cv scholar github linkedin publications
I am a researcher with an affinity for physics, computer science and mathematics. I enjoy building things and solving problems. As an undergraduate at Univeristy of Colorado, I studied adiabatic quantum computation and category theory. My Ph.D. thesis at Tulane focused on time-series analysis and machine learning in a high-dimensional setting. My overarching interest revolves around tackling problems within the domain deep learning and explainable AI.
a few of my interests
random matrix theory time series analysis graph theory machine learning mult-agent LLMs RAG systems skateboarding music cooking
publications
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On the empirical spectral distribution of large wavelet random matrices based on mixed-Gaussian fractional measurements in moderately high dimensions
Orejola, O., Didier, G., Wendt, H. and Abry, P. submitted: arXiv preprint (2024) |
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Identifying high-dimensional self-similarity based on spectral clustering applied to large wavelet random matrices
Orejola, O., Didier, G., Wendt, H., and Abry, P. to appear in 32th European Signal Processing Conference (EUSIPCO) (2024) |
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Bootstrap based test for the unimodality of estimated Hurst exponents. Performance assessment in high-dimensional analysis setting
Lucas, C.G., Wendt, H., Abry, P.,Didier, G., and Orejola, O., XXIXème Colloque Francophone de Traitement du Signal et des Images (GRETSI) (2023) |
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Shhh! The Logic of Clandestine Operations
Naumov, P., Oliver, O. 32nd International Joint Conference on Artificial Intelligence (IJCAI) (2023) |
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Hurst multimodality detection based on large wavelet random matrices
Didier, G., Orejola, O., Wendt, H., and Abry, P. 30th European Signal Processing Conference (EUSIPCO) (2022) |