Daehan Kim - RankMe

14 papers A* 2Journal 11Unranked 1

Year	Rank	Type	Title / Venue / Authors
2023	A*	`conf`	Bidirectional Domain Mixup for Domain Adaptive Semantic Segmentation. AAAI Daehan Kim, Minseok Seo, Kwanyong Park, Inkyu Shin, Sanghyun Woo, In So Kweon, Dong-Geol Choi
2023	J	`jnl`	Bidirectional Domain Mixup for Domain Adaptive Semantic Segmentation. CoRR Daehan Kim, Minseok Seo, Kwanyong Park, Inkyu Shin, Sanghyun Woo, In-So Kweon, Dong-Geol Choi
2023	J	`jnl`	VisDA 2022 Challenge: Domain Adaptation for Industrial Waste Sorting. CoRR Dina Bashkirova, Samarth Mishra, Diala Lteif, Piotr Teterwak, Donghyun Kim, Fadi M. Alladkani, James Akl, Berk Çalli, Sarah Adel Bargal, Kate Saenko, Daehan Kim, Minseok Seo, Youngjin Jeon, Dong-Geol Choi, Shahaf Ettedgui, Raja Giryes, Shady Abu-Hussein, Binhui Xie, Shuang Li
2022	J	`jnl`	1st Place Solution to NeurIPS 2022 Challenge on Visual Domain Adaptation. CoRR Daehan Kim, Minseok Seo, Youngjin Jeon, Dong-Geol Choi
2022	J	`jnl`	A Self-Supervised Sampler for Efficient Action Recognition: Real-World Applications in Surveillance Systems. IEEE Robotics Autom. Lett. Minseok Seo, Donghyeon Cho, Sangwoo Lee, Jongchan Park, Daehan Kim, Jaemin Lee, Jingi Ju, Hyeoncheol Noh, Dong-Geol Choi
2022	J	`jnl`	Source Domain Subset Sampling for Semi-Supervised Domain Adaptation in Semantic Segmentation. CoRR Daehan Kim, Minseok Seo, Jinsun Park, Dong-Geol Choi
2021	J	`jnl`	Diagnostic Assessment Generation via Combinatorial Search. CoRR Daehan Kim, Hyeonseong Choi, Guik Jung
2021	J	`jnl`	Masked Deep Q-Recommender for Effective Question Scheduling. CoRR Keunhyung Chung, Daehan Kim, Sangheon Lee, Guik Jung
2021	A*	`conf`	OCR-based Inventory Management Algorithms Robust to Damaged Images. ICRA Minseok Seo, Daehan Kim, Hyeyoon Kang, Donghyeon Cho, Dong-Geol Choi
2021	J	`jnl`	Sequential Feature Filtering Classifier. IEEE Access Minseok Seo, Jaemin Lee, Jongchan Park, Daehan Kim, Dong-Geol Choi
2021	—	`conf`	VisDA 2022 Challenge: Domain Adaptation for Industrial Waste Sorting. NeurIPS (Competition and Demos) Dina Bashkirova, Samarth Mishra, Diala Lteif, Piotr Teterwak, Donghyun Kim, Fadi M. Alladkani, James Akl, Berk Çalli, Sarah Adel Bargal, Kate Saenko, Daehan Kim, Minseok Seo, Youngjin Jeon, Dong-Geol Choi, Shahaf Ettedgui, Raja Giryes, Shady Abu-Hussein, Binhui Xie, Shuang Li
2021	J	`jnl`	Zero Assignment via Generalized Sampler: A Countermeasure Against Zero-Dynamics Attack. IEEE Access Daehan Kim, Kunhee Ryu, Jung Hoon Kim, Juhoon Back
2020	J	`jnl`	ChimerDB 4.0: an updated and expanded database of fusion genes. Nucleic Acids Res. Ye Eun Jang, Insu Jang, Sunkyu Kim, Subin Cho, Daehan Kim, Keonwoo Kim, Jaewon Kim, Jimin Hwang, Sangok Kim, Jaesang Kim, Jaewoo Kang, Byungwook Lee, Sanghyuk Lee
2019	J	`jnl`	Can Machines Learn to Comprehend Scientific Literature? IEEE Access Donghyeon Park, Yonghwa Choi, Daehan Kim, Minhwan Yu, Seongsoon Kim, Jaewoo Kang

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.