Fares Al-Shargie

31 papers A* 1B 2Journal 18Unranked 10

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	EEG-Based Multi-Level Mental State Classification Using Partial Directed Coherence and Graph Convolutional Networks: Impact of Binaural Beats on Stress Mitigation. IEEE Access Yara Badr, Fares Al-Shargie, Malik Nasir Afzal Khan, Nour Faris Ali, Usman Tariq, Fadwa Al-Mughairbi, Fabio Babiloni, Hasan Al-Nashash
2025	J	`jnl`	Patch-Based and Non-Patch-Based inputs Comparison into Deep Neural Models: Application for the Segmentation of Retinal Diseases on Optical Coherence Tomography Volumes. CoRR Khaled Alsaih, Fares Al-Shargie, Mohammed Isam Al-Hiyali, Reham Alhejaili
2024	J	`jnl`	A review on evaluating mental stress by deep learning using EEG signals. Neural Comput. Appl. Yara Badr, Usman Tariq, Fares Al-Shargie, Fabio Babiloni, Fadwa Al-Mughairbi, Hasan Al-Nashash
2024	—	`conf`	Detecting Deepfakes with Super-Resolution EEG. EMBC Ramzi Al-Sharawi, Hamza Athar, Muhammad Riyyan Khan, Usman Tariq, Fares Al-Shargie, Abhinav Dhall, Hasan Al-Nashash
2024	—	`conf`	Discrimination of Real and Deep Fake Videos using EEG Signals. EMBC Muhammad Riyyan Khan, Hasan Saeed Mir, Fares Al-Shargie, Usman Tariq, Abhinav Dhall, Shahzeb Naeem, Malik Nasir Afzal Khan, Hasan Al-Nashash
2024	J	`jnl`	Mental Stress Assessment in the Workplace: A Review. IEEE Trans. Affect. Comput. Ghinwa Masri, Fares Al-Shargie, Usman Tariq, Fadwa Al-Mughairbi, Fabio Babiloni, Hasan Al-Nashash
2024	J	`jnl`	One-Channel Wearable Mental Stress State Monitoring System. Sensors Lamis Abdul Kader, Fares Al-Shargie, Usman Tariq, Hasan Al-Nashash
2023	—	`conf`	Assessment of Mental Stress During 240-Days Isolation and Confined Environment using EEG Signals. NER Fares Al-Shargie, Saleh Al-Ameri, Abdulla Al-Hammadi, Schastlivtseva Daria Vladimirovna, Usman Tariq, Hasan Al-Nashash
2023	—	`conf`	Classification of Mental Stress Levels using EEG Connectivity and Convolutional Neural Networks. EMBC Fares Al-Shargie, Yara Badr, Usman Tariq, Fabio Babiloni, Fadwa Al-Mughairbi, Hasan Al-Nashash
2023	—	`conf`	Detection of Astronaut's Stress Levels During 240-Day Confinement using EEG Signals and Machine Learning. EMBC Fares Al-Shargie, Saleh Al-Ameri, Abdulla Al-Hammadi, Schastlivtseva Daria Vladimirovna, Usman Tariq, Hasan Al-Nashash
2023	—	`conf`	Exploring Neurophysiological Responses to Cross-Cultural Deepfake Videos. ICMI Companion Muhammad Riyyan Khan, Shahzeb Naeem, Usman Tariq, Abhinav Dhall, Malik Nasir Afzal Khan, Fares Al-Shargie, Hasan Al-Nashash
2023	—	`conf`	Mental Stress Detection and Mitigation using Machine Learning and Binaural Beat Stimulation. EMBC Yara Badr, Fares Al-Shargie, Usman Tariq, Fabio Babiloni, Fadwa Al-Mughairbi, Hasan Al-Nashash
2022	J	`jnl`	Brain Region-Based Vigilance Assessment Using Electroencephalography and Eye Tracking Data Fusion. IEEE Access Nadia Abu Farha, Fares Al-Shargie, Usman Tariq, Hasan Al-Nashash
2022	J	`jnl`	Complexity Analysis of EEG in Patients With Social Anxiety Disorder Using Fuzzy Entropy and Machine Learning Techniques. IEEE Access Abdulhakim Al-Ezzi, Amal A. Al-Shargabi, Fares Al-Shargie, Ammar T. Zahary
