Hormoz Shahrzad
Ph.D. Student
Hormoz has worked on many topics in evolutionary computation, both in theory and practice. His master's thesis focused on BLADE, a method for automatically focusing evolutionary search on the most promising part of the genome, with the search distributed over multiple hosts. He is currently a PhD candidate, continuing his research at the Cognizant AI Lab (https://www.cognizant.com/us/en/ai-lab) and as a visiting student researcher at Stanford University, where he is working on his dissertation.
Publications
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Evolutionary Surrogate-Assisted Prescription: Neuro-Symbolic Framework for Trustworthy Decisioning 2025
Hormoz Shahrzad and Risto Miikkulainen, In Proceedings of Machine Learning Research vol 284:1–3, 2025: 19th Conference on Neurosymbolic Learning and Reasoning, 2025.
GPU-Accelerated Rule Evaluation and Evolution 2025
Hormoz Shahrzad and Risto Miikkulainen, In Proceedings of the Genetic and Evolutionary Computation Conference Companion: Workshop on Evolutionary Rule-based Machine Learning, 2025.
NeuroSAN+NeuroAI: AI-assisted Decision-making through a Synergy of Technologies 2025
Risto Miikkulainen, Dan Fink, Olivier Francon, Babak Hodjat, Noravee Kanchanavatee, Elliot Meyerson, Xin Qiu, Darren Sargent, Hormoz Shahrzad, Deepak Singh, Jean Celestin Yamegni Noubeyo, and Daniel Young, Technical Report 2025-01, Cognizant AI Lab.
Asynchronous Evolution of Deep Neural Network Architectures 2024
Jason Liang, Hormoz Shahrzad, Risto Miikkulainen, Applied Soft Computing, Vol. 152 (2024), pp. 111209. Also arXiv:2308:04102.
Domain-Independent Lifelong Problem Solving through Distributed Alife Actors 2024
Babak Hodjat, Hormoz Shahrzad, and Risto Miikkulainen, Artificial Life, Vol. 30 (2024), pp. 359-276.
EVOTER: Evolution of Transparent Explainable Rule-sets 2024
Hormoz Shahrzad, Babak Hodjat, and Risto Miikkulainen, ACM Transactions on Evolutionary Learning and Optimization (2024).
Accelerating Evolution Through Gene Masking and Distributed Search 2023
Hormoz Shahrzad and Risto Miikkulainen, To Appear In Proceedings of the Genetic and Evolutionary Computation Conference, pp. 972-980, 2023. (Also arXiv:2302.06745).
Accelerating Evolution Through Gene Masking and Distributed Search 2023
Hormoz Shahrzad, Masters Thesis, Department of Computer Science, The University of Texas at Austin.
Evolving Deep Neural Networks 2023
Risto Miikkulainen, Jason Liang, Elliot Meyerson, Aditya Rawal, Dan Fink, Olivier Francon, Bala Raju, Hormoz Shahrzad, Arshak Navruzyan, Nigel Duffy, Babak Hodjat, To Appear In Artificial Intelligence in the Age of Neural Networks and Brain Computing (second edition), R. Kozma, C. Alippi, Y. Choe, and F. Morabito (Eds.), New York, 2023. Elsevier.
DIAS: A Domain-Independent Alife-Based Problem-Solving System 2022
Babak Hodjat, Hormoz Shahrzad, Risto Miikkulainen, In Proceedings of the 2022 Conference on Artificial Life, 2022.
Regularized Evolutionary Population-Based Training 2021
Jason Liang, Santiago Gonzalez, Hormoz Shahrzad, and Risto Miikkulainen, In Proceedings of the Genetic and Evolutionary Computation Conference, pp. 323-331, 2021.
Effective Reinforcement Learning through Evolutionary Surrogate-Assisted Prescription 2020
Olivier Francon, Santiago Gonzalez, Babak Hodjat, Elliot Meyerson, Risto Miikkulainen, Xin Qiu, Hormoz Shahrzad, In Proceedings of the Genetic and Evolutionary Computation Conference (GECCO-2020), 2020.
