Genki Kusano

11 papers A* 2A 3Journal 5Unranked 1

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	Are Large Language Models Really Effective for Training-Free Cold-Start Recommendation? CoRR Genki Kusano, Kenya Abe, Kunihiro Takeoka
2025	J	`jnl`	Few-Shot and Training-Free Review Generation via Conversational Prompting. CoRR Genki Kusano
2025	A	`conf`	Revisiting Prompt Engineering: A Comprehensive Evaluation for LLM-based Personalized Recommendation. RecSys Genki Kusano, Kosuke Akimoto, Kunihiro Takeoka
2025	J	`jnl`	Revisiting Prompt Engineering: A Comprehensive Evaluation for LLM-based Personalized Recommendation. CoRR Genki Kusano, Kosuke Akimoto, Kunihiro Takeoka
2024	J	`jnl`	Are Longer Prompts Always Better? Prompt Selection in Large Language Models for Recommendation Systems. CoRR Genki Kusano, Kosuke Akimoto, Kunihiro Takeoka
2024	A	`conf`	Data Augmentation using Reverse Prompt for Cost-Efficient Cold-Start Recommendation. RecSys Genki Kusano
2024	A*	`conf`	GA-Tag: Data Enrichment with an Automatic Tagging System Utilizing Large Language Models. ICDE Genki Kusano
2023	—	`conf`	Cross-Domain User Similarity without Overlapping Attributes via Optimal Transport Theory. eCom@SIGIR Genki Kusano, Masafumi Oyamada
2021	A	`conf`	User Identity Linkage for Different Behavioral Patterns across Domains. ICWSM Genki Kusano, Masafumi Oyamada
2017	J	`jnl`	Kernel Method for Persistence Diagrams via Kernel Embedding and Weight Factor. J. Mach. Learn. Res. Genki Kusano, Kenji Fukumizu, Yasuaki Hiraoka
2016	A*	`conf`	Persistence weighted Gaussian kernel for topological data analysis. ICML Genki Kusano, Yasuaki Hiraoka, Kenji Fukumizu

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.