Daniel Burkhardt

12 papers A* 1Journal 2Unranked 9

Year	Rank	Type	Title / Venue / Authors
2025	—	`conf`	Anti-Kinetosis: A Hybrid Analytics Approach for Motion Sickness Detection in Software-Defined Vehicles. AMCIS Xiangwei Cheng, Daniel Burkhardt, Dirk Slama, Ismail Gharsallah
2025	J	`jnl`	Benchmarking and Evaluation of AI Models in Biology: Outcomes and Recommendations from the CZI Virtual Cells Workshop. CoRR Elizabeth Fahsbender, Alma Andersson, Jeremy Ash, Polina Binder, Daniel Burkhardt, Benjamin Chang, Georg K. Gerber, Anthony Gitter, Patrick Godau, Ankit Gupta, Genevieve Haliburton, Siyu He, Trey Ideker, Ivana Jelic, Aly Khan, Yang-Joon Kim, Aditi Krishnapriyan, Jon M. Laurent, Tianyu Liu, Emma Lundberg, Shalin B. Mehta, Rob Moccia, Angela Oliveira Pisco, Katherine S. Pollard, Suresh Ramani, Julio Saez-Rodriguez, Yasin Senbabaoglu, Elana Simon, Srinivasan Sivanandan, Gustavo Stolovitzky, Marc Valer, Bo Wang, Xikun Zhang, James Zou, Katrina Kalantar
2025	—	`conf`	Development of an AI Solution for a fast Assessment of Ethical Risks of potential AI Use Cases. ACIS Daniel Burkhardt, Jens F. Lachenmaier, Paul Herbst
2025	J	`jnl`	Overcoming Knowledge Discrepancies: Structuring Reasoning Threads through Knowledge Balancing in Interactive Scenarios. CoRR Daniel Burkhardt, Xiangwei Cheng
2024	A*	`conf`	A benchmark for prediction of transcriptomic responses to chemical perturbations across cell types. NeurIPS Artur Szalata, Andrew Benz, Robrecht Cannoodt, Mauricio Cortes, Jason Fong, Sunil Kuppasani, Richard Lieberman, Tianyu Liu, Javier Mas-Rosario, Rico Meinl, Jalil Nourisa, Jared Tumiel, Tin M. Tunjic, Mengbo Wang, Noah Weber, Hongyu Zhao, Benedict Anchang, Fabian J. Theis, Malte Luecken, Daniel Burkhardt
2021	—	`conf`	A Model Design to evaluate Processes for Autonomization. PACIS Daniel Burkhardt, Nico Enders, Heiner Lasi
2021	—	`conf`	A sandbox for prediction and integration of DNA, RNA, and proteins in single cells. NeurIPS Datasets and Benchmarks Malte Lücken, Daniel Burkhardt, Robrecht Cannoodt, Christopher Lance, Aditi Agrawal, Hananeh Aliee, Ann Chen, Louise Deconinck, Angela Detweiler, Alejandro Granados, Shelly Huynh, Laura Isacco, Yang Kim, Dominik Klein, Bony de Kumar, Sunil Kuppasani, Heiko Lickert, Aaron McGeever, Joaquin Melgarejo, Honey Mekonen, Maurizio Morri, Michaela Müller, Norma Neff, Sheryl Paul, Bastian Rieck, Kaylie Schneider, Scott Steelman, Michael Sterr, Daniel Treacy, Alexander Tong, Alexandra-Chloé Villani, Guilin Wang, Jia Yan, Ce Zhang, Angela Pisco, Smita Krishnaswamy, Fabian J. Theis, Jonathan M. Bloom
2020	—	`conf`	A Conceptual Model of Data-Driven Solutions. AMCIS Daniel Burkhardt, Heiner Lasi
2020	—	`conf`	Design Patterns based on Deep Learning analyzing Distributed Data. Wirtschaftsinformatik (Zentrale Tracks) Daniel Burkhardt, Nana Agyei-Kena, Patrick Frey, Sven Kurrle, Heiner Lasi
2019	—	`conf`	Control of Cyber-Physical Production Systems: A Concept to Increase the Trustworthiness within Multi-Agent Systems with Distributed Ledger Technology. PACIS Andre Lebioda, Jens F. Lachenmaier, Daniel Burkhardt
2019	—	`conf`	The Symbiosis of Distributed Ledger and Machine Learning as a Relevance for Autonomy in the Internet of Things. HICSS Daniel Burkhardt, Patrick Frey, Heiner Lasi
2018	—	`conf`	Distributed Ledger. ICE/ITMC Daniel Burkhardt, Maximilian Werling, Heiner Lasi

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.