Abdulrahman Hamman Adama Chukkol

11 papers Journal 9Unranked 2
YearRankTypeTitle / Venue / Authors
2026 J jnl
KonvLiNA: integrating Kolmogorov-Arnold network with linear Nyström attention for feature fusion in crop disease detection.
Multim. Syst.
Yunusa Haruna, Shiyin Qin, Adamu Lawan, Abdulrahman Hamman Adama Chukkol, Ibrahim Haruna Abdulhamid
2025 J jnl
Exploring the synergies of hybrid convolutional neural network and Vision Transformer architectures for computer vision: A survey.
Eng. Appl. Artif. Intell.
Yunusa Haruna, Shiyin Qin, Abdulrahman Hamman Adama Chukkol, Abdulganiyu Abdu Yusuf, Isah Bello, Adamu Lawan
2025 J jnl
SaRPFF: A self-attention with register-based pyramid feature fusion module for enhanced rice leaf disease (RLD) detection.
Multim. Tools Appl.
Yunusa Haruna, Shiyin Qin, Abdulrahman Hamman Adama Chukkol, Isah Bello, Adamu Lawan
2024 J jnl
Exploring the Synergies of Hybrid CNNs and ViTs Architectures for Computer Vision: A survey.
CoRR
Yunusa Haruna, Shiyin Qin, Abdulrahman Hamman Adama Chukkol, Abdulganiyu Abdu Yusuf, Isah Bello, Adamu Lawan
2024 J jnl
Graph neural networks for visual question answering: a systematic review.
Multim. Tools Appl.
Abdulganiyu Abdu Yusuf, Chong Feng, Xianling Mao, Ramadhani Ally Duma, Mohammed Salah Abood, Abdulrahman Hamman Adama Chukkol
2024 J jnl
KonvLiNA: Integrating Kolmogorov-Arnold Network with Linear Nyström Attention for feature fusion in Crop Field Detection.
CoRR
Yunusa Haruna, Shiyin Qin, Adamu Lawan, Abdulrahman Hamman Adama Chukkol
2024 J jnl
VulCatch: Enhancing Binary Vulnerability Detection through CodeT5 Decompilation and KAN Advanced Feature Extraction.
CoRR
Abdulrahman Hamman Adama Chukkol, Senlin Luo, Kashif Sharif, Yunusa Haruna, Muhammad Muhammad Abdullahi
2024 J jnl
iiANET: Inception Inspired Attention Hybrid Network for efficient Long-Range Dependency.
CoRR
Yunusa Haruna, Shiyin Qin, Abdulrahman Hamman Adama Chukkol, Isah Bello, Adamu Lawan
2024 J jnl
mAPm: multi-scale Attention Pyramid module for Enhanced scale-variation in RLD detection.
CoRR
Yunusa Haruna, Shiyin Qin, Abdulrahman Hamman Adama Chukkol, Isah Bello, Adamu Lawan
2023 — conf
An approach to detecting extremely small or large objects based on an improved scale variation in YOLOv3.
ICMLT
Yunusa Haruna, Shiyin Qin, Peshraw Salam Abdulqadir, Mesmin J. Mbyamm Kiki, Abdulrahman Hamman Adama Chukkol
2023 — conf
VulPin: Finer-Grained Slicing for Pinpointing Vulnerability in Binary Programs.
CSAI
Abdulrahman Hamman Adama Chukkol, Senlin Luo, Yunusa Haruna, Abdulganiyu Abdu Yusuf, Abulfatahi Mohammed

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.

In 2025, he co-authored Assessing the Effectiveness of the Tigress Obfuscator Against MOPSA and BinaryNinja, published at CheckMATE. The paper evaluates the effectiveness of obfuscation techniques and their impact on source-level static analysis and binary-level decompilation.

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.