Daniel Ulbricht

12 papers A* 3A 1Journal 6Unranked 1

Year	Rank	Type	Title / Venue / Authors
2025	—	`conf`	Revealing the Utilized Rank of Subspaces of Learning in Neural Networks. AAAI Spring Symposia Isha Garg, Christian Koguchi, Eshan Verma, Daniel Ulbricht
2025	J	`jnl`	Towards Multimodal Understanding via Stable Diffusion as a Task-Aware Feature Extractor. CoRR Vatsal Agarwal, Matthew Gwilliam, Gefen Kohavi, Eshan Verma, Daniel Ulbricht, Abhinav Shrivastava
2024	J	`jnl`	Revealing the Utilized Rank of Subspaces of Learning in Neural Networks. CoRR Isha Garg, Christian Koguchi, Eshan Verma, Daniel Ulbricht
2022	A	`conf`	Fast and Explicit Neural View Synthesis. WACV Pengsheng Guo, Miguel Ángel Bautista, Alex Colburn, Liang Yang, Daniel Ulbricht, Joshua M. Susskind, Qi Shan
2022	A*	`conf`	GAUDI: A Neural Architect for Immersive 3D Scene Generation. NeurIPS Miguel Ángel Bautista, Pengsheng Guo, Samira Abnar, Walter Talbott, Alexander Toshev, Zhuoyuan Chen, Laurent Dinh, Shuangfei Zhai, Hanlin Goh, Daniel Ulbricht, Afshin Dehghan, Joshua M. Susskind
2022	J	`jnl`	GAUDI: A Neural Architect for Immersive 3D Scene Generation. CoRR Miguel Ángel Bautista, Pengsheng Guo, Samira Abnar, Walter Talbott, Alexander Toshev, Zhuoyuan Chen, Laurent Dinh, Shuangfei Zhai, Hanlin Goh, Daniel Ulbricht, Afshin Dehghan, Josh M. Susskind
2021	J	`jnl`	Fast and Explicit Neural View Synthesis. CoRR Pengsheng Guo, Miguel Ángel Bautista, Alex Colburn, Liang Yang, Daniel Ulbricht, Joshua M. Susskind, Qi Shan
2020	A*	`conf`	Learning to Branch for Multi-Task Learning. ICML Pengsheng Guo, Chen-Yu Lee, Daniel Ulbricht
2020	J	`jnl`	Learning to Branch for Multi-Task Learning. CoRR Pengsheng Guo, Chen-Yu Lee, Daniel Ulbricht
2019	A*	`conf`	Sliced Wasserstein Discrepancy for Unsupervised Domain Adaptation. CVPR Chen-Yu Lee, Tanmay Batra, Mohammad Haris Baig, Daniel Ulbricht
2019	J	`jnl`	Sliced Wasserstein Discrepancy for Unsupervised Domain Adaptation. CoRR Chen-Yu Lee, Tanmay Batra, Mohammad Haris Baig, Daniel Ulbricht
2011	—	`ch.`	Evolution of a Tracking System. Handbook of Augmented Reality Sebastian Lieberknecht, Quintus Stierstorfer, Georg Kuschk, Daniel Ulbricht, Marion Langer, Selim Benhimane

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.