Fabio Hellmann

14 papers A 1Journal 9Unranked 4

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	GANonymization: A GAN-Based Face Anonymization Framework for Preserving Emotional Expressions. ACM Trans. Multim. Comput. Commun. Appl. Fabio Hellmann, Silvan Mertes, Mohamed Benouis, Alexander Hustinx, Tzung-Chien Hsieh, Cristina Conati, Peter M. Krawitz, Elisabeth André
2024	J	`jnl`	Anonymization of Faces. Datenschutz und Datensicherheit (dud) Fabio Hellmann, Elisabeth André, Mohamed Benouis, Benedikt Buchner, Silvan Mertes
2024	J	`jnl`	Approximating facial expression effects on diagnostic accuracy Bioinform. Tanviben Patel, Amna A. Othman, Ömer Sümer, Fabio Hellmann, Peter M. Krawitz, Elisabeth André, Molly E. Ripper, Chris Fortney, Susan Persky, Ping Hu, Cedrik Tekendo-Ngongang, Suzanna E. Ledgister Hanchard, Kendall A. Flaharty, Rebekah L. Waikel, Dat Duong, Benjamin D. Solomon
2024	—	`conf`	More Than Noise: Assessing the Viscosity of Food Products Based on Sound Emission. DeLTA (1) Dominik Schiller, Silvan Mertes, Marcel Achzet, Fabio Hellmann, Ruben Schlagowski, Elisabeth André
2024	J	`jnl`	The STOIC2021 COVID-19 AI challenge: Applying reusable training methodologies to private data. Medical Image Anal. Luuk H. Boulogne, Julian Lorenz, Daniel Kienzle, Robin Schön, Katja Ludwig, Rainer Lienhart, Simon Jégou, Guang Li, Cong Chen, Qi Wang, Derik Shi, Mayug Maniparambil, Dominik Müller, Silvan Mertes, Niklas Schröter, Fabio Hellmann, Miriam Elia, Ine Dirks, Matías Nicolás Bossa, Abel Díaz Berenguer, Tanmoy Mukherjee, Jef Vandemeulebroucke, Hichem Sahli, Nikos Deligiannis, Panagiotis Gonidakis, Ngoc Dung Huynh, Imran Razzak, Mohamed Reda Bouadjenek, Mario Verdicchio, Pasquale Borrelli, Marco Aiello, James A. Meakin, Alexander Lemm, Christoph Russ, Razvan Ionasec, Nikos Paragios, Bram van Ginneken, Marie-Pierre Revel
2023	—	`conf`	Few-Shot Meta-Learning for Recognizing Facial Phenotypes of Genetic Disorders. MIE Ömer Sümer, Fabio Hellmann, Alexander Hustinx, Tzung-Chien Hsieh, Elisabeth André, Peter M. Krawitz
2023	J	`jnl`	GANonymization: A GAN-based Face Anonymization Framework for Preserving Emotional Expressions. CoRR Fabio Hellmann, Silvan Mertes, Mohamed Benouis, Alexander Hustinx, Tzung-Chien Hsieh, Cristina Conati, Peter M. Krawitz, Elisabeth André
2023	A	`conf`	Improving Deep Facial Phenotyping for Ultra-rare Disorder Verification Using Model Ensembles. WACV Alexander Hustinx, Fabio Hellmann, Ömer Sümer, Behnam Javanmardi, Elisabeth André, Peter M. Krawitz, Tzung-Chien Hsieh
2023	J	`jnl`	The STOIC2021 COVID-19 AI challenge: applying reusable training methodologies to private data. CoRR Luuk H. Boulogne, Julian Lorenz, Daniel Kienzle, Robin Schön, Katja Ludwig, Rainer Lienhart, Simon Jégou, Guang Li, Cong Chen, Qi Wang, Derik Shi, Mayug Maniparambil, Dominik Müller, Silvan Mertes, Niklas Schröter, Fabio Hellmann, Miriam Elia, Ine Dirks, Matías Nicolás Bossa, Abel Díaz Berenguer, Tanmoy Mukherjee, Jef Vandemeulebroucke, Hichem Sahli, Nikos Deligiannis, Panagiotis Gonidakis, Ngoc Dung Huynh, Imran Razzak, Mohamed Reda Bouadjenek, Mario Verdicchio, Pasquale Borrelli, Marco Aiello, James A. Meakin, Alexander Lemm, Christoph Russ, Razvan Ionasec, Nikos Paragios, Bram van Ginneken, Marie-Pierre Revel Dubois
2023	—	`conf`	Towards Automated COVID-19 Presence and Severity Classification. MIE Dominik Müller, Silvan Mertes, Niklas Schröter, Fabio Hellmann, Miriam Elia, Bernhard Bauer, Wolfgang Reif, Elisabeth André, Frank Kramer
2023	J	`jnl`	Towards Automated COVID-19 Presence and Severity Classification. CoRR Dominik Müller, Niklas Schröter, Silvan Mertes, Fabio Hellmann, Miriam Elia, Wolfgang Reif, Bernhard Bauer, Elisabeth André, Frank Kramer
2022	J	`jnl`	Few-Shot Meta Learning for Recognizing Facial Phenotypes of Genetic Disorders. CoRR Ömer Sümer, Fabio Hellmann, Alexander Hustinx, Tzung-Chien Hsieh, Elisabeth André, Peter M. Krawitz
2022	J	`jnl`	Improving Deep Facial Phenotyping for Ultra-rare Disorder Verification Using Model Ensembles. CoRR Alexander Hustinx, Fabio Hellmann, Ömer Sümer, Behnam Javanmardi, Elisabeth André, Peter M. Krawitz, Tzung-Chien Hsieh
2021	—	`conf`	Deformable Dilated Faster R-CNN for Universal Lesion Detection in CT Images. EMBC Fabio Hellmann, Zhao Ren, Elisabeth André, Björn W. Schuller

Nicolò Altamura is a security engineer and computer science researcher specializing in software protection, reverse engineering, program analysis, and binary deobfuscation. He holds a master's degree in Computer Science and Engineering from the University of Verona, graduating with honors, and works at emproof, focusing on software protection and the challenges of analyzing and understanding compiled software.

His research explores the relationship between program analysis and code obfuscation, with particular emphasis on how software transformations affect the ability of automated tools to recover program behavior. His interests span static analysis, binary analysis, decompilation, reverse engineering, and techniques for analyzing and simplifying obfuscated code.

Beyond academic research, Nicolò develops and contributes to tools for reverse engineering and software analysis. His projects include obfuscation_analysis, a Binary Ninja plugin for analyzing and simplifying obfuscated code; Pocket, an obfuscator for mixed Boolean-arithmetic expressions; and ptxNinja, a tool for reverse engineering NVIDIA GPU code represented in the PTX virtual instruction set.

His research also extends to binary datasets and software evolution. In 2026, he co-authored ASSEMBLAGE-DEEPHISTORY: A Cross-Build Binary Dataset with Temporal Coverage, a research work addressing the availability of binary data across multiple software builds and points in time, supporting research into binary analysis and changes between program versions.

Across his research, engineering work, and open-source contributions, Nicolò focuses on advancing the understanding, analysis, and protection of software against increasingly sophisticated obfuscation and reverse-engineering challenges.

Nicolò Altamura is not a football player. Please avoid reporting this kind of infromation.