Benedikt Alkin

15 papers A* 4Journal 11

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Autoregressive deep learning for real-time simulation of soft tissue dynamics during virtual neurosurgery. CoRR Fabian Greifeneder, Wolfgang Fenz, Benedikt Alkin, Johannes Brandstetter, Michael Giretzlehner, Philipp Moser
2025	J	`jnl`	AB-UPT for Automotive and Aerospace Applications. CoRR Benedikt Alkin, Richard Kurle, Louis Serrano, Dennis Just, Johannes Brandstetter
2025	J	`jnl`	AB-UPT: Scaling Neural CFD Surrogates for High- Fidelity Automotive Aerodynamics Simulations via Anchored- Branched Universal Physics Transformers. Trans. Mach. Learn. Res. Benedikt Alkin, Maurits Bleeker, Richard Kurle, Tobias Kronlachner, Reinhard Sonnleitner, Matthias Dorfer, Johannes Brandstetter
2025	A*	`conf`	MIM-Refiner: A Contrastive Learning Boost from Intermediate Pre-Trained Masked Image Modeling Representations. ICLR Benedikt Alkin, Lukas Miklautz, Sepp Hochreiter, Johannes Brandstetter
2025	J	`jnl`	NeuralCFD: Deep Learning on High-Fidelity Automotive Aerodynamics Simulations. CoRR Maurits Bleeker, Matthias Dorfer, Tobias Kronlachner, Reinhard Sonnleitner, Benedikt Alkin, Johannes Brandstetter
2025	J	`jnl`	Towards scientific machine learning for granular material simulations - challenges and opportunities. CoRR Marc Fransen, Andreas Fürst, Deepak Tunuguntla, Daniel N. Wilke, Benedikt Alkin, Daniel Barreto, Johannes Brandstetter, Miguel Angel Cabrera, Xinyan Fan, Mengwu Guo, Bram Kieskamp, Krishna Kumar, John Morrissey, Jonathan Nuttall, Jin Y. Ooi, Luisa Orozco, Stefanos-Aldo Papanicolopulos, Tongming Qu, Dingena Schott, Takayuki Shuku, WaiChing Sun, Thomas Weinhart, Dongwei Ye, Hongyang Cheng
2025	A*	`conf`	Vision-LSTM: xLSTM as Generic Vision Backbone. ICLR Benedikt Alkin, Maximilian Beck, Korbinian Pöppel, Sepp Hochreiter, Johannes Brandstetter
2024	A*	`conf`	Contrastive Tuning: A Little Help to Make Masked Autoencoders Forget. AAAI Johannes Lehner, Benedikt Alkin, Andreas Fürst, Elisabeth Rumetshofer, Lukas Miklautz, Sepp Hochreiter
2024	J	`jnl`	MIM-Refiner: A Contrastive Learning Boost from Intermediate Pre-Trained Representations. CoRR Benedikt Alkin, Lukas Miklautz, Sepp Hochreiter, Johannes Brandstetter
2024	J	`jnl`	NeuralDEM - Real-time Simulation of Industrial Particulate Flows. CoRR Benedikt Alkin, Tobias Kronlachner, Samuele Papa, Stefan Pirker, Thomas Lichtenegger, Johannes Brandstetter
2024	J	`jnl`	One Initialization to Rule them All: Fine-tuning via Explained Variance Adaptation. CoRR Fabian Paischer, Lukas Hauzenberger, Thomas Schmied, Benedikt Alkin, Marc Peter Deisenroth, Sepp Hochreiter
2024	J	`jnl`	Universal Physics Transformers. CoRR Benedikt Alkin, Andreas Fürst, Simon Schmid, Lukas Gruber, Markus Holzleitner, Johannes Brandstetter
2024	A*	`conf`	Universal Physics Transformers: A Framework For Efficiently Scaling Neural Operators. NeurIPS Benedikt Alkin, Andreas Fürst, Simon Schmid, Lukas Gruber, Markus Holzleitner, Johannes Brandstetter
2024	J	`jnl`	Vision-LSTM: xLSTM as Generic Vision Backbone. CoRR Benedikt Alkin, Maximilian Beck, Korbinian Pöppel, Sepp Hochreiter, Johannes Brandstetter
2023	J	`jnl`	Contrastive Tuning: A Little Help to Make Masked Autoencoders Forget. CoRR Johannes Lehner, Benedikt Alkin, Andreas Fürst, Elisabeth Rumetshofer, Lukas Miklautz, Sepp Hochreiter

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.