evolution of the Contours of AI, 2018. preprint PDF bibTeX abstract
Degroote, Hans, Patrick De Causmaecker, Bernd Bischl, and Lars Kotthoff. “A Regression-Based Methodology for Online Algorithm Selection.” In 11th International Symposium on Combinatorial Search (SoCS), 37–45, 2018. preprint PDF bibTeX abstract
Bhuiyan, Faisal H., Lars Kotthoff, and Ray S. Fertig. “A Machine Learning Technique to Predict Static Multi-Axial Failure Envelope of Laminated Composites.” In American Society for Composites 33rd Annual Technical Conference, 2018. preprint PDF bibTeX abstract
Bistarelli, Stefano, Lars Kotthoff, Francesco Santini, and Carlo Taticchi. “Containerisation and Dynamic Frameworks in ICCMA’19.” In Second International Workshop on Systems and Algorithms for Formal Argumentation (SAFA 2018) Co-Located with the 7th International Conference on Computational Models of Argument (COMMA 2018), 2171:4–9. CEUR Workshop Proceedings. CEUR-WS.org, 2018. preprint PDF bibTeX abstract
Bessière, Christian, Luc de Raedt, Tias Guns, Lars Kotthoff, Mirco Nanni, Siegfried Nijssen, Barry O’Sullivan, Anastasia Paparrizou, Dino Pedreschi, and Helmut Simonis. “The Inductive Constraint Programming Loop.” IEEE Intelligent Systems, 2018. https://doi.org/10.1109/MIS.2017.265115706. preprint PDF bibTeX abstract
Hutter, Frank, Lars Kotthoff, and Joaquin Vanschoren, eds. Automatic Machine Learning: Methods, Systems, Challenges. Springer, 2018. bibTeX
Kerschke, Pascal, Lars Kotthoff, Jakob Bossek, Holger H. Hoos, and Heike Trautmann. “Leveraging TSP Solver Complementarity through Machine Learning.” Evolutionary Computation 26, no. 4 (2018): 597–620. https://doi.org/10.1162/evco_a_00215. preprint PDF bibTeX abstract
Kotthoff, Lars, Barry Hurley, and Barry O’Sullivan. “The ICON Challenge on Algorithm Selection.” AI Magazine 38, no. 2 (2017): 91–93. preprint PDF bibTeX
Kotthoff, Lars, Chris Thornton, Holger H. Hoos, Frank Hutter, and Kevin Leyton-Brown. “Auto-WEKA 2.0: Automatic Model Selection and Hyperparameter Optimization in WEKA.” Journal of Machine Learning Research 18, no. 25 (2017): 1–5. preprint PDF bibTeX abstract
Lindauer, Marius, Jan N. van Rijn, and Lars Kotthoff, eds. Proceedings of the Open Algorithm Selection Challenge. Vol. 79. Proceedings of Machine Learning Research. PMLR, 2017. bibTeX
———. “Open Algorithm Selection Challenge 2017: Setup and Scenarios.” In Proceedings of the Open Algorithm Selection Challenge, 79:1–7. Proceedings of Machine Learning Research. Brussels, Belgium: PMLR, 2017. preprint PDF bibTeX abstract
Fawcett, Chris, Lars Kotthoff, and Holger H. Hoos. “Hot-Rodding the Browser Engine: Automatic Configuration of JavaScript Compilers.” CoRR abs/1707.04245 (2017). preprint PDF bibTeX
Fréchette, Alexandre, Lars Kotthoff, Talal Rahwan, Holger H. Hoos, Kevin Leyton-Brown, and Tomasz P. Michalak. “Using the Shapley Value to Analyze Algorithm Portfolios.” In 30th AAAI Conference on Artificial Intelligence, 3397–3403, 2016. preprint PDF bibTeX abstract
Bischl, Bernd, Pascal Kerschke, Lars Kotthoff, Marius Lindauer, Yuri Malitsky, Alexandre Fréchette, Holger H. Hoos, et al. “ASlib: A Benchmark Library for Algorithm Selection.” Artificial Intelligence Journal (AIJ), no. 237 (2016): 41–58. preprint PDF bibTeX abstract
Kotthoff, Lars, Ciaran McCreesh, and Christine Solnon. “Portfolios of Subgraph Isomorphism Algorithms.” In LION 10, 2016. preprint PDF bibTeX abstract
Bischl, Bernd, Michel Lang, Lars Kotthoff, Julia Schiffner, Jakob Richter, Erich Studerus, Giuseppe Casalicchio, and Zachary M. Jones. “Mlr: Machine Learning in R.” Journal of Machine Learning Research 17, no. 170 (2016): 1–5. preprint PDF bibTeX abstract
