Gaurav Menghani

16 papers A* 4Journal 11Unranked 1

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	GUIDE: Guided Initialization and Distillation of Embeddings. CoRR Khoa Trinh, Gaurav Menghani, Erik Vee
2025	A*	`conf`	LAuReL: Learned Augmented Residual Layer. ICML Gaurav Menghani, Ravi Kumar, Sanjiv Kumar
2024	J	`jnl`	LAuReL: Learned Augmented Residual Layer. CoRR Gaurav Menghani, Ravi Kumar, Sanjiv Kumar
2023	J	`jnl`	Efficient Deep Learning: A Survey on Making Deep Learning Models Smaller, Faster, and Better. ACM Comput. Surv. Gaurav Menghani
2023	A*	`conf`	Robust Active Distillation. ICLR Cenk Baykal, Khoa Trinh, Fotis Iliopoulos, Gaurav Menghani, Erik Vee
2023	A*	`conf`	SLaM: Student-Label Mixing for Distillation with Unlabeled Examples. NeurIPS Vasilis Kontonis, Fotis Iliopoulos, Khoa Trinh, Cenk Baykal, Gaurav Menghani, Erik Vee
2023	J	`jnl`	SLaM: Student-Label Mixing for Semi-Supervised Knowledge Distillation. CoRR Vasilis Kontonis, Fotis Iliopoulos, Khoa Trinh, Cenk Baykal, Gaurav Menghani, Erik Vee
2022	J	`jnl`	Robust Active Distillation. CoRR Cenk Baykal, Khoa Trinh, Fotis Iliopoulos, Gaurav Menghani, Erik Vee
2022	A*	`conf`	Weighted Distillation with Unlabeled Examples. NeurIPS Fotis Iliopoulos, Vasilis Kontonis, Cenk Baykal, Gaurav Menghani, Khoa Trinh, Erik Vee
2022	J	`jnl`	Weighted Distillation with Unlabeled Examples. CoRR Fotis Iliopoulos, Vasilis Kontonis, Cenk Baykal, Gaurav Menghani, Khoa Trinh, Erik Vee
2021	J	`jnl`	Efficient Deep Learning: A Survey on Making Deep Learning Models Smaller, Faster, and Better. CoRR Gaurav Menghani
2021	J	`jnl`	Fast Bitmap Fit: A CPU Cache Line friendly memory allocator for single object allocations. CoRR Dhruv Mátáni, Gaurav Menghani
2020	J	`jnl`	An Easy-to-Use-and-Deploy Grid Computing Framework. CoRR Gaurav Menghani, Anil Harwani, Yash Londhe, Kalpesh Kagresha
2019	J	`jnl`	A Simple Solution to the Level-Ancestor Problem. CoRR Gaurav Menghani, Dhruv Mátáni
2019	J	`jnl`	Learning from a Teacher using Unlabeled Data. CoRR Gaurav Menghani, Sujith Ravi
2013	—	`conf`	Avoiding Locks and Atomic Instructions in Shared-Memory Parallel BFS Using Optimistic Parallelization. IPDPS Workshops Jesmin Jahan Tithi, Dhruv Mátáni, Gaurav Menghani, Rezaul Alam Chowdhury

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.