Elham Azizi - RankMe

23 papers A* 3B 1C 1Journal 16Unranked 1

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Learning Lineage-guided Geodesics with Finsler Geometry. CoRR Aaron Zweig, Mingxuan Zhang, David A. Knowles, Elham Azizi
2026	J	`jnl`	Scalable Contrastive Causal Discovery under Unknown Soft Interventions. CoRR Mingxuan Zhang, Khushi Desai, Sopho Kevlishvili, Elham Azizi
2025	J	`jnl`	Energy Guided Geometric Flow Matching. CoRR Aaron Zweig, Mingxuan Zhang, Elham Azizi, David A. Knowles
2025	J	`jnl`	Interpretable Neural ODEs for Gene Regulatory Network Discovery under Perturbations. CoRR Zaikang Lin, Sei Chang, Aaron Zweig, Minseo Kang, Elham Azizi, David A. Knowles
2025	J	`jnl`	Towards Identifiability of Interventional Stochastic Differential Equations. CoRR Aaron Zweig, Zaikang Lin, Elham Azizi, David A. Knowles
2024	J	`jnl`	AstroBug: Automatic Game Bug Detection Using Deep Learning. IEEE Trans. Games Elham Azizi, Loutfouz Zaman
2024	B	`conf`	DIISCO: A Bayesian Framework for Inferring Dynamic Intercellular Interactions from Time-Series Single-Cell Data. RECOMB Cameron Park, Shouvik Mani, Nicolas Beltran-Velez, Katie Maurer, Satyen Gohil, Shuqiang Li, Teddy Huang, David A. Knowles, Catherine J. Wu, Elham Azizi
2024	A*	`conf`	Stable Differentiable Causal Discovery. ICML Achille Nazaret, Justin Hong, Elham Azizi, David M. Blei
2023	C	`conf`	Automatic Bug Detection in Games using LSTM Networks. CoG Elham Azizi, Loutfouz Zaman
2023	J	`jnl`	Automatic Bug Detection in Games using LSTM Networks. CoRR Elham Azizi, Loutfouz Zaman
2023	J	`jnl`	Cellstitch: 3D cellular anisotropic image segmentation via optimal transport. BMC Bioinform. Yining Liu, Yinuo Jin, Elham Azizi, Andrew J. Blumberg
2023	J	`jnl`	Deep Learning Pet Identification Using Face and Body. Inf. Elham Azizi, Loutfouz Zaman
2023	J	`jnl`	Predicting subscription renewal using binary classification in World of Warcraft. Entertain. Comput. Md. Yousuf Hossain, Elham Azizi, Loutfouz Zaman
2023	J	`jnl`	Stable Differentiable Causal Discovery. CoRR Achille Nazaret, Justin Hong, Elham Azizi, David M. Blei
2022	—	`conf`	Data Analysis and Friendship Prediction for Twitch Streamers. GEM Elham Azizi, Loutfouz Zaman
2020	J	`jnl`	An Empirical Study on Detecting COVID-19 in Chest X-ray Images Using Deep Learning Based Methods. CoRR Ramtin Babaeipour, Elham Azizi, Hassan Khotanlou
2019	J	`jnl`	A Nonparametric Multi-view Model for Estimating Cell Type-Specific Gene Regulatory Networks. CoRR Cassandra Burdziak, Elham Azizi, Sandhya Prabhakaran, Dana Pe'er
2019	J	`jnl`	Selected Papers from the Workshop on Computational Biology: Joint with the International Joint Conference on Artificial Intelligence and the International Conference on Machine Learning, 2018. J. Comput. Biol. Abdoulaye Baniré Diallo, Engelbert Mephu Nguifo, Wajdi Dhifli, Elham Azizi, Sandhya Prabhakaran, Wesley Tansey
2016	A*	`conf`	Dirichlet Process Mixture Model for Correcting Technical Variation in Single-Cell Gene Expression Data. ICML Sandhya Prabhakaran, Elham Azizi, Ambrose J. Carr, Dana Pe'er
2014	A*	`conf`	Learning Modular Structures from Network Data and Node Variables. ICML Elham Azizi, Edoardo M. Airoldi, James E. Galagan
2014	J	`jnl`	Learning modular structures from network data and node variables. CoRR Elham Azizi, James E. Galagan, Edoardo M. Airoldi
2014	—	`—`	Modeling gene regulatory networks through data integration Elham Azizi
2013	J	`jnl`	The Nat. James E. Galagan, Kyle J. Minch, Matthew Peterson, Anna Lyubetskaya, Elham Azizi, Linsday Sweet, Antonio Gomes, Tige R. Rustad, Gregory Dolganov, Irina Glotova, Thomas Abeel, Chris Mahwinney, Adam D. Kennedy, René Allard, William Brabant, Andrew Krueger, Suma Jaini, Brent Honda, Wen-Han Yu, Mark J. Hickey, Jeremy Zucker, Christopher Garay, Brian Weiner, Peter Sisk, Christian Stolte, Jessica K. Winkler, Yves Van de Peer, Paul Iazzetti, Diogo Camacho, Jonathan M. Dreyfuss, Yang Liu, Anca Dorhoi, Hans-Joachim Mollenkopf, Paul Drogaris, Julie Lamontagne, Yiyong Zhou, Julie Piquenot, Sang Tae Park, Sahadevan Raman, Stefan H. E. Kaufmann, Robert P. Mohney, Daniel Chelsky, D. Branch Moody, David R. Sherman, Gary K. Schoolnik

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.