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\n  \n 2026\n \n \n (2)\n \n \n
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\n \n\n \n \n \n \n \n \n Canonical Bayesian System Identification.\n \n \n \n \n\n\n \n Bryutkin, A.; Levine, M. H.; Urteaga, I.; and Marzouk, Y. M.\n\n\n \n\n\n\n May 2026.\n \n\n\n\n
\n\n\n\n \n \n \"CanonicalPaper\n  \n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@Conference{Bryutkin2026,\n  author    = {Andrey Bryutkin and Matthew H. Levine and I{\\~n}igo Urteaga and Youssef M. Marzouk},\n  booktitle = {{SIAM Conference on Uncertainty Quantification (UQ26)}},\n  title     = {{Canonical Bayesian System Identification}},\n  year      = {2026},\n  month     = may,\n  url       = {https://www.siam.org/media/xygnvalm/uq26_abstracts.pdf},\n}\n\n
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\n \n\n \n \n \n \n \n \n A Unified Probabilistic Programming Frameworkfor State Estimation and Dynamics Discovery.\n \n \n \n \n\n\n \n Levine, M. H.; and Urteaga, I.\n\n\n \n\n\n\n May 2026.\n \n\n\n\n
\n\n\n\n \n \n \"APaper\n  \n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@Conference{Levine2026a,\n  author    = {Matthew H. Levine and I{\\~n}igo Urteaga},\n  booktitle = {{SIAM Conference on Uncertainty Quantification (UQ26)}},\n  title     = {{A Unified Probabilistic Programming Frameworkfor State Estimation and Dynamics Discovery}},\n  year      = {2026},\n  month     = may,\n  url       = {https://www.siam.org/media/xygnvalm/uq26_abstracts.pdf},\n}\n\n
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\n  \n 2025\n \n \n (2)\n \n \n
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\n \n\n \n \n \n \n \n Enhancing the Perceived Quality of Task-Oriented Chatbots: Can In-Context Reinforcement Learning be a Breakthrough?.\n \n \n \n\n\n \n Lee, C.; Mamykina, L.; and Urteaga, I.\n\n\n \n\n\n\n October 2025.\n \n\n\n\n
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@Conference{Lee205,\n  author       = {Changhun Lee and Lena Mamykina and I{\\~n}igo Urteaga},\n  booktitle    = {{INFORMS Workshop on Data Science 2025}},\n  title        = {{Enhancing the Perceived Quality of Task-Oriented Chatbots: Can In-Context Reinforcement Learning be a Breakthrough?}},\n  year         = {2025},\n  month        = oct,\n  organization = {INFORMS College on Artificial Intelligence},\n}\n\n
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\n \n\n \n \n \n \n \n Instance generation for maximum independent set using graph generative models.\n \n \n \n\n\n \n Pérez, I.; Uribe, J. C.; and Urteaga, I.\n\n\n \n\n\n\n May 2025.\n \n\n\n\n
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@Conference{Perez2025,\n  author    = {Iker P\\'erez and Josu Ceberio Uribe and I{\\~n}igo Urteaga},\n  booktitle = {{XVI Congreso Espa{\\~n}ol de Metaheur\\'isticas, Algoritmos Evolutivos y Bioinspirados:(MAEB 2025)}},\n  title     = {{Instance generation for maximum independent set using graph generative models}},\n  year      = {2025},\n  month     = may,\n}\n\n
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\n  \n 2024\n \n \n (1)\n \n \n
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\n \n\n \n \n \n \n \n Data-assimilation meets automatic dierentiation for identication of dynamical systems from irregularly-sampled, noisy data.\n \n \n \n\n\n \n Levine, M.; and Urteaga, I.\n\n\n \n\n\n\n June 2024.\n \\textttOral presentation\n\n\n\n
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@Conference{Levine2024,\n  author       = {Matthew Levine and I{\\~n}igo Urteaga},\n  booktitle    = {{XXVIII Congress of Differential Equations and Applications (CEDYA) \\& XVIII Congress of Applied Mathematics (CMA)}},\n  title        = {{Data-assimilation meets automatic dierentiation for identication of dynamical systems from irregularly-sampled, noisy data}},\n  year         = {2024},\n  month        = jun,\n  note         = {\\texttt{\\textit{Oral presentation}}},\n  organization = {Spanish Society of Applied Mathematics (SeMA)},\n}\n\n
