Ege Beyazit - RankMe

13 papers A* 4A 1B 1Journal 5Unranked 2

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	$$\texttt{C2-DPO}$$: Constrained Controlled Direct Preference Optimization. Trans. Mach. Learn. Res. Kavosh Asadi, Xingzi Xu, Julien Han, Ege Beyazit, Idan Pipano, Dominique Perrault-Joncas, Shoham Sabach, Mohammad Ghavamzadeh, Karim Bouyarmane
2025	J	`jnl`	Enabling Fine-Grained Operating Points for Black-Box LLMs. CoRR Ege Beyazit, KL Navaneet, Prashant Mathur, Roi Blanco, Vidit Bansal, Karim Bouyarmane
2023	A*	`conf`	An Inductive Bias for Tabular Deep Learning. NeurIPS Ege Beyazit, Jonathan Kozaczuk, Bo Li, Vanessa Wallace, Bilal Fadlallah
2021	J	`jnl`	Toward Mining Capricious Data Streams: A Generative Approach. IEEE Trans. Neural Networks Learn. Syst. Yi He, Baijun Wu, Di Wu, Ege Beyazit, Sheng Chen, Xindong Wu
2020	J	`jnl`	Cost Efficient Repository Management for Cloud-Based On-Demand Video Streaming. CoRR Mahmoud Darwich, Ege Beyazit, Mohsen Amini Salehi, Magdy A. Bayoumi
2020	A*	`conf`	Learning Interpretable Representations with Informative Entanglements. IJCAI Ege Beyazit, Doruk Tuncel, Xu Yuan, Nian-Feng Tzeng, Xindong Wu
2020	A	`conf`	Online Learning to Accelerate Neural Network Inference with Traveling Classifiers. ECAI Ege Beyazit, Yi He, Nian-Feng Tzeng, Xindong Wu
2019	J	`jnl`	Cost-Efficient Cloud-Based Video Streaming Through Measuring Hotness. Comput. J. Mahmoud Darwich, Mohsen Amini Salehi, Ege Beyazit, Magdy A. Bayoumi
2019	A*	`conf`	Online Learning from Capricious Data Streams: A Generative Approach. IJCAI Yi He, Baijun Wu, Di Wu, Ege Beyazit, Sheng Chen, Xindong Wu
2019	A*	`conf`	Online Learning from Data Streams with Varying Feature Spaces. AAAI Ege Beyazit, Jeevithan Alagurajah, Xindong Wu
2018	—	`conf`	Learning Simplified Decision Boundaries from Trapezoidal Data Streams. ICANN (1) Ege Beyazit, Matin Hosseini, Anthony Maida, Xindong Wu
2018	B	`conf`	Supervised Data Synthesizing and Evolving - A Framework for Real-World Traffic Crash Severity Classification. ICTAI Yi He, Di Wu, Ege Beyazit, Xiaoduan Sun, Xindong Wu
2017	—	`conf`	Cost Efficient Repository Management for Cloud-Based On-demand Video Streaming. MobileCloud Mahmoud Darwich, Ege Beyazit, Mohsen Amini Salehi, Magdy A. Bayoumi

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.