Publications & Preprints 2025 Xavier Mootoo, Hina Tabassum, Luca Chiaraviglio. EMForecaster: A Deep Learning Framework for Time Series Forecasting in Wireless Networks with Distribution-Free Uncertainty Quantification (IEEE Transactions on Network Science and Engineering, under review).Xavier Mootoo, Alan A. Díaz-Montiel, Milad Lankarany, Hina Tabassum. Stochastic Sparse Sampling: A Framework for Variable-Length Medical Time Series Classification (IEEE Transactions on Neural Networks and Learning Systems, under review). 2024 Xavier Mootoo, Alan A. Díaz-Montiel, Milad Lankarany, Hina Tabassum. Stochastic Sparse Sampling: A Framework for Local Explainability in Variable-Length Medical Time Series. NeurIPS 2024 Workshop on Time Series in the Age of Large Models.Mehrazin Alizadeh, Xavier Mootoo, Omer Waqar and Hina Tabassum. QoS-Aware Deep Unsupervised Learning for STAR-RIS Assisted Networks: A Novel Differentiable Projection Framework, in IEEE Wireless Communications Letters, doi: 10.1109/LWC.2024.3413544. 2023 Xavier Mootoo, Alice Fours, Chinthaka Dinesh, Mohammad Ashkani, Adam Kiss, Mateusz Faltyn. Detecting Alzheimer Disease in EEG Data with Machine learning and the Graph Discrete Fourier Transform. medRxiv 2023.11.01.23297940; doi: https://doi.org/10.1101/2023.11.01.23297940 2022 Xavier Mootoo* and Paul Skoufranis*, Joint Majorization in Continuous Matrix Algebras, Journal of Operator Theory (2022). Nantel Bergeron*, Xavier Mootoo*, and Vedarth Vyas*, The Gröbner Basis of a Catalan Path Ideal, Enumerative Combinatorics and Applications 2:3 (2022) Article S2R21. *Indicates equal authorship.