Babak Hodjat
Collaborator
Babak is CTO of AI at Cognizant. He has a PhD from Kuyshu University in 2003.
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Discovering Effective Policies for Land-Use Planning with Neuroevolution 2024
Risto Miikkulainen, Olivier Francon, Daniel Young, Elliot Meyerson, Clemens Schwingshackl, Jacob Bieker, Hugo Cunha, and Babak Hodjat, arXiv:2311.12304 (2024). (A shorter version appeared in the Proceedings of the NeurIPS 2023 Workshop: Tackling Climate Change with Machine Learning).
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.
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.
Evolution of Transparent Explainable Rule-sets 2022
Hormoz Shahrzad, Babak Hodjat, and Risto Miikkulainen, arXiv:2204.10438 (2022).
From Prediction to Prescription: Evolutionary Optimization of Non-Pharmaceutical Interventions in the COVID-19 Pandemic 2021
Risto Miikkulainen, Olivier Francon, Elliot Meyerson, Xin Qiu, Darren Sargent, Elisa Canzani, Babak Hodjat, To Appear In IEEE Transactions on Evolutionary Computation, Vol. 25 (2021), pp. 386-401.
Ascend by Evolv: AI-Based Massively Multivariate Conversion Rate Optimization 2020
Risto Miikkulainen, Myles Brundage, Jonathan Epstein, Tyler Foster, Babak Hodjat, Neil Iscoe, Jingbo Jiang, Diego Legrand, Sam Nazari, Xin Qiu, Michael Scharff, Cory Schoolland, Robert Severn, Aaron Shagrin, AI Magazine, Vol. 41 (2020), pp. 44-60.
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.
Better Future through AI: Avoiding Pitfalls and Guiding AI Towards its Full Potential 2019
Risto Miikkulainen, Bret Greenstein, Babak Hodjat, Jerry Smith, arxiv:1905.13178 (2019).
Evolutionary Neural AutoML for Deep Learning 2019
Jason Liang, Elliot Meyerson, Babak Hodjat, Dan Fink, Karl Mutch, and Risto Miikkulainen, In Proceedings of the Genetic and Evolutionary Computation Conference (GECCO-2019), pp. 401–409 2019.
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...
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.
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..
Currently affiliated with Neural Networks