La Cava, W., Lee, P.C., Ajmal, I., Ding, X., Cohen, J.B., Solanki, P., Moore, J.H., and Herman, D.S (2020). Application of concise machine learning to construct accurate and interpretable EHR computable phenotypes. In Review. medRxiv

La Cava, W. & Moore, Jason H. (2020). Genetic programming approaches to learning fair classifiers. GECCO 2020. Best Paper Award. ACM. arXiv

La Cava, W., Williams, H., Fu, W., Vitale, S., Srivatsan, D., Moore, J. H. (2020). Evaluating recommender systems for AI-driven biomedical informatics. Bioinformatics. open access

Bartz-Beielstein, T., Doerr, C., Berg, D. van den, Bossek, J., Chandrasekaran, S., Eftimov, T., Fischbach, A., Kerschke, P., La Cava, W., Lopez-Ibanez, M., Malan, K. M., Moore, J. H., Naujoks, B., Orzechowski, P., Volz, V., Wagner, M., & Weise, T. (2020). Benchmarking in Optimization: Best Practice and Open Issues. arXiv

Le, T. T., La Cava, W., Romano, J. D., Gregg, J. T., Goldberg, D. J., Chakraborty, P., Ray, N. L., Himmelstein, D., Fu, W., & Moore, J. H. (2020). PMLB v1.0: An open source dataset collection for benchmarking machine learning methods. arXiv

La Cava, W. & Moore, J.H. (2020). Learning feature spaces for regression with genetic programming. Genetic Programming and Evolvable Machines (GPEM). link, pdf


La Cava, W., Bauer, C. R., Moore, J. H., & Pendergrass, S. A. (2019). Interpretation of machine learning predictions for patient outcomes in electronic health records. AMIA 2019 Annual Symposium. arXiv

La Cava, W., & Moore, J. H. (2019). Semantic variation operators for multidimensional genetic programming. GECCO 2019. https://doi.org/10.1145/3321707.3321776. arXiv

La Cava, W., & Moore, J. H. (2019). Learning concise representations for regression by evolving networks of trees. ICLR 2019. arXiv

Wojcieszynski Jr, A. P., La Cava, W., Baumann, B. C., Lukens, J. N., Fotouhi Ghiam, A., Urbanowicz, R. J., … Metz, J. M. (2019). Machine Learning to Predict Toxicity in Head and Neck Cancer Patients Treated with Definitive Chemoradiation. International Journal of Radiation Oncology • Biology • Physics. link, pdf

La Cava, W., Silva, S., Danai, K., Spector, L., Vanneschi, L., & Moore, J. H. (2019). Multidimensional genetic programming for multiclass classification. Swarm and Evolutionary Computation. https://doi.org/10.1016/j.swevo.2018.03.015. Preprint


La Cava, W., Helmuth, T., Spector, L., & Moore, J. H. (2018). A probabilistic and multi-objective analysis of lexicase selection and epsilon-lexicase selection. Evolutionary Computation, 1–28. https://doi.org/10.1162/evco_a_00224. arXiv

La Cava, W., & Moore, J. H. (2018). An Analysis of epsilon-lexicase Selection for Large-scale Many-objective Optimization. GECCO 2018 Companion. https://doi.org/10.1145/3205651.3205656.

La Cava, W., & Moore, J. H. (2018). Behavioral search drivers and the role of elitism in soft robotics. Artificial Life, 206–213. MIT Press. https://doi.org/10.1162/isal_a_00044. MIT Pdf

Orzechowski, P., La Cava, W., & Moore, J. H. (2018). Where are we now? A large benchmark study of recent symbolic regression methods. GECCO 2018. https://doi.org/10.1145/3205455.3205539. arXiv

Urbanowicz, R. J., Meeker, M., La Cava, W., Olson, R. S., & Moore, J. H. (2018). Relief-based feature selection: Introduction and review. Journal of Biomedical Informatics, 85, 189 – 203. https://doi.org/10.1016/j.jbi.2018.07.014. arXiv


La Cava, W., & Moore, J. H. (2017). A general feature engineering wrapper for machine learning using ϵ-lexicase survival. European Conference on Genetic Programming, 80–95. https://doi.org/10.1007/978-3-319-55696-3_6. Preprint

La Cava, W., & Moore, J. H. (2017). Ensemble representation learning: An analysis of fitness and survival for wrapper-based genetic programming methods. GECCO 2017. arXiv

La Cava, W., Sahare, K., & Danai, K. (2017). Restructuring Controllers to Accommodate Plant Nonlinearities. Journal of Dynamic Systems, Measurement, and Control, 139(8), 081004–081004–10. https://doi.org/10.1115/1.4035870. Preprint

La Cava, W., Silva, S., Vanneschi, L., Spector, L., & Moore, J. (2017). Genetic Programming Representations for Multi-dimensional Feature Learning in Biomedical Classification. EvoStar Applications of Evolutionary Computation, 10199, 158–173. https://doi.org/10.1007/978-3-319-55849-3_11. Preprint

Olson, R. S., La Cava, W., Orzechowski, P., Urbanowicz, R. J., & Moore, J. H. (2017). PMLB: A Large Benchmark Suite for Machine Learning Evaluation and Comparison. BioData Mining. arXiv

