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Paola Cascante Bonilla

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Paola Cascante Bonilla

    20192026

    Research activity per year

    Personal profile

    Biography

    Paola Cascante-Bonilla is a tenure-track Assistant Professor in the Department of Computer Science at Stony Brook University (SUNY). Before that, she was a Postdoctoral Associate at the University of Maryland Institute for Advanced Computer Studies (UMIACS), working with Professor Hal Daumé III, developing methods and metrics related to trustworthy machine learning. She received her Ph.D. in Computer Science at Rice University in 2024, advised by Professor Vicente Ordóñez Román, working on Computer Vision, Natural Language Processing, and Machine Learning. She is the recipient of the Ken Kennedy Institute SLB Graduate Fellowship (2022/23), and was selected as a Future Faculty Fellow by Rice's George R. Brown School of Engineering (2023) and as a Rising Star in EECS (2023). She received a Master of Computer Science at the University of Virginia and a B.S. in Engineering at the Tecnológico de Costa Rica. Previously, she interned at the Mitsubishi Electric Research Laboratories (MERL) and twice at the MIT-IBM Watson AI Lab.Before that, she spent 10 years working as a Software Engineer at different tech companies.

    Research interests

    Vision and Language & Multi-modal learning:

    Zero/few-shot learning, representation learning, continual learning.
    Visual-question answering, crossmodal retrieval, multi-hop reasoning.

    Synthetic data generation for compositionality and privacy protection:

    Simulated environments to provide a safe, controlled setting where agents can learn.
    Virtual playgrounds that allow systems to experience and interact within the 3D space.

    Dynamic evaluations and real-world applications:

    Data distribution and mitigation of spurious correlations.
    Assessing the performance and effectiveness of models under varying conditions.
    • Computer Vision, Natural Language Processing, Machine Learning.
    • Compositional reasoning and common-sense inference through vision and language.
    • Data distribution, explainability and trustworthy AI.

    Resources

    Education/Academic qualification

    PhD, Computer Science, Rice University

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    • 12 Conference contribution
    • 1 Paper
    • 1 Conference article

    • Can Hallucination Correction Improve Video-Language Alignment?

      Zhao, L., Xie, M., Cascante-Bonilla, P., Daumé, H. & Lee, K., 2025, Findings of the Association for Computational Linguistics: ACL 2025. Che, W., Nabende, J., Shutova, E. & Pilehvar, M. T. (eds.). Association for Computational Linguistics (ACL), p. 25636-25646 11 p. (Proceedings of the Annual Meeting of the Association for Computational Linguistics).

      Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

    • Grounding Language Models for Visual Entity Recognition

      Xiao, Z., Gong, M., Cascante-Bonilla, P., Zhang, X., Wu, J. & Ordonez, V., 2025, Computer Vision – ECCV 2024 - 18th European Conference, Proceedings. Leonardis, A., Ricci, E., Roth, S., Russakovsky, O., Sattler, T. & Varol, G. (eds.). Springer Science and Business Media Deutschland GmbH, p. 393-411 19 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) ; vol. 15069 LNCS).

      Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

      3 Scopus citations

    • NATURAL LANGUAGE INFERENCE IMPROVES COMPOSITIONALITY IN VISION-LANGUAGE MODELS

      Cascante-Bonilla, P., Hou, Y., Cao, Y. T., Daumé, H. & Rudinger, R., 2025, 13th International Conference on Learning Representations, ICLR 2025. International Conference on Learning Representations, ICLR, p. 37583-37604 22 p. (13th International Conference on Learning Representations, ICLR 2025).

      Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

      2 Scopus citations

    • Improved Visual Grounding through Self-Consistent Explanations

      He, R., Cascante-Bonilla, P., Yang, Z., Berg, A. C. & Ordonez, V., 2024, Proceedings - 2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition, CVPR 2024. IEEE Computer Society, p. 13095-13105 11 p. (Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition).

      Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

      20 Scopus citations

    • PropTest: Automatic Property Testing for Improved Visual Programming

      Koo, J., Yang, Z., Cascante-Bonilla, P., Ray, B. & Ordonez, V., 2024, EMNLP 2024 - 2024 Conference on Empirical Methods in Natural Language Processing, Findings of EMNLP 2024. Al-Onaizan, Y., Bansal, M. & Chen, Y.-N. (eds.). Association for Computational Linguistics (ACL), p. 8241-8256 16 p. (EMNLP 2024 - 2024 Conference on Empirical Methods in Natural Language Processing, Findings of EMNLP 2024).

      Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

      Open Access
      6 Scopus citations
    View all 14 Research outputs