Chowdhury, Tahiya. “Computational Thinking with Computer Vision: Developing AI Competency in an Introductory Computer Science Course.” Proceedings of the AAAI Conference on Artificial Intelligence vol 39, 2025. https://doi.org/10.48550/arXiv.2503.19006

Chowdhury, Tahiya and Verónica Romero. “Can We Trust Machine Learning? The Reliability of Features from Open-Source Speech Analysis Tools for Speech Modeling.” 2025. https:/doi.org/10.48550/arXiv.2506.11072

Donaldson, Sonya. Interview by John Drabinski. “Episode 47.”  The Black Studies Podcast. 14 October 2024. https://blackstudiespodcast.substack.com/p/sonya-donaldson-department-of-african?utm_source=publication-search

Fan, Chengyu, Verónica Romero, Alexandra Paxton, and Tahiya Chowdhury. “Towards Multimodality: Comparing Quantifications of Movement Coordination.” ICMI Companion ’24: Companion Proceedings of the 26th International Conference on Multimodal Interaction, 2024, pp. 21-25. https://doi.org/10.1145/3686215.3690149

Imai, Saki, Tahiya Chowdhury, and Amanda Stent. “Evaluating Open-Source ASR Systems: Performance Across Diverse Audio Conditions and Error Correction Methods.” Proceedings of the 31st International Conference on Computational Linguistics, pp. 5027-5039, 2025. https://aclanthology.org/2025.coling-main.336/

Margolis, Micah, Anna Mackey, Isabella Kuhr, and Michael Donihue. “Generative AI in Liberal Arts Education: A Comparative Analysis of Student Experiences.” Journal of Writing With and About AI, 2025. https://www.flipsnack.com/99B9EC66AED/jwai-issue2-v2 

Martinez, José.  Prelude V1 – José Martínez (Daniel Perea and Nicolás Molina – virtual performers).” 31 July, 2025. https://www.youtube.com/watch?v=v4IKWoZnKtU&ab_channel=Jos%C3%A9Mart%C3%ADnez

Wang, Raymond, Nicholas R. Record, Whitney D. King, and Tahiya Chowdhury. “Designing a Sustainable Marine Debris Clean-up Framework without Human Labels.” COMPASS ’24: Proceedings of the 7th ACM SIGCAS/SIGCHI Conference on Computing and Sustainable Societies, 2024, pp. 211-219. https://doi.org/10.1145/3674829.3675076

Wang, Ray, Tahiya Chowdhury, and Alejandra C. Ortiz. “Semantic Segmentation Framework for Atoll Satellite Imagery: An In-depth Exploration Using UNet Variants and Segmentation Gym.” Applied Computing and Geosciences vol. 25,  2025. https://doi.org/10.1016/j.acags.2024.100217

Chowdhury, Tahiya, Verónica Romero, and Amanda Stent. “Interactional coordination between conversation part­ners with autism using non-verbal cues in dialogues.” Proceedings of the First Workshop on Connecting Multiple Disciplines to AI Techniques in Interaction-centric Autism Research and Diagnosis (ICARD 2023). 2023.

Chowdhury, Tahiya, Verónica Romero, and Amanda Stent. “Parameter Selection for Analyzing Conversations with Autism Spectrum Disorder.” Proceedings of INTERSPEECH. 2023.

Al Madi, Naser. “How readable is model-generated code? examining readability and visual inspection of github co­pilot.” Proceedings of the 37th IEEE/ACM International Conference on Automated Software Engineering. 2022.

Paxton, Alexandra, Tahiya Chowdhury, and Verónica Romero. “Language in the Time of COVID: Sensitivity of Lin­guistic Alignment to Conversation Type and Communication Modality.” Proceedings of the Annual Meeting of the Cognitive Science Society. Vol. 45. No. 45. 2023.

Raczaszek-Leonardi, Joanna, et al. “Putting interaction center-stage for the study of knowledge structures and processes.” Proceedings of the Annual Meeting of the Cognitive Science Society. Vol. 45. No. 45. 2023.

Good, Aidan, et al. “Recall distortion in neural network pruning and the undecayed pruning algorithm.” Advances in Neural Information Processing Systems 35 (2022): 32762-32776.

Maus, Natalie, and Oliver W. Layton. “Estimating heading from optic flow: Comparing deep learning network and human performance.” Neural Networks 154 (2022): 383-396.

Stent, A., Mann, G., & Kambadur, P. (2023). NLP in Finance. In Machine Learning and Data Sciences for Financial Markets: A Guide to Contemporary Practices (pp. 563–592). chapter, Cambridge University Press.

Good, A., Lin, J., Sieg, H., Fergurson, M., Yu, X., Zhe, S., Wieczorek, J., & Serra, T. (2022). Recall distortion in neural network pruning and the undecayed pruning algorithm. In Proc. NeurIPS. arXiv preprint: https://arxiv.org/abs/2206.02976.

Al Madi, N. (2022) How readable is model-generated code? Examining readability and visual inspection of GitHub Copilot. To appear in Proceedings of ASE 2022.

Li, Y., Li, C., Chen, J., & Roinou, C. (2022) Energy-aware multi-agent reinforcement learning for collaborative execution in mission-oriented drone networks. In Proceedings of IEEE ICCCN.

Layton, O. W., & Fajen, B. R. (2022). Distributed encoding of curvilinear self-motion across spiral optic flow patterns. Scientific Reports, 12(1), 1-15. https://www.nature.com/articles/s41598-022-16371-4

Maus, N., & Layton, O. W. (2022). Estimating heading from optic flow: Comparing deep learning network and human performance. Neural Networks, 154, 383-396. https://doi.org/10.1016/j.neunet.2022.07.007

Layton, O. W., Powell, N., Steinmetz, S. T., & Fajen, B. R. (2022). Estimating curvilinear self-motion from optic flow with a biologically inspired neural system. Bioinspiration & Biomimetics, 17(4), 046013. https://pubmed.ncbi.nlm.nih.gov/35580573/

Steinmetz, S. T., Layton, O. W., Powell, N. V., & Fajen, B. R. (2022). A Dynamic Efficient Sensory Encoding Approach to Adaptive Tuning in Neural Models of Optic Flow Processing. Frontiers in Computational Neuroscience, 16. https://pubmed.ncbi.nlm.nih.gov/35431848/*