Ragav Venkatesan

19 papers A* 2B 2Journal 10Unranked 5

Year	Rank	Type	Title / Venue / Authors
2020	—	`conf`	Evaluating the Effectiveness of Efficient Neural Architecture Search for Sentence-Pair Tasks. Insights Ansel MacLaughlin, Jwala Dhamala, Anoop Kumar, Sriram Venkatapathy, Ragav Venkatesan, Rahul Gupta
2020	J	`jnl`	Evaluating the Effectiveness of Efficient Neural Architecture Search for Sentence-Pair Tasks. CoRR Ansel MacLaughlin, Jwala Dhamala, Anoop Kumar, Sriram Venkatapathy, Ragav Venkatesan, Rahul Gupta
2020	J	`jnl`	Out-of-the-box channel pruned networks. CoRR Ragav Venkatesan, Gurumurthy Swaminathan, Xiong Zhou, Anna Luo
2019	A*	`conf`	d-SNE: Domain Adaptation Using Stochastic Neighborhood Embedding. CVPR Xiang Xu, Xiong Zhou, Ragav Venkatesan, Gurumurthy Swaminathan, Orchid Majumder
2019	J	`jnl`	d-SNE: Domain Adaptation using Stochastic Neighborhood Embedding. CoRR Xiang Xu, Xiong Zhou, Ragav Venkatesan, Gurumurthy Swaminathan, Orchid Majumder
2017	J	`jnl`	A Strategy for an Uncompromising Incremental Learner. CoRR Ragav Venkatesan, Hemanth Venkateswara, Sethuraman Panchanathan, Baoxin Li
2017	J	`jnl`	Classification of Diabetic Retinopathy Images Using Multi-Class Multiple-Instance Learning Based on Color Correlogram Features. CoRR Ragav Venkatesan, Parag S. Chandakkar, Baoxin Li
2016	J	`jnl`	Diving deeper into mentee networks. CoRR Ragav Venkatesan, Baoxin Li
2016	J	`jnl`	Neural Dataset Generality. CoRR Ragav Venkatesan, Vijetha Gattupalli, Baoxin Li
2016	B	`conf`	On the generality of neural image features. ICIP Ragav Venkatesan, Vijetha Gattupalli, Baoxin Li
2015	J	`jnl`	Evolution of fashion brands on Twitter and Instagram. CoRR Lydia Manikonda, Ragav Venkatesan, Subbarao Kambhampati, Baoxin Li
2015	A*	`conf`	Simpler Non-Parametric Methods Provide as Good or Better Results to Multiple-Instance Learning. ICCV Ragav Venkatesan, Parag Shridhar Chandakkar, Baoxin Li
2015	J	`jnl`	Spatiotemporal video deinterlacing using control grid interpolation. J. Electronic Imaging Ragav Venkatesan, Christine M. Zwart, David H. Frakes, Baoxin Li
2014	—	`conf`	Video-Based Self-positioning for Intelligent Transportation Systems Applications. ISVC (1) Parag S. Chandakkar, Ragav Venkatesan, Baoxin Li
2013	—	`conf`	Retrieving clinically relevant diabetic retinopathy images using a multi-class multiple-instance framework. Computer-Aided Diagnosis Parag S. Chandakkar, Ragav Venkatesan, Baoxin Li
2012	—	`conf`	A machine-learning approach to retrieving diabetic retinopathy images. BCB Parag S. Chandakkar, Ragav Venkatesan, Baoxin Li, Helen K. Li
2012	—	`conf`	Classification of diabetic retinopathy images using multi-class multiple-instance learning based on color correlogram features. EMBC Ragav Venkatesan, Parag S. Chandakkar, Baoxin Li, Helen K. Li
2012	J	`jnl`	Decomposed multidimensional control grid interpolation for common consumer electronic image processing applications. J. Electronic Imaging Christine M. Zwart, Ragav Venkatesan, David H. Frakes
2012	B	`conf`	Video deinterlacing with control grid interpolation. ICIP Ragav Venkatesan, Christine M. Zwart, David H. Frakes

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.