Tanzila Rahman

22 papers A* 4A 3B 2Journal 12Unranked 1

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	To Sink or Not to Sink: Visual Information Pathways in Large Vision-Language Models. CoRR Jiayun Luo, Wan-Cyuan Fan, Lyuyang Wang, Xiangteng He, Tanzila Rahman, Purang Abolmaesumi, Leonid Sigal
2024	J	`jnl`	MMFactory: A Universal Solution Search Engine for Vision-Language Tasks. CoRR Wan-Cyuan Fan, Tanzila Rahman, Leonid Sigal
2024	A*	`conf`	Prompting Hard or Hardly Prompting: Prompt Inversion for Text-to-Image Diffusion Models. CVPR Shweta Mahajan, Tanzila Rahman, Kwang Moo Yi, Leonid Sigal
2024	J	`jnl`	Visual Concept-driven Image Generation with Text-to-Image Diffusion Model. CoRR Tanzila Rahman, Shweta Mahajan, Hsin-Ying Lee, Jian Ren, Sergey Tulyakov, Leonid Sigal
2023	A*	`conf`	Make-A-Story: Visual Memory Conditioned Consistent Story Generation. CVPR Tanzila Rahman, Hsin-Ying Lee, Jian Ren, Sergey Tulyakov, Shweta Mahajan, Leonid Sigal
2023	J	`jnl`	Prompting Hard or Hardly Prompting: Prompt Inversion for Text-to-Image Diffusion Models. CoRR Shweta Mahajan, Tanzila Rahman, Kwang Moo Yi, Leonid Sigal
2022	J	`jnl`	Make-A-Story: Visual Memory Conditioned Consistent Story Generation. CoRR Tanzila Rahman, Hsin-Ying Lee, Jian Ren, Sergey Tulyakov, Shweta Mahajan, Leonid Sigal
2021	—	`conf`	An Improved Attention for Visual Question Answering. CVPR Workshops Tanzila Rahman, Shih-Han Chou, Leonid Sigal, Giuseppe Carenini
2021	J	`jnl`	TriBERT: Full-body Human-centric Audio-visual Representation Learning for Visual Sound Separation. CoRR Tanzila Rahman, Mengyu Yang, Leonid Sigal
2021	A*	`conf`	TriBERT: Human-centric Audio-visual Representation Learning. NeurIPS Tanzila Rahman, Mengyu Yang, Leonid Sigal
2021	A	`conf`	Weakly-Supervised Audio-Visual Sound Source Detection and Separation. ICME Tanzila Rahman, Leonid Sigal
2021	J	`jnl`	Weakly-supervised Audio-visual Sound Source Detection and Separation. CoRR Tanzila Rahman, Leonid Sigal
2020	J	`jnl`	An Improved Attention for Visual Question Answering. CoRR Tanzila Rahman, Shih-Han Chou, Leonid Sigal, Giuseppe Carenini
2019	A	`conf`	Convolutional Temporal Attention Model for Video-Based Person Re-Identification. ICME Tanzila Rahman, Mrigank Rochan, Yang Wang
2019	J	`jnl`	Convolutional Temporal Attention Model for Video-based Person Re-identification. CoRR Tanzila Rahman, Mrigank Rochan, Yang Wang
2019	B	`conf`	Non-Local Attentive Temporal Network for Video-Based Person Re-Identification. AVSS Shivansh Rao, Peng Cao, Tanzila Rahman, Mrigank Rochan, Yang Wang
2019	B	`conf`	Video-Based Person Re-Identification using Refined Attention Networks. AVSS Tanzila Rahman, Mrigank Rochan, Yang Wang
2019	A*	`conf`	Watch, Listen and Tell: Multi-Modal Weakly Supervised Dense Event Captioning. ICCV Tanzila Rahman, Bicheng Xu, Leonid Sigal
2019	J	`jnl`	Watch, Listen and Tell: Multi-modal Weakly Supervised Dense Event Captioning. CoRR Tanzila Rahman, Bicheng Xu, Leonid Sigal
2018	J	`jnl`	Membership Inference Attack against Differentially Private Deep Learning Model. Trans. Data Priv. Md. Atiqur Rahman, Tanzila Rahman, Robert Laganière, Noman Mohammed
2018	J	`jnl`	Video-based Person Re-identification Using Spatial-Temporal Attention Networks. CoRR Shivansh Rao, Tanzila Rahman, Mrigank Rochan, Yang Wang
2017	A	`conf`	Person Re-Identification by Localizing Discriminative Regions. BMVC Tanzila Rahman, Mrigank Rochan, Yang Wang

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.