S. M. Taslim Uddin Raju

21 papers B 4Journal 15Unranked 2

Year	Rank	Type	Title / Venue / Authors
2025	—	`conf`	A Signer-Invariant Conformer and Multi-Scale Fusion Transformer for Continuous Sign Language Recognition. ICCVW Md. Rezwanul Haque, Md. Milon Islam, S. M. Taslim Uddin Raju, Fakhri Karray
2025	J	`jnl`	A Signer-Invariant Conformer and Multi-Scale Fusion Transformer for Continuous Sign Language Recognition. CoRR Md. Rezwanul Haque, Md. Milon Islam, S. M. Taslim Uddin Raju, Fakhri Karray
2025	J	`jnl`	Bridging Brain with Foundation Models through Self-Supervised Learning. CoRR Hamdi Altaheri, Fakhri Karray, Md. Milon Islam, S. M. Taslim Uddin Raju, Amir-Hossein Karimi
2025	J	`jnl`	FusionEnsemble-Net: An Attention-Based Ensemble of Spatiotemporal Networks for Multimodal Sign Language Recognition. CoRR Md. Milon Islam, Md. Rezwanul Haque, S. M. Taslim Uddin Raju, Fakhri Karray
2025	—	`conf`	FusionEnsembleNet: An Attention-Based Ensemble of Spatiotemporal Networks for Multimodal Sign Language Recognition. ICCVW Md. Milon Islam, Md. Rezwanul Haque, S. M. Taslim Uddin Raju, Fakhri Karray
2025	B	`conf`	GNN-ViTCap: GNN-Enhanced Multiple Instance Learning with Vision Transformers for Whole Slide Image Classification and Captioning. IJCNN S. M. Taslim Uddin Raju, Md. Milon Islam, Md. Rezwanul Haque, Hamdi Altaheri, Fakhri Karray
2025	J	`jnl`	GNN-ViTCap: GNN-Enhanced Multiple Instance Learning with Vision Transformers for Whole Slide Image Classification and Captioning. CoRR S. M. Taslim Uddin Raju, Md. Milon Islam, Md. Rezwanul Haque, Hamdi Altaheri, Fakhri Karray
2025	B	`conf`	MDD-Net: Multimodal Depression Detection through Mutual Transformer. SMC Md. Rezwanul Haque, Md. Milon Islam, S. M. Taslim Uddin Raju, Hamdi Altaheri, Lobna Nassar, Fakhri Karray
2025	J	`jnl`	MDD-Net: Multimodal Depression Detection through Mutual Transformer. CoRR Md. Rezwanul Haque, Md. Milon Islam, S. M. Taslim Uddin Raju, Hamdi Altaheri, Lobna Nassar, Fakhri Karray
2025	B	`conf`	MMFformer: Multimodal Fusion Transformer Network for Depression Detection. SMC Md. Rezwanul Haque, Md. Milon Islam, S. M. Taslim Uddin Raju, Hamdi Altaheri, Lobna Nassar, Fakhri Karray
2025	J	`jnl`	MMFformer: Multimodal Fusion Transformer Network for Depression Detection. CoRR Md. Rezwanul Haque, Md. Milon Islam, S. M. Taslim Uddin Raju, Hamdi Altaheri, Lobna Nassar, Fakhri Karray
2024	J	`jnl`	DNN-BP: a novel framework for cuffless blood pressure measurement from optimal PPG features using deep learning model. Medical Biol. Eng. Comput. S. M. Taslim Uddin Raju, Safin Ahmed Dipto, Md Imran Hossain, Md. Abu Shahid Chowdhury, Fabliha Haque, Ayesha Tun Nashrah, Araf Nishan, Md Mahamudul Hasan Khan, M. M. A. Hashem
2024	B	`conf`	TransUAAE-CapGen: Caption Generation from Histopathological Patches through Transformer and UNet-Based Adversarial Autoencoder. SMC S. M. Taslim Uddin Raju, Abdul Raqeeb Mohammad, Md. Milon Islam, Fakhri Karray
2022	J	`jnl`	An Approach for Demand Forecasting in Steel Industries Using Ensemble Learning. Complex. S. M. Taslim Uddin Raju, Amlan Sarker, Apurba Das, Md. Milon Islam, Mabrook S. Al-Rakhami, Atif Alamri, Tasniah Mohiuddin, Fahad R. Albogamy
2021	J	`jnl`	A Novel Technique for Non-Invasive Measurement of Human Blood Component Levels From Fingertip Video Using DNN Based Models. IEEE Access Md. Rezwanul Haque, S. M. Taslim Uddin Raju, Md. Asaf-Uddowla Golap, M. M. A. Hashem
2021	J	`jnl`	Corrections to "A Novel Technique for Non-Invasive Measurement of Human Blood Component Levels From Fingertip Video Using DNN Based Models". IEEE Access Md. Rezwanul Haque, S. M. Taslim Uddin Raju, Md. Asaf-Uddowla Golap, M. M. A. Hashem
2021	J	`jnl`	Dermo-DOCTOR: A framework for concurrent skin lesion detection and recognition using a deep convolutional neural network with end-to-end dual encoders. Biomed. Signal Process. Control. Md. Kamrul Hasan, Shidhartho Roy, Chayan Mondal, Md. Ashraful Alam, Md. Toufick E. Elahi, Aishwariya Dutta, S. M. Taslim Uddin Raju, Md. Tasnim Jawad, Mohiuddin Ahmad
2021	J	`jnl`	Dermo-DOCTOR: A framework for concurrent skin lesion detection and recognition using a deep convolutional neural network with end-to-end dual encoders. CoRR Md. Kamrul Hasan, Shidhartho Roy, Chayan Mondal, Md. Ashraful Alam, Md. Toufick E. Elahi, Aishwariya Dutta, S. M. Taslim Uddin Raju, Md. Tasnim Jawad, Mohiuddin Ahmad
2021	J	`jnl`	Hemoglobin and glucose level estimation from PPG characteristics features of fingertip video using MGGP-based model. Biomed. Signal Process. Control. Md. Asaf-Uddowla Golap, S. M. Taslim Uddin Raju, Md. Rezwanul Haque, M. M. A. Hashem
2021	J	`jnl`	Scalable Telehealth Services to Combat Novel Coronavirus (COVID-19) Pandemic. SN Comput. Sci. Shah Muhammad Azmat Ullah, Md. Milon Islam, Saifuddin Mahmud, Sheikh Nooruddin, S. M. Taslim Uddin Raju, Md. Rezwanul Haque
2020	J	`jnl`	Breathing Aid Devices to Support Novel Coronavirus (COVID-19)Infected Patients. SN Comput. Sci. Md. Milon Islam, Shah Muhammad Azmat Ullah, Saifuddin Mahmud, S. M. Taslim Uddin Raju

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.