Ran Wang - RankMe

17 papers A* 1C 4Journal 9Unranked 3

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	Information-State-Based Reinforcement Learning for the Control of Partially Observed Nonlinear Systems. IEEE Trans. Neural Networks Learn. Syst. Raman Goyal, Mohamed Naveed Gul Mohamed, Ran Wang, Aayushman Sharma, Suman Chakravorty
2025	C	`conf`	Information-state based Approach to the Optimal Output Feedback Control of Nonlinear Systems. ACC Raman Goyal, Mohamed Naveed Gul Mohamed, Ran Wang, Aayushman Sharma, Suman Chakravorty
2025	C	`conf`	The Search for Feedback in Reinforcement Learning. ACC Ran Wang, Aayushman Sharma, Karthikeya S. Parunandi, Raman Goyal, Mohamed Naveed Gul Mohamed, Suman Chakravorty
2023	—	`conf`	Learning to Control Under Uncertainty with Data-Based Iterative Linear Quadratic Regulator. CDC Ran Wang, Raman Goyal, Suman Chakravorty
2023	J	`jnl`	Learning to Control under Uncertainty with Data-Based Iterative Linear Quadratic Regulator. CoRR Ran Wang, Raman Goyal, Suman Chakravorty
2023	C	`conf`	The Information-State Based Approach to Linear System Identification. ACC Mohamed Naveed Gul Mohamed, Raman Goyal, Suman Chakravorty, Ran Wang
2022	J	`jnl`	Decoupled Data-Based Approach for Learning to Control Nonlinear Dynamical Systems. IEEE Trans. Autom. Control. Ran Wang, Karthikeya S. Parunandi, Dan Yu, Dileep M. Kalathil, Suman Chakravorty
2022	C	`conf`	On the Feedback Law in Stochastic Optimal Nonlinear Control. ACC Mohamed Naveed Gul Mohamed, Suman Chakravorty, Raman Goyal, Ran Wang
2022	J	`jnl`	The Information-State Based Approach to Linear System Identification. CoRR Mohamed Naveed Gul Mohamed, Raman Goyal, Suman Chakravorty, Ran Wang
2021	A*	`conf`	Data-based Control of Partially-Observed Robotic Systems. ICRA Ran Wang, Raman Goyal, Suman Chakravorty, Robert E. Skelton
2021	—	`conf`	On the Convergence of Reinforcement Learning in Nonlinear Continuous State Space Problems. CDC Raman Goyal, Suman Chakravorty, Ran Wang, Mohamed Naveed Gul Mohamed
2021	—	`conf`	On the Search for Feedback in Reinforcement Learning. CDC Ran Wang, Karthikeya S. Parunandi, Aayushman Sharma, Raman Goyal, Suman Chakravorty
2021	J	`jnl`	Partially-Observed Decoupled Data-based Control (POD2C) for Complex Robotic Systems. CoRR Raman Goyal, Ran Wang, Suman Chakravorty, Robert E. Skelton
2020	J	`jnl`	Model and Data Based Approaches to the Control of Tensegrity Robots. IEEE Robotics Autom. Lett. Ran Wang, Raman Goyal, Suman Chakravorty, Robert E. Skelton
2020	J	`jnl`	On the Convergence of Reinforcement Learning. CoRR Suman Chakravorty, Ran Wang, Mohamed Naveed Gul Mohamed
2020	J	`jnl`	On the Search for Feedback in Reinforcement Learning. CoRR Ran Wang, Karthikeya S. Parunandi, Dan Yu, Dileep M. Kalathil, Suman Chakravorty
2019	J	`jnl`	Decoupled Data Based Approach for Learning to Control Nonlinear Dynamical Systems. CoRR Ran Wang, Karthikeya S. Parunandi, Dan Yu, Dileep M. Kalathil, Suman Chakravorty

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.