Eeshan Gunesh Dhekane

16 papers A* 3Misc 2Journal 10Unranked 1

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	How PARTs assemble into wholes: Learning the relative composition of images. CoRR Melika Ayoughi, Samira Abnar, Chen Huang, Christopher Michael Sandino, Sayeri Lala, Eeshan Gunesh Dhekane, Dan Busbridge, Shuangfei Zhai, Vimal Thilak, Joshua M. Susskind, Pascal Mettes, Paul Groth, Hanlin Goh
2025	J	`jnl`	Self-reflective Uncertainties: Do LLMs Know Their Internal Answer Distribution? CoRR Michael Kirchhof, Luca Füger, Adam Golinski, Eeshan Gunesh Dhekane, Arno Blaas, Sinead Williamson
2025	A*	`conf`	Theory, Analysis, and Best Practices for Sigmoid Self-Attention. ICLR Jason Ramapuram, Federico Danieli, Eeshan Gunesh Dhekane, Floris Weers, Dan Busbridge, Pierre Ablin, Tatiana Likhomanenko, Jagrit Digani, Zijin Gu, Amitis Shidani, Russell Webb
2025	J	`jnl`	Which Evaluation for Which Model? A Taxonomy for Speech Model Assessment. CoRR Maureen de Seyssel, Eeshan Gunesh Dhekane
2024	A*	`conf`	Poly-View Contrastive Learning. ICLR Amitis Shidani, R. Devon Hjelm, Jason Ramapuram, Russell Webb, Eeshan Gunesh Dhekane, Dan Busbridge
2024	J	`jnl`	Poly-View Contrastive Learning. CoRR Amitis Shidani, R. Devon Hjelm, Jason Ramapuram, Russ Webb, Eeshan Gunesh Dhekane, Dan Busbridge
2024	J	`jnl`	Theory, Analysis, and Best Practices for Sigmoid Self-Attention. CoRR Jason Ramapuram, Federico Danieli, Eeshan Gunesh Dhekane, Floris Weers, Dan Busbridge, Pierre Ablin, Tatiana Likhomanenko, Jagrit Digani, Zijin Gu, Amitis Shidani, Russ Webb
2023	J	`jnl`	Bootstrap Your Own Variance. CoRR Polina Turishcheva, Jason Ramapuram, Sinead Williamson, Dan Busbridge, Eeshan Gunesh Dhekane, Russ Webb
2023	A*	`conf`	How to Scale Your EMA. NeurIPS Dan Busbridge, Jason Ramapuram, Pierre Ablin, Tatiana Likhomanenko, Eeshan Gunesh Dhekane, Xavier Suau Cuadros, Russell Webb
2023	J	`jnl`	How to Scale Your EMA. CoRR Dan Busbridge, Jason Ramapuram, Pierre Ablin, Tatiana Likhomanenko, Eeshan Gunesh Dhekane, Xavier Suau, Russ Webb
2022	J	`jnl`	Elastic Weight Consolidation Improves the Robustness of Self-Supervised Learning Methods under Transfer. CoRR Andrius Ovsianas, Jason Ramapuram, Dan Busbridge, Eeshan Gunesh Dhekane, Russ Webb
2019	Misc	`conf`	Learning Affective Correspondence between Music and Image. ICASSP Gaurav Verma, Eeshan Gunesh Dhekane, Tanaya Guha
2019	J	`jnl`	Learning Affective Correspondence between Music and Image. CoRR Gaurav Verma, Eeshan Gunesh Dhekane, Tanaya Guha
2019	J	`jnl`	Transfer Learning by Modeling a Distribution over Policies. CoRR Disha Shrivastava, Eeshan Gunesh Dhekane, Riashat Islam
2018	Misc	`conf`	Convolutional Neural Network Based Sensors for Mobile Robot Relocalization. MMAR Harsh Sinha, Jay Patrikar, Eeshan Gunesh Dhekane, Gaurav Pandey, Mangal Kothari
2015	—	`conf`	High Accuracy Optical Flow based future image frame predictor model. AIPR Nishchal K. Verma, Eeshan Gunesh Dhekane, G. S. S. Srinivas Rao, Aakansha Mishra

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.