I am a PhD Candidate in Machine Learning at CentraleSupélec-Université Paris-Saclay working towards trustworthy and robust AI under the supervision of Prof. Pablo Piantanida. My PhD is supported by the BPI France through the IBM Research project AIDA: Artificial Intelligence for Digital Automation. Through my work, I am committed to making AI a beneficial technology for all.
| 2023-11 | I will present on the NeurIPS 2023 Conference Workshop on Mathemathics of Modern Machine Learning. |
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| 2023-07 | Will service as a reviewer for the NeurIPS 2023 Conference. |
| 2023-06 | I was selected to attend to the 2023 edition of the Nordic Probabilistic AI School (ProbAI) being hosted by the Norwegian University of Science and Technology (NTNU) and sponsored by DeepMind. |
| 2023-05 | Together with colleagues, released detectors: open-source library for out-of-distribution detection on computer vision applications. |
| 2023-01 | Together with colleagues, released Todd: open-source library for text out-of-distribution detection built on top of the Huggingface Transformers library. |
| 2022-09 | Our work entitled “Beyond Mahalanobis Distance for Textual OOD Detection” has been accepted to appear in the NeurIPS 2022 Conference. |
| 2022-12 | Will service as a reviewer for the CVPR 2023 Conference. |
| 2022-04 | Gave a talk at a poster session of the NeurIPS 2022 Conference. |
| 2022-11 | Will attend the NeurIPS 2022 Conference in New Orleans, LA, USA. |
| 2019-10 | I am happy to start a research internship at the International Laboratory on Learning Systems (ILLS) in partnership with McGill University, ÉTS Montreal, Mila – Quebec AI Institute, CNRS and Université Paris-Saclay. |
For a complete list, please check my Google Scholar page.
E. Dadalto, P. Colombo, G. Staerman, N. Noiry, and P. Piantanida, “A functional data perspective and baseline on multi-layer out-of-distribution detection.” 2023. Available: https://arxiv.org/abs/2306.03522
E. Dadalto, M. Romanelli, F. Granese, and P. Piantanida, “A simple training-free method for rejection option.” 2023.
E. Dadalto, M. Romanelli, G. Pichler, and P. Piantanida, “A data-driven measure of relative uncertainty for misclassification detection.” 2023. Available: https://arxiv.org/abs/2306.01710
M. Darrin, G. Staerman, E. Dadalto, J. C. Cheung, P. Piantanida, and P. Colombo, “Unsupervised layer-wise score aggregation for textual OOD detection.” 2023. Available: https://arxiv.org/abs/2302.09852
P. Colombo, E. Dadalto, G. Staerman, N. Noiry, and P. Piantanida, “Beyond mahalanobis distance for textual OOD detection,” in Advances in neural information processing systems, 2022. Available: https://proceedings.neurips.cc/paper_files/paper/2022/file/70fa5df8e3300dc30bf19bee44a56155-Paper-Conference.pdf
E. Dadalto, F. Alberge, P. Duhamel, and P. Piantanida, “Igeood: An information geometry approach to out-of-distribution detection,” in International conference on learning representations, 2022. Available: https://openreview.net/forum?id=mfwdY3U_9ea
M. Benammar, E. Dadalto, and P. Piantanida, “CSI-aided robust neural-based decoders,” in 2021 11th international symposium on topics in coding (ISTC), 2021, pp. 1–5. doi: 10.1109/ISTC49272.2021.9594117
You can contact me via email at edadaltocg@gmail.com. Happy to discuss new projects and collaborations.