2022	J	`jnl`	Discriminating Fake and Real Smiles Using Electroencephalogram Signals With Convolutional Neural Networks. IEEE Access Mostafa Moussa, Usman Tariq, Fares Al-Shargie, Hasan Al-Nashash
2022	J	`jnl`	Improved Cognitive Vigilance Assessment after Artifact Reduction with Wavelet Independent Component Analysis. Sensors Nadia Abu Farha, Fares Al-Shargie, Usman Tariq, Hasan Al-Nashash
2022	B	`conf`	Mental Stress Assessment Using fNIRS and LSTM. SMC Rateb Katmah, Fares Al-Shargie, Usman Tariq, Fabio Babiloni, Fadwa Al-Mughairbi, Hasan Al-Nashash
2022	A*	`conf`	Sentiment-aware Classifier for Out-of-Context Caption Detection. ACM Multimedia Muhannad Alkaddour, Abhinav Dhall, Usman Tariq, Hasan Al-Nashash, Fares Al-Shargie
2021	J	`jnl`	A Review on Mental Stress Assessment Methods Using EEG Signals. Sensors Rateb Katmah, Fares Al-Shargie, Usman Tariq, Fabio Babiloni, Fadwa Al-Mughairbi, Hasan Al-Nashash
2021	J	`jnl`	Cognitive Vigilance Enhancement Using Audio Stimulation of Pure Tone at 250 Hz. IEEE Access Fares Al-Shargie, Usman Tariq, Fabio Babiloni, Hasan Al-Nashash
2021	J	`jnl`	EEG Mental Stress Assessment Using Hybrid Multi-Domain Feature Sets of Functional Connectivity Network and Time-Frequency Features. Sensors Ala Hag, Dini Oktarina Dwi Handayani, Thulasyammal Pillai, Teddy Mantoro, Hou Kit Mun, Fares Al-Shargie
2021	J	`jnl`	Enhancing EEG-Based Mental Stress State Recognition Using an Improved Hybrid Feature Selection Algorithm. Sensors Ala Hag, Dini Oktarina Dwi Handayani, Maryam Altalhi, Thulasyammal Pillai, Teddy Mantoro, Hou Kit Mun, Fares Al-Shargie
2021	B	`conf`	Stress Assessment and Mitigation using fNIRS and Binaural Beat Stimulation. SMC Fares Al-Shargie, Rateb Katmah, Usman Tariq, Fabio Babiloni, Fadwa Al-Mughairbi, Hasan Al-Nashash
2020	J	`jnl`	Discrimination of Genuine and Acted Emotional Expressions Using EEG Signal and Machine Learning. IEEE Access Meera Alex, Usman Tariq, Fares Al-Shargie, Hasan Saeed Mir, Hasan Al-Nashash
2020	J	`jnl`	EEG-Based Semantic Vigilance Level Classification Using Directed Connectivity Patterns and Graph Theory Analysis. IEEE Access Fares Al-Shargie, Omnia Hassanin, Usman Tariq, Hasan Al-Nashash
2019	—	`conf`	Discerning Genuine and Acted Smiles Using Neural Networks. ISSPIT Mostafa Moussa, Usman Tariq, Hasan Al-Nashash, Fares Al-Shargie
2019	J	`jnl`	Emotion Recognition Based on Fusion of Local Cortical Activations and Dynamic Functional Networks Connectivity: An EEG Study. IEEE Access Fares Al-Shargie, Usman Tariq, Meera Alex, Hasan Saeed Mir, Hasan Al-Nashash
2018	J	`jnl`	Towards multilevel mental stress assessment using SVM with ECOC: an EEG approach. Medical Biol. Eng. Comput. Fares Al-Shargie, Tong Boon Tang, Nasreen Badruddin, Masashi Kiguchi
2017	J	`jnl`	Stress Assessment Based on Decision Fusion of EEG and fNIRS Signals. IEEE Access Fares Al-Shargie, Tong Boon Tang, Masashi Kiguchi
2016	—	`conf`	Mental stress grading based on fNIRS signals. EMBC Fares Al-Shargie, Tong Boon Tang, Masashi Kiguchi
2015	—	`conf`	Simultaneous measurement of EEG-fNIRS in classifying and localizing brain activation to mental stress. ICSIPA Fares Al-Shargie, Tong Boon Tang, Nasreen Badruddin, Masashi Kiguchi

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.