🧠 Postdoc Researcher & Lecturer @ University of Insubria
Jesús F. Cevallos M. received his Ph.D. in Computer Science Engineering from Sapienza University (Rome) in 2022. He now holds a postdoctoral researcher position at the University of Insubria (Varese, Italy).
His main research interests are industrial/ethical applications of Deep Learning with a special focus on Natural Language Processing and Neural Algorithmic Reasoning.
Advisor: Prof. Alessandra Rizzardi
Board: Prof. Sabrina Sicari, Prof. Alberto Coen-Porisini
Program Committee Member (TPC):
Reviewer for Conferences:
Reviewer for Journals:
Can LLMs resist harmful representation engineering?
End-to-end online-learning approach using the relational-bottleneck Inductive Bias for Prototype attack synthesis from raw network traffic.
Extreme value theory, the algorithmic way!
Full firepower of the Neural Algorithmic Reasoning paradigm for zero-day attack detection!
A powerful optimal-control framework needs a powerful task to be tested against!
End-to-end online-learning approach using the relational-bottleneck Inductive Bias for Prototype attack synthesis from raw network traffic.
Online optimization for live-streaming CDNs using dueling DDQN.
Deep learning approach for understanding embryonic regulatory mechanisms through graph representation learning.
Collaborative research on secure and reliable IoT systems.
Sapienza University of Rome, 2022
Tor Vergata University of Rome, 2018
Tor Vergata University of Rome, 2015
Insubria University, Varese, 2023/2024
Bachelor's degree in Computer Science
Politecnico di Milano, 2022/2023
Master's degree in Music and Acoustic Engineering
Insubria University (Italy), 2023
Bachelor's degree course on Legal Computer Science
Insubria University (Italy), 2024
Bachelor's degree course on Legal Computer Science
Insubria University (Italy), 2025
Bachelor's degree course on Legal Computer Science
Federico II University (Italy), 2024 - A Research Retrospective
Insubria University (Italy), 2023
Guest Lecture on the Innovative IoT PhD course
Collaborative research on secure and reliable IoT systems.
I'm always open to discussing research collaborations, interesting AI problems, or just chatting about the latest developments in deep learning and cybersecurity.