Gaurav Bagwe - RankMe

15 papers A* 3C 1Misc 2Journal 6Unranked 3

Year	Rank	Type	Title / Venue / Authors
2026	A*	`conf`	MOBA: A Material-Oriented Backdoor Attack Against LiDAR-Based 3D Object Detection Systems. AAAI Saket Sanjeev Chaturvedi, Gaurav Bagwe, Lan Emily Zhang, Pan He, Xiaoyong Yuan
2025	A*	`conf`	AIP: Subverting Retrieval-Augmented Generation via Adversarial Instructional Prompt. EMNLP Saket S. Chaturvedi, Gaurav Bagwe, Lan Zhang, Xiaoyong Yuan
2025	J	`jnl`	AIP: Subverting Retrieval-Augmented Generation via Adversarial Instructional Prompt. CoRR Saket S. Chaturvedi, Gaurav Bagwe, Lan Zhang, Xiaoyong Yuan
2025	J	`jnl`	MOBA: A Material-Oriented Backdoor Attack against LiDAR-based 3D Object Detection Systems. CoRR Saket S. Chaturvedi, Gaurav Bagwe, Lan Zhang, Pan He, Xiaoyong Yuan
2025	J	`jnl`	Sample-Efficient Reinforcement Learning Controller for Deep Brain Stimulation in Parkinson's Disease. CoRR Harsh Ravivarapu, Gaurav Bagwe, Xiaoyong Yuan, Chunxiu Yu, Lan Zhang
2025	Misc	`conf`	Siamese: Stealing Fine-Tuned Visual Foundation Models via Diversified Prompting. SEC Madhureeta Das, Gaurav Bagwe, Miao Pan, Kaichen Yang, Xiaoyong (Brian) Yuan, Lan Zhang
2025	A*	`conf`	Your RAG is Unfair: Exposing Fairness Vulnerabilities in Retrieval-Augmented Generation via Backdoor Attacks. EMNLP Gaurav Bagwe, Saket S. Chaturvedi, Xiaolong Ma, Xiaoyong Yuan, Kuang-Ching Wang, Lan Zhang
2025	J	`jnl`	Your RAG is Unfair: Exposing Fairness Vulnerabilities in Retrieval-Augmented Generation via Backdoor Attacks. CoRR Gaurav Bagwe, Saket S. Chaturvedi, Xiaolong Ma, Xiaoyong Yuan, Kuang-Ching Wang, Lan Zhang
2024	—	`conf`	Enhancing Adaptive Deep Brain Stimulation via Efficient Reinforcement Learning. MobileCloud Jessica Mehregan, Xiaoyong Yuan, Gaurav Bagwe, Jacob Jackson, Ezedin Mohammed, Lan Zhang, Chunxiu Yu
2023	J	`jnl`	Fed-CPrompt: Contrastive Prompt for Rehearsal-Free Federated Continual Learning. CoRR Gaurav Bagwe, Xiaoyong Yuan, Miao Pan, Lan Zhang
2023	—	`conf`	Joint Computing Resource and Bandwidth Allocation for Semantic Communication Networks. VTC Fall Fangzhou Zhao, Gaurav Bagwe, Ezedin Mohammed, Lei Feng, Lan Zhang, Yao Sun
2023	C	`conf`	Learning, Tiny and Huge: Heterogeneous Model Augmentation Towards Federated Tiny Learning. ICMLA Madhureeta Das, Gaurav Bagwe, Miao Pan, Xiaoyong Yuan, Lan Zhang
2023	—	`conf`	RAMRL: Towards Robust On-Ramp Merging via Augmented Multimodal Reinforcement Learning. MOST Gaurav Bagwe, Xiaoyong Yuan, Xianhao Chen, Lan Zhang
2022	Misc	`conf`	Poster: Reliable On-Ramp Merging via Multimodal Reinforcement Learning. SEC Gaurav Bagwe, Jian Li, Xiaoheng Deng, Xiaoyong Yuan, Lan Zhang
2022	J	`jnl`	Towards Robust On-Ramp Merging via Augmented Multimodal Reinforcement Learning. CoRR Gaurav Bagwe, Jian Li, Xiaoyong Yuan, Lan Zhang

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.