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\n  \n 2022\n \n \n (4)\n \n \n
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\n \n\n \n \n \n \n \n Human-Centered Reinforcement Learning for Personalized Self-Management Strategies.\n \n \n \n\n\n \n Urteaga, I.; and Elhadad, N.\n\n\n \n\n\n\n May 2022.\n \n\n\n\n
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@Conference{c-Urteaga2022d,\n  author    = {I{\\~n}igo Urteaga and No\\'{e}mie Elhadad},\n  booktitle = {CHI 2022 Workshop ``Grand Challenges for Personal Informatics and AI''},\n  title     = {{Human-Centered Reinforcement Learning for Personalized Self-Management Strategies}},\n  year      = {2022},\n  month     = may,\n}\n\n
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\n \n\n \n \n \n \n \n Sequential Monte Carlo for Multi-Armed Bandit Agents.\n \n \n \n\n\n \n Urteaga, I.; and Wiggins, C. H.\n\n\n \n\n\n\n April 2022.\n \n\n\n\n
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@Conference{c-Urteaga2022c,\n  author    = {I{\\~n}igo Urteaga and Chris H. Wiggins},\n  booktitle = {5th Workshop on Sequential Monte Carlo Methods},\n  title     = {{Sequential Monte Carlo for Multi-Armed Bandit Agents}},\n  year      = {2022},\n  month     = apr,\n}\n\n
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\n \n\n \n \n \n \n \n Gaussian Process Thompson sampling for Bayesian optimization of dynamic masking-based language model pre-training.\n \n \n \n\n\n \n Urteaga, I.; Draïdia, M.; Lancewicki, T.; and Khadivi, S.\n\n\n \n\n\n\n December 2022.\n \n\n\n\n
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@Conference{c-Urteaga2022a,\n  author    = {I{\\~n}igo Urteaga and Moulay-Za\\"idane Dra\\"idia and Tomer Lancewicki and Shahram Khadivi},\n  booktitle = {NeurIPS 2022 Workshop ``Gaussian Processes, Spatiotemporal Modeling, and Decision-making Systems''},\n  title     = {{Gaussian Process Thompson sampling for Bayesian optimization of dynamic masking-based language model pre-training}},\n  year      = {2022},\n  month     = dec,\n}\n\n
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\n \n\n \n \n \n \n \n Thompson sampling for interactive Bayesian optimization of dynamic masking-based language model pre-training.\n \n \n \n\n\n \n Urteaga, I.; Draïdia, M.; Lancewicki, T.; and Khadivi, S.\n\n\n \n\n\n\n December 2022.\n \\textttLightning Talk\n\n\n\n
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@Conference{c-Urteaga2022b,\n  author    = {I{\\~n}igo Urteaga and Moulay-Za\\"idane Dra\\"idia and Tomer Lancewicki and Shahram Khadivi},\n  booktitle = {EMNLP 2022 Workshop ``Novel Ideas in Learning-to-Learn through Interaction'' (NILLI)},\n  title     = {{Thompson sampling for interactive Bayesian optimization of dynamic masking-based language model pre-training}},\n  year      = {2022},\n  month     = dec,\n  note      = {\\texttt{\\textit{Lightning Talk}}},\n}\n\n
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\n  \n 2020\n \n \n (2)\n \n \n
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\n \n\n \n \n \n \n \n A generative, predictive model for menstrual cycle lengths that accounts for potential self-tracking artifacts in mobile health data.\n \n \n \n\n\n \n Li, K.; Urteaga, I.; Shea, A.; Vitzthum, V.; Wiggins, C. H; and Elhadad, N.\n\n\n \n\n\n\n 2020.\n \\textttSpotlight talk, Health Sciences track\n\n\n\n
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@Conference{c-Li2020b,\n  author    = {Kathy Li and I{\\~n}igo Urteaga and Amanda Shea and Virginia Vitzthum and Chris H Wiggins and No\\'{e}mie Elhadad},\n  title     = {{A generative, predictive model for menstrual cycle lengths that accounts for potential self-tracking artifacts in mobile health data}},\n  booktitle = {Machine Learning in Science \\& Engineering (MLSE2020)},\n  year      = {2020},\n  note      = {\\texttt{\\textit{Spotlight talk}}, Health Sciences track},\n}\n\n