Degroote, Hans, Bernd Bischl, Lars Kotthoff, and Patrick de Causmacker. “Reinforcement Learning for Automatic Online Algorithm Selection - an Empirical Study.” In ITAT, 1649:93–101. CEUR Workshop Proceedings, 2016. preprint PDF bibTeX abstract
Bessière, Christian, Luc De Raedt, Lars Kotthoff, Siegfried Nijssen, Barry O’Sullivan, and Dino Pedreschi, eds. Data Mining and Constraint Programming: Foundations of a Cross-Disciplinary Approach. 1st ed. Vol. 10101. Lecture Notes in Artificial Intelligence. Springer, 2016. preprint PDF bibTeX abstract
Kotthoff, Lars. “Algorithm Selection for Combinatorial Search Problems: A Survey.” In Data Mining and Constraint Programming: Foundations of a Cross-Disciplinary Approach, edited by Christian Bessiere, Luc De Raedt, Lars Kotthoff, Siegfried Nijssen, Barry O’Sullivan, and Dino Pedreschi, 149–90. Cham: Springer International Publishing, 2016. https://doi.org/10.1007/978-3-319-50137-6_7. bibTeX abstract
Hurley, Barry, Lars Kotthoff, Barry O’Sullivan, and Helmut Simonis. “ICON Loop Health Show Case.” In Data Mining and Constraint Programming: Foundations of a Cross-Disciplinary Approach, edited by Christian Bessiere, Luc De Raedt, Lars Kotthoff, Siegfried Nijssen, Barry O’Sullivan, and Dino Pedreschi, 325–33. Cham: Springer International Publishing, 2016. https://doi.org/10.1007/978-3-319-50137-6_14. bibTeX abstract
Nanni, Mirco, Lars Kotthoff, Riccardo Guidotti, Barry O’Sullivan, and Dino Pedreschi. “ICON Loop Carpooling Show Case.” In Data Mining and Constraint Programming: Foundations of a Cross-Disciplinary Approach, edited by Christian Bessiere, Luc De Raedt, Lars Kotthoff, Siegfried Nijssen, Barry O’Sullivan, and Dino Pedreschi, 310–24. Cham: Springer International Publishing, 2016. https://doi.org/10.1007/978-3-319-50137-6_13. bibTeX abstract
Bessière, Christian, Luc De Raedt, Tias Guns, Lars Kotthoff, Mirco Nanni, Siegfried Nijssen, Barry O’Sullivan, Anastasia Paparrizou, Dino Pedreschi, and Helmut Simonis. “The Inductive Constraint Programming Loop.” In Data Mining and Constraint Programming: Foundations of a Cross-Disciplinary Approach, edited by Christian Bessiere, Luc De Raedt, Lars Kotthoff, Siegfried Nijssen, Barry O’Sullivan, and Dino Pedreschi, 303–9. Cham: Springer International Publishing, 2016. https://doi.org/10.1007/978-3-319-50137-6_12. bibTeX abstract
Hurley, Barry, Lars Kotthoff, Yuri Malitsky, Deepak Mehta, and Barry O’Sullivan. “Advanced Portfolio Techniques.” In Data Mining and Constraint Programming: Foundations of a Cross-Disciplinary Approach, edited by Christian Bessiere, Luc De Raedt, Lars Kotthoff, Siegfried Nijssen, Barry O’Sullivan, and Dino Pedreschi, 191–225. Cham: Springer International Publishing, 2016. https://doi.org/10.1007/978-3-319-50137-6_8. bibTeX abstract
Kotthoff, Lars, Pascal Kerschke, Holger Hoos, and Heike Trautmann. “Improving the State of the Art in Inexact TSP Solving Using Per-Instance Algorithm Selection.” In LION 9, 202–17, 2015. preprint PDF bibTeX abstract
Kotthoff, Lars, Mirco Nanni, Riccardo Guidotti, and Barry O’Sullivan. “Find Your Way Back: Mobility Profile Mining with Constraints.” In CP, 638–53. Cork, Ireland, 2015. preprint PDF bibTeX abstract
Kotthoff, Lars, Barry O’Sullivan, S. S. Ravi, and Ian Davidson. “Complex Clustering Using Constraint Programming: Modelling Electoral Map Creation.” In 14th International Workshop on Constraint Modelling and Reformulation, 2015. preprint PDF bibTeX abstract
