Tae-Yoon Kim

14 papers C 1Journal 3Unranked 10

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Multiagent Deep Reinforcement Learning for Joint Movement and User Association of UAV-BS Emergency Indoor User Service. IEEE Internet Things J. Tae-Yoon Kim, Jihong Park, Junghwa Kang, Jaeyeol Lee, Soyi Jung, Jae-Hyun Kim
2025	—	`conf`	Joint Movement and User Association of UAV-BS for Indoor User Service: A Multi-Agent Deep Reinforcement Learning Approach. CCNC Tae-Yoon Kim, Yujeong Ahn, Jaeyeol Lee, Jae-Hyun Kim
2025	—	`conf`	Optimization Satellite Power Control in Integrated Non-Terrestrial Networks Using Multi-Agent Deep Reinforcement Learning. CCNC Jaeyeol Lee, Won-Jae Lee, Tae-Yoon Kim, Taehan Moon, Jae-Hyun Kim
2025	—	`conf`	Optimizing Beam-Hopping in LEO Constellation Systems with Random Cell Traffic Using Multi-Agent Reinforcement Learning. VTC2025-Spring Jaeyeol Lee, Tae-Yoon Kim, Taehan Moon, Youngpo Lee, Dongwook Kim, Takki Yu, Jae-Hyun Kim
2024	J	`jnl`	Group contention-based full-duplex unmanned aerial vehicle relay system. ICT Express Won-Jae Lee, Tae-Yoon Kim, Jin-Ki Kim, Soyi Jung, Jae-Hyun Kim
2024	—	`conf`	Performance Evaluation of Distance-Based Handover Using LSTM in LEO-Based NTN. ICTC Yujeong Ahn, Jongtae Lee, Tae-Yoon Kim, Jae-Hyun Kim
2023	—	`conf`	Deep Reinforcement Learning-Based Full-Duplex Communication UAV Base Station Trajectory Optimization in Disaster Environments. APWCS Tae-Yoon Kim, Jaeyeol Lee, Jae-Hyun Kim
2023	J	`jnl`	Energy-efficient full-duplex MAC protocol design for air-terrestrial communication. J. Commun. Networks Tae-Yoon Kim, Jin-Ki Kim, Won-Jae Lee, Soyi Jung, Jae-Hyun Kim
2023	—	`conf`	Performance Analysis of Multiple High Altitude Platform Stations Cellular Network Coverage. ICTC Jaeyeol Lee, Tae-Yoon Kim, Jae-Hyun Kim
2023	C	`conf`	WIP: Performance Evaluation of Angle-based Handover in LEO-based NTN. WoWMoM Jina Yu, Tae-Yoon Kim, Jae-Hyun Kim
2022	—	`conf`	Deep Reinforcement Learning based SAR Image Pre-Processing Algorithm with Finite Buffer LEO Satellite Networks. ICTC Tae-Yoon Kim, Kyeong-Rok Kim, Jae-Hyun Kim
2021	—	`conf`	A Design of Hybrid CSMA using Sequential-based Scheduling Algorithm. ICTC Tae-Yoon Kim, Lara Fernandez Capon, Hyuk Park, Jae-Hyun Kim
2021	—	`conf`	Performance Evaluation of Wireless LAN for UAS Communication. ICOIN Tae-Yoon Kim, Jun-Woo Cho, Jae-Hyun Kim
2020	—	`conf`	Implementation of unmanned aerial system for surveillance mode. ICTC Tae-Yoon Kim, Jae-Hyun Kim

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.

In 2025, he co-authored Assessing the Effectiveness of the Tigress Obfuscator Against MOPSA and BinaryNinja, published at CheckMATE. The paper evaluates the effectiveness of obfuscation techniques and their impact on source-level static analysis and binary-level decompilation.

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.