Jhony H. Giraldo

Assistant Professor at Télécom Paris, Institut Polytechnique de Paris

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Office 5D24

19 place Marguerite Perey

91120 Palaiseau, France

I am an Assistant Professor at Télécom Paris, Institut Polytechnique de Paris, working in the Information Processing and Communications Laboratory (LTCI) in the Multimedia team. I’m a member of the ELLIS Society.

My research focuses on the theory and applications of Geometric Deep Learning (graph and higher-order networks), Computer Vision, Machine Learning, and Graph Signal Processing.

I received my Ph.D. in Applied Mathematics from La Rochelle Université (Laboratoire MIA – Mathématiques, Image et Applications) in 2022. During my Ph.D., I was a visiting researcher at the Centre de Vision Numérique (CVN) and Inria OPIS, CentraleSupélec, Université Paris-Saclay (2022), and at the CVPR Lab, Università degli Studi di Napoli Parthenope, Italy (2021).

Before my doctoral studies, I worked as a Research Assistant at the University of Delaware, USA (2018–2019), focusing on Graph Signal Processing. I hold both a Master’s degree (with honors, 2018) and a Bachelor’s degree in Electronics Engineering (2016) from Universidad de Antioquia, Colombia.

📢 Call for Postdoc: I am looking for postdoc interested in geometric deep learning starting in spring/summer 2026. More information: Full postdoc call

🎓 For M1 and M2 students at IP Paris: I am happy to supervise a limited number of master’s projects. Please note that I expect you to be enrolled in my course Machine Learning with Graphs (APM_5DS30_TP).

News

May 15, 2026 I’ve been selected among the Gold Reviewers (top 25%) for ICML 2026.
Apr 30, 2026 We have two papers accepted at ICML 2026: “Feature-aware (Hyper)graph Generation via Next-Scale Prediction”, and “Spatiotemporal Imputation with Graph-Informed Flow Matching”.
Apr 14, 2026 I’ve been selected among the Top 200 Reviewers for ICLR 2026.
Mar 20, 2026 Our paper “Consistent Soundscape Connectomes via Stability-Refined Graph Learning” was accepted at IJCNN 2026!
Jan 22, 2026 Our paper “Generalization Bounds for Spectral GNNs via Fourier Domain Analysis” was accepted at AISTATS 2026!