Chue Hong, Neil P., Tom Crick, Ian P. Gent, Lars Kotthoff, and Kenji Takeda. “Top Tips to Make Your Research Irreproducible.” CoRR abs/1504.00062 (2015). preprint PDF bibTeX abstract
Kotthoff, Lars. “ICON Challenge on Algorithm Selection.” CoRR abs/1511.04326 (2015). preprint PDF bibTeX
———. “Reliability of Computational Experiments on Virtualised Hardware.” Journal of Experimental and Theoretical Artificial Intelligence 26, no. 1 (2014): 33–49. preprint PDF bibTeX abstract
———. “Algorithm Selection for Combinatorial Search Problems: A Survey.” AI Magazine 35, no. 3 (2014): 48–60. preprint PDF bibTeX abstract
———. “Ranking Algorithms by Performance.” In LION 8, 16–19, 2014. preprint PDF bibTeX
Geschwender, Daniel, Frank Hutter, Lars Kotthoff, Yuri Malitsky, Holger H. Hoos, and Kevin Leyton-Brown. “Algorithm Configuration in the Cloud: A Feasibility Study.” In LION 8, 41–44, 2014. preprint PDF bibTeX
Hurley, Barry, Lars Kotthoff, Yuri Malitsky, and Barry O’Sullivan. “Proteus: A Hierarchical Portfolio of Solvers and Transformations.” In CPAIOR, 301–17, 2014. preprint PDF bibTeX abstract
Kelsey, Thomas W., Lars Kotthoff, Christopher A. Jefferson, Stephen A. Linton, Ian Miguel, Peter Nightingale, and Ian P. Gent. “Qualitative Modelling via Constraint Programming.” Constraints 19, no. 2 (2014): 163–73. preprint PDF bibTeX abstract
Johnson, Peter George, Tina Balke, and Lars Kotthoff. “Integrating Optimisation and Agent-Based Modelling.” In 28th European Conference on Modelling & Simulation. Brescia, Italy, 2014. preprint PDF bibTeX abstract
Hussain, Bilal, Ian P. Gent, Christopher A. Jefferson, Lars Kotthoff, Ian Miguel, Glenna F. Nightingale, and Peter Nightingale. “Discriminating Instance Generation for Automated Constraint Model Selection.” In 20th International Conference on Principles and Practice of Constraint Programming, 356–65. Lyon, France, 2014. preprint PDF bibTeX abstract
Kelsey, Thomas W., Martin McCaffery, and Lars Kotthoff. “Web-Scale Distributed EScience AI Search across Disconnected and Heterogeneous Infrastructures.” In 10th IEEE International Conference on EScience, 39–46. Guarujá, Brazil, 2014. preprint PDF bibTeX abstract
Gent, Ian P., and Lars Kotthoff. “Recomputation.org: Experience of Its First Year and Lessons Learned.” In Recomputability 2014. London, UK, 2014. preprint PDF bibTeX abstract
Kotthoff, Lars. “Algorithm Selection in Practice.” AISB Quarterly, no. 138 (2014): 4–8. preprint PDF bibTeX
Wilson, Nic, and Lars Kotthoff. “Taking into Account Expected Future Bids in EPolicy Optimisation Problem.” Insight Centre for Data Analytics, July 2014. preprint PDF bibTeX
Kotthoff, Lars, and Barry O’Sullivan. “Constraint-Based Clustering.” In 10th International Conference on Integration of Artificial Intelligence (AI) and Operations Research (OR) Techniques in Constraint Programming, 2013. bibTeX abstract
Akgun, Ozgur, Alan M. Frisch, Bilal Hussain, Christopher A. Jefferson, Lars Kotthoff, Ian Miguel, and Peter Nightingale. “An Automated Constraint Modelling and Solving Toolchain.” In 20th Automated Reasoning Workshop, 2013. preprint PDF bibTeX
Prokopas, Arunas, Alan M. Frisch, Ian P. Gent, Christopher A. Jefferson, Lars Kotthoff, Ian Miguel, and Peter Nightingale. “Constructing Constraint Solvers Using Monte Carlo Tree Search.” In 20th Automated Reasoning Workshop, 2013. preprint PDF bibTeX abstract
Kotthoff, Lars. “LLAMA: Leveraging Learning to Automatically Manage Algorithms.” arXiv, June 2013. preprint PDF bibTeX abstract
Hurley, Barry, Lars Kotthoff, Yuri Malitsky, and Barry O’Sullivan. “Proteus: A Hierarchical Portfolio of Solvers and Transformations.” arXiv, June 2013. preprint PDF bibTeX abstract