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\n \n\n \n \n \n \n \n \n A generative, predictive model for menstrual cycle lengths that accounts for potential self-tracking artifacts in mobile health data.\n \n \n \n \n\n\n \n Li, K.; Urteaga, I.; Shea, A.; Vitzthum, V.; Wiggins, C. H; and Elhadad, N.\n\n\n \n\n\n\n 2020.\n \\textttContributed Talk\n\n\n\n
\n\n\n\n \n \n \"APaper\n  \n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@Conference{c-Li2020a,\n  author    = {Kathy Li and I{\\~n}igo Urteaga and Amanda Shea and Virginia Vitzthum and Chris H Wiggins and No\\'{e}mie Elhadad},\n  booktitle = {NeurIPS 2020 Workshop ``Machine Learning for Mobile Health''},\n  title     = {{A generative, predictive model for menstrual cycle lengths that accounts for potential self-tracking artifacts in mobile health data}},\n  year      = {2020},\n  note      = {\\texttt{\\textit{Contributed Talk}}},\n  url       = {https://drive.google.com/open?id=1DKf8RBEtjzWOf8JMRdAcaT6iO3ZS5FSt},\n}\n\n
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\n \n\n \n \n \n \n \n Sequential Monte Carlo for Dynamic Softmax Bandits.\n \n \n \n\n\n \n Urteaga, I.; and Wiggins, C. H.\n\n\n \n\n\n\n 2018.\n \n\n\n\n
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@Conference{c-Urteaga2018a,\n  author    = {I{\\~n}igo Urteaga and Chris H. Wiggins},\n  title     = {{Sequential Monte Carlo for Dynamic Softmax Bandits}},\n  booktitle = {1st Symposium on Advances in Approximate Bayesian Inference (AABI 2018)},\n  year      = {2018},\n}\n\n
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\n \n\n \n \n \n \n \n Nonparametric Gaussian mixture models for the multi-armed contextual bandit.\n \n \n \n\n\n \n Urteaga, I.; and Wiggins, C. H.\n\n\n \n\n\n\n 2018.\n \n\n\n\n
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@Conference{c-Urteaga2018b,\n  author    = {I{\\~n}igo Urteaga and Chris H. Wiggins},\n  title     = {{Nonparametric Gaussian mixture models for the multi-armed contextual bandit}},\n  booktitle = {NeurIPS 2018 Workshop ``All of Bayesian Nonparametrics (Especially the Useful Bits)''},\n  year      = {2018},\n}\n\n
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\n \n\n \n \n \n \n \n Bandits with sequentially observed rewards: a Bayesian generative Thompson sampling approach.\n \n \n \n\n\n \n Urteaga, I.; and Wiggins, C. H.\n\n\n \n\n\n\n 2018.\n \n\n\n\n
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@Conference{c-Urteaga2018c,\n  author    = {I{\\~n}igo Urteaga and Chris H. Wiggins},\n  title     = {{Bandits with sequentially observed rewards: a Bayesian generative Thompson sampling approach}},\n  booktitle = {NeurIPS 2018 Workshop ``Reinforcement Learning under Partial Observability''},\n  year      = {2018},\n}\n\n
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\n \n\n \n \n \n \n \n \n Towards Personalized Modeling of the Female Hormonal Cycle: Experiments with Mechanistic Models and Gaussian Processes.\n \n \n \n \n\n\n \n Urteaga, I.; Albers, D. J.; Wheeler, M. V.; Druet, A.; Raffauf, H.; and Elhadad, N.\n\n\n \n\n\n\n 2017.\n \n\n\n\n
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@Conference{c-Urteaga2017b,\n  author        = {I{\\~n}igo Urteaga and David J. Albers and Marija Vlajic Wheeler and Anna Druet and Hans Raffauf and No\\'{e}mie Elhadad},\n  title         = {{Towards Personalized Modeling of the Female Hormonal Cycle: Experiments with Mechanistic Models and Gaussian Processes}},\n  booktitle     = {NeurIPS 2017 Workshop ``Machine Learning for Health''},\n  year          = {2017},\n  url           = {https://arxiv.org/abs/1712.00117},\n}\n\n
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