Da-Woon Heo - RankMe

18 papers A* 1Journal 14Unranked 3

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Complex wavelet-based Transformer for neurodevelopmental disorder diagnosis via direct modeling of real and imaginary components. Medical Image Anal. Ah-Yeong Jeong, Da-Woon Heo, Heung-Il Suk
2026	J	`jnl`	Explainable Normative Modeling for Brain Disorder Identification in Resting-State fMRI. IEEE Trans. Medical Imaging Yeajin Shon, Eunsong Kang, Da-Woon Heo, Heung-Il Suk
2026	J	`jnl`	FIESTA: Fourier-Based Semantic Augmentation With Uncertainty Guidance for Enhanced Domain Generalizability in Medical Image Segmentation. IEEE Trans. Neural Networks Learn. Syst. Kwanseok Oh, Eunjin Jeon, Da-Woon Heo, Yooseung Shin, Heung-Il Suk
2026	A*	`conf`	HyFI: Hyperbolic Feature Interpolation for Brain-Vision Alignment. AAAI Sangmin Jo, Wootaek Jeong, Da-Woon Heo, Yoohwan Hwang, Heung-Il Suk
2026	J	`jnl`	HyFI: Hyperbolic Feature Interpolation for Brain-Vision Alignment. CoRR Sangmin Jo, Wootaek Jeong, Da-Woon Heo, Yoohwan Hwang, Heung-Il Suk
2026	J	`jnl`	Transferring ultrahigh-field representations for intensity-guided brain segmentation of low-field magnetic resonance imaging. Pattern Recognit. Kwanseok Oh, Jieun Lee, Da-Woon Heo, Dinggang Shen, Heung-Il Suk
2025	J	`jnl`	A quantitatively interpretable model for Alzheimer's disease prediction using deep counterfactuals. NeuroImage Kwanseok Oh, Da-Woon Heo, Ahmad Wisnu Mulyadi, Wonsik Jung, Eunsong Kang, Kun Ho Lee, Heung-Il Suk
2024	J	`jnl`	A Learnable Counter-Condition Analysis Framework for Functional Connectivity-Based Neurological Disorder Diagnosis. IEEE Trans. Medical Imaging Eunsong Kang, Da-Woon Heo, Jiwon Lee, Heung-Il Suk
2024	—	`conf`	BrainWaveNet: Wavelet-Based Transformer for Autism Spectrum Disorder Diagnosis. MICCAI (2) Ah-Yeong Jeong, Da-Woon Heo, Eunsong Kang, Heung-Il Suk
2024	J	`jnl`	FIESTA: Fourier-Based Semantic Augmentation with Uncertainty Guidance for Enhanced Domain Generalizability in Medical Image Segmentation. CoRR Kwanseok Oh, Eunjin Jeon, Da-Woon Heo, Yooseung Shin, Heung-Il Suk
2024	J	`jnl`	Medical Transformer: Universal Encoder for 3-D Brain MRI Analysis. IEEE Trans. Neural Networks Learn. Syst. Eunji Jun, Seungwoo Jeong, Da-Woon Heo, Heung-Il Suk
2024	J	`jnl`	Site-Invariant Meta-Modulation Learning for Multisite Autism Spectrum Disorders Diagnosis. IEEE Trans. Neural Networks Learn. Syst. Jaein Lee, Eunsong Kang, Da-Woon Heo, Heung-Il Suk
2024	J	`jnl`	Transferring Ultrahigh-Field Representations for Intensity-Guided Brain Segmentation of Low-Field Magnetic Resonance Imaging. CoRR Kwanseok Oh, Jieun Lee, Da-Woon Heo, Dinggang Shen, Heung-Il Suk
2023	J	`jnl`	A Learnable Counter-condition Analysis Framework for Functional Connectivity-based Neurological Disorder Diagnosis. CoRR Eunsong Kang, Da-Woon Heo, Jiwon Lee, Heung-Il Suk
2023	J	`jnl`	A Quantitatively Interpretable Model for Alzheimer's Disease Prediction Using Deep Counterfactuals. CoRR Kwanseok Oh, Da-Woon Heo, Ahmad Wisnu Mulyadi, Wonsik Jung, Eunsong Kang, Kun Ho Lee, Heung-Il Suk
2022	—	`conf`	Prototype Learning of Inter-network Connectivity for ASD Diagnosis and Personalized Analysis. MICCAI (3) Eunsong Kang, Da-Woon Heo, Heung-Il Suk
2021	—	`conf`	Inter-regional High-Level Relation Learning from Functional Connectivity via Self-supervision. MICCAI (2) Wonsik Jung, Da-Woon Heo, Eunjin Jeon, Jaein Lee, Heung-Il Suk
2021	J	`jnl`	Medical Transformer: Universal Brain Encoder for 3D MRI Analysis. CoRR Eunji Jun, Seungwoo Jeong, Da-Woon Heo, Heung-Il Suk

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.