Akgun, Ozgur, Alan M. Frisch, Ian P. Gent, Bilal Hussain, Christopher A. Jefferson, Lars Kotthoff, Ian Miguel, and Peter Nightingale. “Automated Symmetry Breaking and Model Selection in Conjure.” In 19th International Conference on Principles and Practice of Constraint Programming, 107–16. Uppsala, Sweden, 2013. preprint PDF bibTeX abstract
Mehta, Deepak, Barry O’Sullivan, Lars Kotthoff, and Yuri Malitsky. “Lazy Branching for Constraint Satisfaction.” In ICTAI, 1012–19, 2013. preprint PDF bibTeX abstract
Kotthoff, Lars. “Ranking Algorithms by Performance,” November 2013. preprint PDF bibTeX abstract
Kelsey, Thomas W., Lars Kotthoff, Christopher A. Jefferson, Stephen A. Linton, Ian Miguel, Peter Nightingale, and Ian P. Gent. “Qualitative Modelling via Constraint Programming: Past, Present and Future.” In 18th International Conference on Principles and Practice of Constraint Programming (Position Paper), 2012. preprint PDF bibTeX abstract
Distler, Andreas, Christopher A. Jefferson, Tom Kelsey, and Lars Kotthoff. “The Semigroups of Order 10.” In 18th International Conference on Principles and Practice of Constraint Programming, 883–99, 2012. preprint PDF bibTeX abstract
Kotthoff, Lars, Ian P. Gent, and Ian Miguel. “An Evaluation of Machine Learning in Algorithm Selection for Search Problems.” AI Communications 25, no. 3 (2012): 257–70. preprint PDF bibTeX abstract
Hammond, Gail, Samantha Krause, Lars Kotthoff, and Thomas H. Guderjan. “Continuing Research Using Landscape Archaeology and GIS at Nojol Nah, Belize.” In 77th Annual Meeting of the Society for American Archaeology. Memphis, TN, 2012. preprint PDF bibTeX abstract
Kotthoff, Lars, and Thomas H. Guderjan. “An Interactive Atlas of Maya Sites.” In 77th Annual Meeting of the Society for American Archaeology. Memphis, TN, 2012. preprint PDF bibTeX abstract
Kotthoff, Lars. “On Algorithm Selection, with an Application to Combinatorial Search Problems.” Ph.D., University of St Andrews, 2012. preprint PDF bibTeX abstract
Balasubramaniam, Dharini, Christopher Jefferson, Lars Kotthoff, Ian Miguel, and Peter Nightingale. “An Automated Approach to Generating Efficient Constraint Solvers.” In 34th International Conference on Software Engineering, 661–71, 2012. preprint PDF bibTeX abstract
Kotthoff, Lars. “Hybrid Regression-Classification Models for Algorithm Selection.” In 20th European Conference on Artificial Intelligence, 480–85, 2012. preprint PDF bibTeX abstract
———. “Algorithm Selection for Combinatorial Search Problems: A Survey.” University College Cork, 2012. preprint PDF bibTeX abstract
Kelsey, Tom, and Lars Kotthoff. “Exact Closest String as a Constraint Satisfaction Problem.” In Proceedings of the International Conference on Computational Science, 1062–71, 2011. preprint PDF bibTeX abstract
Kotthoff, Lars, Ian P. Gent, and Ian Miguel. “A Preliminary Evaluation of Machine Learning in Algorithm Selection for Search Problems.” In Fourth Annual Symposium on Combinatorial Search, 84–91, 2011. preprint PDF bibTeX abstract
Gent, Ian P., Christopher A. Jefferson, Lars Kotthoff, and Ian Miguel. “Modelling Constraint Solver Architecture Design as a Constraint Problem.” In Annual ERCIM Workshop on Constraint Solving and Constraint Logic Programming, 87–96, 2011. preprint PDF bibTeX abstract
Gent, Ian P., and Lars Kotthoff. “Reliability of Computational Experiments on Virtualised Hardware.” In AAAI Workshop AI for Data Center Management and Cloud Computing, 2011. preprint PDF bibTeX abstract