Olson, R. S., La Cava, William, Mustahsan, Z., Varik, A., & Moore, J. H. (2017). Data-driven Advice for Applying Machine Learning to Bioinformatics Problems. Pacific Symposium on Biocomputing (PSB). arXiv


La Cava, W., Danai, K., & Spector, L. (2016). Inference of compact nonlinear dynamic models by epigenetic local search. Engineering Applications of Artificial Intelligence, 55, 292–306. https://doi.org/10.1016/j.engappai.2016.07.004. Preprint

La Cava, W., Spector, L., & Danai, K. (2016). Epsilon-Lexicase Selection for Regression. GECCO 2016. https://doi.org/10.1145/2908812.2908898. arXiv

Park, S., Lackner, M. A., Cross-Whiter, J., Tsouroukdissian, A. R., & La Cava, W. (2016). An Investigation of Passive and Semi-Active Tuned Mass Dampers for a Tension Leg Platform Floating Offshore Wind Turbine in ULS Conditions. ASME 2016 35th International Conference on Ocean, Offshore and Arctic Engineering, V003T02A061–V003T02A061. American Society of Mechanical Engineers. OSTI

Rodriguez Tsouroukdissian, A., Lackner, M., Cross-Whiter, J., Park, S. M., Pourazarm, P., La Cava, W., & Lee, S. (2016). Smart Novel Semi-Active Tuned Mass Damper for Fixed-Bottom and Floating Offshore Wind. Offshore Technology Conference. U.S. DOE Office of Science and Technical Information. OSTI


Guo, Y., Keller, J., La Cava, W., Austin, J., Nejad, A., Halse, C., … Helsen, J. (2015). Recommendations on Model Fidelity for Wind Turbine Gearbox Simulations. Conference for Wind Power Drives (CWD) 2015. NREL Preprint

La Cava, W., & Danai, K. (2015). Gradient-based adaptation of continuous dynamic model structures. International Journal of Systems Science, 47(1), 249–263. https://doi.org/10.1080/00207721.2015.1069905. Preprint

La Cava, W., & Danai, K. (2015). Model Structure Adaptation: A Gradient-based Approach. ASME 2015 Dynamic Systems and Control Conference. ASME.

La Cava, W., Danai, K., Spector, L., Fleming, P., Wright, A. D., & Lackner, M. (2015). Automated Identification of Closed-Loop Wind Turbine Dynamics via Genetic Programming. ASME 2015 Dynamic Systems and Control Conference. ASME.

La Cava, W., Danai, K., Spector, L., Fleming, P., Wright, A., & Lackner, M. (2015). Automatic identification of wind turbine models using evolutionary multiobjective optimization. Renewable Energy. https://doi.org/10.1016/j.renene.2015.09.068. Preprint

La Cava, W., Helmuth, T., Spector, L., & Danai, K. (2015). Genetic Programming with Epigenetic Local Search. GECCO 2015. https://doi.org/10.1145/2739480.2754763. Preprint


Guo, Y., Keller, J., & La Cava, W. (2014). Planetary gear load sharing of wind turbine drivetrains subjected to non-torque loads. Wind Energy, 18, 757–768. https://doi.org/10.1002/we.1731. Preprint

La Cava, W., Spector, L., Danai, K., & Lackner, M. (2014). Evolving differential equations with developmental linear genetic programming and epigenetic hill climbing. GECCO 2014 Companion. https://doi.org/10.1145/2598394.2598491.


La Cava, W., Guo, Y., Marks, C., Xing, Y., & Moan, T. (2013). Three-dimensional bearing load share behaviour in the planetary stage of a wind turbine gearbox. IET Renewable Power Generation, 7(4), 359–369. https://doi.org/10.1049/iet-rpg.2012.0274. Preprint


Guo, Y., Keller, J., & La Cava, W. (2012). Combined effects of gravity, bending moment, bearing clearance, and input torque on wind turbine planetary gear load sharing. AGMA Fall Technical Meeting. AGMA. NREL Preprint

Keller, J., Link, H. F., Guo, Y., La Cava, W., & McNiff, B. P. (2012). Gearbox reliability collaborative phase 1 and 2: Testing and modelling results. Conference Proceedings of ISMA2012-USD2012. Presented at the International Conference on Noise and Vibration engineering, Leuven, Belgium. ICNVA Pdf

La Cava, W., Keller, J., & McNiff, B. (2012). Gearbox reliability collaborative: Test and model investigation of sun orbit and planet load share in a wind turbine gearbox. AIAA 53rd Structures, Structural Dynamics, and Materials and Colocated Conferences. AIAA Pdf

La Cava, W., Xing, Y., Guo, Y., & Moan, T. (2012). Determining wind turbine gearbox model complexity using measurement validation and cost comparison. EWEA 2012. NREL Preprint


La Cava, W., McNiff, B., & van Dam, J. (2011). NREL Gearbox Reliability Collaborative: Comparing In-field Gearbox Response to Different Dynamometer Test Conditions. AWEA Windpower 2011. NREL Preprint