Taewon Park - RankMe

15 papers A* 3Journal 9Unranked 3

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	HVR-SSLE: Hierarchical Visual Reasoning for Self-Supervised Low-Light Image Enhancement. IEEE Access Dongwon Choo, Qikang Deng, Taewon Park, Dohoon Lee
2025	A*	`conf`	PoP-ECC: Robust and Flexible Error Correction against Multi-Bit Upsets in DNN Accelerators. DAC Taewon Park, Saeid Gorgin, Dongwhee Kim, Jaeho Shin, Michael B. Sullivan, Jungrae Kim
2024	A*	`conf`	Attention-based Iterative Decomposition for Tensor Product Representation. ICLR Taewon Park, Inchul Choi, Minho Lee
2024	J	`jnl`	Attention-based Iterative Decomposition for Tensor Product Representation. CoRR Taewon Park, Inchul Choi, Minho Lee
2024	A*	`conf`	Discrete Dictionary-based Decomposition Layer for Structured Representation Learning. NeurIPS Taewon Park, Hyun-Chul Kim, Minho Lee
2024	J	`jnl`	Discrete Dictionary-based Decomposition Layer for Structured Representation Learning. CoRR Taewon Park, Hyun-Chul Kim, Minho Lee
2022	J	`jnl`	Experimental evaluation of digitally-verifiable photonic computing for blockchain and cryptocurrency. CoRR Sunil Pai, Taewon Park, Marshall Ball, Bogdan Penkovsky, Maziyar Milanizadeh, Michael Dubrovsky, Nathnael Abebe, Francesco Morichetti, Andrea Melloni, Shanhui Fan, Olav Solgaard, David A. B. Miller
2022	J	`jnl`	Experimentally realized in situ backpropagation for deep learning in nanophotonic neural networks. CoRR Sunil Pai, Zhanghao Sun, Tyler W. Hughes, Taewon Park, Ben Bartlett, Ian A. D. Williamson, Momchil Minkov, Maziyar Milanizadeh, Nathnael Abebe, Francesco Morichetti, Andrea Melloni, Shanhui Fan, Olav Solgaard, David A. B. Miller
2022	—	`conf`	Learning Associative Reasoning Towards Systematicity Using Modular Networks. ICONIP (2) Jun-Hyun Bae, Taewon Park, Minho Lee
2022	J	`jnl`	Multi-Prediction Compression: An Efficient and Scalable Memory Compression Framework for GP-GPU. IEEE Comput. Archit. Lett. Hoyong Jin, Donghun Jeong, Taewon Park, Jong Hwan Ko, Jungrae Kim
2021	—	`conf`	4W1H Keyword Extraction based Summarization Model. ICEIC Seungyeon Lee, Taewon Park, Minho Lee
2021	J	`jnl`	Distributed associative memory network with memory refreshing loss. Neural Networks Taewon Park, Inchul Choi, Minho Lee
2020	J	`jnl`	Distributed Memory based Self-Supervised Differentiable Neural Computer. CoRR Taewon Park, Inchul Choi, Minho Lee
2011	—	`conf`	A Verification Tool for Splice Junction Sites on Whole Genome with Massive Reads. FGIT-DTA/BSBT Sora Kim, Taewon Park, Kiejung Park, Hwan-Gue Cho
2005	J	`jnl`	Transmit power allocation for a downlink two-user interference channel. IEEE Commun. Lett. Taewon Park, Jiho Jang, Oh-Soon Shin, Kwang Bok Lee

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.