Balasubramaniam, Dharini, Lakshitha de Silva, Christopher A. Jefferson, Lars Kotthoff, Ian Miguel, and Peter Nightingale. “Dominion: An Architecture-Driven Approach to Generating Efficient Constraint Solvers.” In 9th Working IEEE/IFIP Conference on Software Architecture, 228–31, 2011. preprint PDF bibTeX abstract
Kotthoff, Lars, and Neil C.A. Moore. “Distributed Solving through Model Splitting.” In 3rd Workshop on Techniques for Implementing Constraint Programming Systems (TRICS), 26–34, 2010. preprint PDF bibTeX abstract
Gent, Ian P., Lars Kotthoff, Ian Miguel, and Peter Nightingale. “Machine Learning for Constraint Solver Design – a Case Study for the Alldifferent Constraint.” In 3rd Workshop on Techniques for Implementing Constraint Programming Systems (TRICS), 13–25, 2010. preprint PDF bibTeX abstract
Kotthoff, Lars, Ian Miguel, and Peter Nightingale. “Ensemble Classification for Constraint Solver Configuration.” In 16th International Conference on Principles and Practices of Constraint Programming, 321–29, 2010. preprint PDF bibTeX abstract
Gent, Ian P., Christopher A. Jefferson, Lars Kotthoff, Ian Miguel, Neil Moore, Peter Nightingale, and Karen E. Petrie. “Learning When to Use Lazy Learning in Constraint Solving.” In 19th European Conference on Artificial Intelligence, 873–78, 2010. preprint PDF bibTeX abstract
Kotthoff, Lars, Ian P. Gent, and Ian Miguel. “Using Machine Learning to Make Constraint Solver Implementation Decisions.” In SICSA PhD Conference, 2010. preprint PDF bibTeX abstract
Kotthoff, Lars. “Constraint Solvers: An Empirical Evaluation of Design Decisions.” CIRCA preprint. University of St Andrews, Centre for Interdisciplinary Research in Computational Algebra, 2009. preprint PDF bibTeX abstract
Gent, Ian P., Christopher A. Jefferson, Lars Kotthoff, Ian Miguel, and Peter Nightingale. “Specification of the Dominion Input Language Version 0.1.” University of St Andrews, 2009. preprint PDF bibTeX
Kotthoff, Lars. “Dominion – A Constraint Solver Generator.” In Doctoral Program of CP, 2009. preprint PDF bibTeX abstract
———. “Using Constraints to Render Websites — Applications of Artificial Intelligence in E-Commerce Environments.” Diplom, University of Leipzig, 2007. preprint PDF bibTeX abstract
Maintainer of the FSelector R package.
Author and maintainer of LLAMA, an R package to simplify common algorithm selection tasks such as training a classifier as portfolio selector.
Core contributor to the mlr R package (Github) for all things machine learning in R.
Leading the Auto-WEKA project, which brings automated machine learning to WEKA.
NSF award 1813537, Robust Performance Models ($412,000).
Outstanding PC award at AAAI 2018.
I have been awarded €3,000 funding from Artificial Intelligence Journal for the
I was awarded a University of Wyoming Global Engagement Office travel grant worth $2000.
My collaborators and I have won the Best Paper Award at the Computational Intelligence and Data Mining workshop at the ITAT conference 2016.
I was awarded an EPSRC Doctoral Prize.
My collaborators and I have won the Best Student Paper Prize at the Symposium on Combinatorial Search 2011.
Apart from my main affiliation, I am a research associate with the Maya Research Program. If I'm not in the office, it's possible that you can find me in the jungle of Belize excavating and/or mapping Maya ruins. Check out the interactive map.
I am also involved with the OpenML project project and a core contributor to ASlib, the benchmark library for algorithm selection.
While you're here, have a look at my overview of the Algorithm Selection literature. For something more visual, have a look at my pictures on Flickr.