Enhanced Optimization with Composite Objectives and Novelty Pulsation 2020
Hormoz Shahrzad, Babak Hodjat, Camille Dolle, Andrei Denissov, Simon Lau, Donn Goodhew, Justin Dyer, and Risto Miikkulainen, To Appear In Genetic Programming Theory and Practice XVII 2020. Springer, New York.
Evolving Deep Neural Networks 2019
Risto Miikkulainen, Jason Liang, Elliot Meyerson, Aditya Rawal, Dan Fink, Olivier Francon, Bala Raju, Hormoz Shahrzad, Arshak Navruzyan, Nigel Duffy, and Babak Hodjat, In Artificial Intelligence in the Age of Neural Networks and Brain Computing, Robert Kozma, Cesare Alippi, Yoonsuck Choe, and Francesco Carlo Morabito (Eds.), pp. 293-312 2019. Amsterdam: Elsev...
Enhanced Optimization with Composite Objectives and Novelty Selection 2018
Hormoz Shahrzad, Daniel Fink and Risto Miikkulainen, In Proceedings of the 2018 Conference on Artificial Life, Tokyo, Japan 2018.
PRETSL: Distributed Probabilistic Rule Evolution for Time-Series Classification 2018
Babak Hodjat, Hormoz Shahrzad, Risto Miikkulainen, Lawrence Murray, and Chris Holmes, In Genetic Programming Theory and Practice XIV, New York 2018. Springer.
How to Select a Winner in Evolutionary Optimization? 2017
Risto Miikkulainen, Hormoz Shahrzad, Nigel Duffy, and Phil Long, In Proceedings of the IEEE Symposium Series in Computational Intelligence 2017. IEEE.
Distributed Age-Layered Novelty Search 2016
Babak Hodjat, Hormoz Shahrzad, and Risto Miikkulainen, To Appear In Proceedings of the Fifteenth International Conference on the Synthesis and Simulation of Living Systems (Alife'16, Cancun, Mexico) 2016.
Estimating the Advantage of Age-Layering in Evolutionary Algorithms 2016
Hormoz Shahrzad, Babak Hodjat, and Risto Miikkulainen, To Appear In Proceedings of the Genetic and Evolutionary Computation Conference (GECCO-2016, Denver, CO) 2016.
nPool: Massively Distributed Simultaneous Evolution and Cross-Validation in EC-Star 2016
Babak Hodjat, Hormoz Shahrzad, In Genetic Programming Theory and Practice XIII, 2016. Springer, Cham.
Tackling the Boolean Multiplexer Function Using a Highly Distributed Genetic Programming System 2015
Hormoz Shahrzad, Babak Hodjat, In Genetic Programming Theory and Practice XII, Riolo, R., Worzel, W., Kotanchek, M. (Eds.), University of Michigan, Ann Arbor, USA, May 2015. Springer International Publishing Switzerland.
Learning Decision Lists with Lags for Physiological Time Series 2014
Erik Hemberg, Kalyan Veeramachaneni, Prashan Wanigasekara, Hormoz Shahrzad, Babak Hodjat, Una-May O'Reilly, In Workshop on Data Mining for Medicine and Healthcare at the 14th SIAM International Conference on Data Mining, pp. 82-87, 2014.
Maintenance of a Long Running Distributed Genetic Programming System for Solving Problems Requiring Big Data 2014
Babak Hodjat, Erik Hemberg, Hormoz Shahrzad, Una-May O’Reilly, In Genetic Programming Theory and Practice XI, Riolo, R., Moore, J., Kotanchek, M. (Eds.), University of Michigan, Ann Arbor, USA, May 2014. Springer, New York, NY..
Introducing an Age-Varying Fitness Estimation Function 2013
Babak Hodjat, Hormoz Shahrzad , In Genetic Programming Theory and Practice X, Riolo, R., Vladislavleva, E., Ritchie, M., Moore, J. (Eds.), University of Michigan, Ann Arbor, USA, May 2013. Springer, New York, NY..
Areas of Interest
Applications Evolutionary Computation Game Playing Neuroevolution Theory of Evolutionary Computation
Labs
Currently affiliated with Neural Networks