Beat Buesser - RankMe

21 papers A* 3A 1B 1Journal 12Unranked 4

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	Adversarial Prompt Evaluation: Systematic Benchmarking of Guardrails Against Prompt Input Attacks on LLMs. CoRR Giulio Zizzo, Giandomenico Cornacchia, Kieran Fraser, Muhammad Zaid Hameed, Ambrish Rawat, Beat Buesser, Mark Purcell, Pin-Yu Chen, Prasanna Sattigeri, Kush R. Varshney
2025	J	`jnl`	Design Patterns for Securing LLM Agents against Prompt Injections. CoRR Luca Beurer-Kellner, Beat Buesser, Ana-Maria Cretu, Edoardo Debenedetti, Daniel Dobos, Daniel Fabian, Marc Fischer, David Froelicher, Kathrin Grosse, Daniel Naeff, Ezinwanne Ozoani, Andrew Paverd, Florian Tramèr, Václav Volhejn
2024	—	`conf`	Assuring Compliance of LLMs with EUAIA Robustness Demands. Wirtschaftsinformatik Tomas Bueno Momcilovic, Beat Buesser, Giulio Zizzo, Mark Purcell, Dian Balta
2024	J	`jnl`	Attack Atlas: A Practitioner's Perspective on Challenges and Pitfalls in Red Teaming GenAI. CoRR Ambrish Rawat, Stefan Schoepf, Giulio Zizzo, Giandomenico Cornacchia, Muhammad Zaid Hameed, Kieran Fraser, Erik Miehling, Beat Buesser, Elizabeth M. Daly, Mark Purcell, Prasanna Sattigeri, Pin-Yu Chen, Kush R. Varshney
2024	—	`conf`	Developing Assurance Cases for Adversarial Robustness and Regulatory Compliance in LLMs. ISSRE (Workshops) Tomas Bueno Momcilovic, Dian Balta, Beat Buesser, Giulio Zizzo, Mark Purcell
2024	J	`jnl`	Developing Assurance Cases for Adversarial Robustness and Regulatory Compliance in LLMs. CoRR Tomas Bueno Momcilovic, Dian Balta, Beat Buesser, Giulio Zizzo, Mark Purcell
2024	J	`jnl`	Knowledge-Augmented Reasoning for EUAIA Compliance and Adversarial Robustness of LLMs. CoRR Tomas Bueno Momcilovic, Dian Balta, Beat Buesser, Giulio Zizzo, Mark Purcell
2024	—	`conf`	Towards Assurance of LLM Adversarial Robustness using Ontology-Driven Argumentation. xAI (Late-breaking Work, Demos, Doctoral Consortium) Tomas Bueno Momcilovic, Beat Buesser, Giulio Zizzo, Mark Purcell, Dian Balta
2024	J	`jnl`	Towards Assurance of LLM Adversarial Robustness using Ontology-Driven Argumentation. CoRR Tomas Bueno Momcilovic, Beat Buesser, Giulio Zizzo, Mark Purcell, Dian Balta
2024	J	`jnl`	Towards Assuring EU AI Act Compliance and Adversarial Robustness of LLMs. CoRR Tomas Bueno Momcilovic, Beat Buesser, Giulio Zizzo, Mark Purcell, Dian Balta
2022	J	`jnl`	Boundary Adversarial Examples Against Adversarial Overfitting. CoRR Muhammad Zaid Hameed, Beat Buesser
2021	A*	`conf`	Automated Data Science for Relational Data. ICDE Hoang Thanh Lam, Beat Buesser, Hong Min, Tran Ngoc Minh, Martin Wistuba, Udayan Khurana, Gregory Bramble, Theodoros Salonidis, Dakuo Wang, Horst Samulowitz
2021	J	`jnl`	Automated Robustness with Adversarial Training as a Post-Processing Step. CoRR Ambrish Rawat, Mathieu Sinn, Beat Buesser
2020	J	`jnl`	FAT: Federated Adversarial Training. CoRR Giulio Zizzo, Ambrish Rawat, Mathieu Sinn, Beat Buesser
2020	B	`conf`	Survey on Automated End-to-End Data Science? IJCNN Djallel Bouneffouf, Charu C. Aggarwal, Thanh Hoang, Udayan Khurana, Horst Samulowitz, Beat Buesser, Sijia Liu, Tejaswini Pedapati, Parikshit Ram, Ambrish Rawat, Martin Wistuba, Alexander G. Gray
2019	A*	`conf`	Depth-First Proof-Number Search with Heuristic Edge Cost and Application to Chemical Synthesis Planning. NeurIPS Akihiro Kishimoto, Beat Buesser, Bei Chen, Adi Botea
2019	J	`jnl`	How can AI Automate End-to-End Data Science? CoRR Charu C. Aggarwal, Djallel Bouneffouf, Horst Samulowitz, Beat Buesser, Thanh Hoang, Udayan Khurana, Sijia Liu, Tejaswini Pedapati, Parikshit Ram, Ambrish Rawat, Martin Wistuba, Alexander G. Gray
2019	—	`conf`	Recurrent Neural Networks for Autoregressive Moving Average Model Selection. ICBK Bei Chen, Beat Buesser, Kelsey Dipietro
2018	A*	`conf`	AI Meets Chemistry. AAAI Akihiro Kishimoto, Beat Buesser, Adi Botea
2018	J	`jnl`	Learning Features For Relational Data. CoRR Hoang Thanh Lam, Tran Ngoc Minh, Mathieu Sinn, Beat Buesser, Martin Wistuba
2017	A	`conf`	Chemical Reactant Recommendation Using a Network of Organic Chemistry. RecSys John Savage, Akihiro Kishimoto, Beat Buesser, Ernesto Diaz-Aviles, Carlos Alzate

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.