Takeshi Takahashi

12 papers A* 3A 2Journal 2Unranked 5

Year	Rank	Type	Title / Venue / Authors
2018	A	`conf`	Intrinsically Motivated Self-Supervised Deep Sensorimotor Learning for Grasping. IROS Takeshi Takahashi, Michael William Lanighan, Roderic A. Grupen
2018	A*	`conf`	Planning Robust Manual Tasks in Hierarchical Belief Spaces. ICAPS Michael William Lanighan, Takeshi Takahashi, Roderic A. Grupen
2017	A*	`conf`	Hybrid Task Planning Grounded in Belief: Constructing Physical Copies of Simple Structures. ICAPS Takeshi Takahashi, Michael William Lanighan, Roderic A. Grupen
2017	—	`conf`	Summary of Experiments in Belief-Space Planning at the Laboratory for Perceptual Robotics. AAAI Spring Symposia Scott Michael Jordan, Dirk Ruiken, Tiffany Q. Liu, Takeshi Takahashi, Michael William Lanighan, Roderic A. Grupen
2016	A	`conf`	Affordance-based Active Belief: Recognition using visual and manual actions. IROS Dirk Ruiken, Jay Ming Wong, Tiffany Q. Liu, Mitchell Hebert, Takeshi Takahashi, Michael William Lanighan, Roderic A. Grupen
2016	—	`conf`	Reconfigurable tasks in belief-space planning. Humanoids Dirk Ruiken, Tiffany Q. Liu, Takeshi Takahashi, Roderic A. Grupen
2015	—	`conf`	Continual planning for search and rescue robots. Humanoids Luis Enrique Pineda, Takeshi Takahashi, Hee-Tae Jung, Shlomo Zilberstein, Roderic A. Grupen
2015	—	`conf`	Efficient aspect object models using pre-trained convolutional neural networks. Humanoids Eric Wilkinson, Takeshi Takahashi
2013	—	`conf`	Towards extended virtual presence of the therapist in stroke rehabilitation. ICORR Hee-Tae Jung, Takeshi Takahashi, Yu-Kyong Choe, Jennifer Baird, Tammie Foster, Roderic A. Grupen
2008	J	`jnl`	An efficient system for combined route traversal and collision avoidance. Auton. Robots Bradley Hamner, Sanjiv Singh, Stephan Roth, Takeshi Takahashi
2003	A*	`conf`	Proposal and evaluation of natural language human-robot interface system based on conversation theory. ICRA Yasushi Nakauchi, Piyawat Naphattalung, Takeshi Takahashi, Takashi Matsubara, Eiichi Kashiwagi
2002	J	`jnl`	Commitment-based Natural Language Interface System for Robots. J. Robotics Mechatronics Yasushi Nakauchi, Takeshi Takahashi, Piyawat Naphattalung, Takashi Matsubara, Eiichi Kashiwagi

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.