Edric John Cruz Nacpil

15 papers Journal 12Unranked 3

Year	Rank	Type	Title / Venue / Authors
2024	J	`jnl`	Artificial Intelligence-Assisted Robustness of Optoelectronics for Automated Driving: A Review. IEEE Trans. Intell. Transp. Syst. Edric John Cruz Nacpil, JiYe Han, Il Jeon
2024	J	`jnl`	Evaluation of Visual Risk Perception of Automated Driving Tasks by Analyzing Gaze Pattern Dispersion. IEEE Trans. Intell. Veh. Chao Liu, Edric John Cruz Nacpil, Wenbin Hou, Yaling Qin, Rencheng Zheng
2024	J	`jnl`	Modeling Lateral Control Behavior of Driver for Manual Takeover of Automated Vehicles During Pedestrian Collision Avoidance. IEEE Trans. Veh. Technol. Feixiang Xu, Edric John Cruz Nacpil, Zheng Wang, Chen Zhou
2023	J	`jnl`	Modeling Lateral Control Behaviors of Distracted Drivers for Haptic-Shared Steering System. IEEE Trans. Intell. Transp. Syst. Feixiang Xu, Shi-Yong Feng, Edric John Cruz Nacpil, Zheng Wang, Guoqing Wang, Chen Zhou
2021	J	`jnl`	Effect of Adaptive and Fixed Shared Steering Control on Distracted Driver Behavior. CoRR Zheng Wang, Satoshi Suga, Edric John Cruz Nacpil, Bo Yang, Kimihiko Nakano
2021	J	`jnl`	Effect of Fixed and sEMG-Based Adaptive Shared Steering Control on Distracted Driver Behavior. Sensors Zheng Wang, Satoshi Suga, Edric John Cruz Nacpil, Bo Yang, Kimihiko Nakano
2021	J	`jnl`	Feasibility assessment of transfer functions describing biomechanics of the human lower limb during the gait cycle. Biomed. Signal Process. Control. Edric John Cruz Nacpil, Somer M. Nacy, George Youssef
2020	J	`jnl`	Adaptive driver-automation shared steering control via forearm surface electromyography measurement. CoRR Zheng Wang, Satoshi Suga, Edric John Cruz Nacpil, Zhanhong Yan, Kimihiko Nakano
2020	—	`conf`	Driving Simulator Validation of Machine Learning Classification for a Surface Electromyography-Based Steering Assistance Interface. AHFE (6) Edric John Cruz Nacpil, Kimihiko Nakano
2020	J	`jnl`	Modeling and analysis of driver behavior under shared control through weighted visual and haptic guidance. CoRR Zheng Wang, Rencheng Zheng, Edric John Cruz Nacpil, Kimihiko Nakano
2020	J	`jnl`	Surface Electromyography-Controlled Automobile Steering Assistance. Sensors Edric John Cruz Nacpil, Kimihiko Nakano
2020	J	`jnl`	Surface Electromyography-controlled Pedestrian Collision Avoidance: A Driving Simulator Study. CoRR Edric John Cruz Nacpil, Zheng Wang, Zhanhong Yan, Tsutomu Kaizuka, Kimihiko Nakano
2019	J	`jnl`	Design and Evaluation of a Surface Electromyography-Controlled Steering Assistance Interface. Sensors Edric John Cruz Nacpil, Zheng Wang, Rencheng Zheng, Tsutomu Kaizuka, Kimihiko Nakano
2019	—	`conf`	Driving Simulator Validation of Surface Electromyography Controlled Driving Assistance for Bilateral Transhumeral Amputees. AHFE (7) Edric John Cruz Nacpil, Tsutomu Kaizuka, Kimihiko Nakano
2017	—	`conf`	Implementation of a sEMG-Machine Interface for Steering a Virtual Car in a Driving Simulator. AHFE (7) Edric John Cruz Nacpil, Rencheng Zheng, Tsutomu Kaizuka, Kimihiko Nakano

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.