Gavin Weiguang Ding

25 papers A* 3A 1Journal 14Unranked 7

Year	Rank	Type	Title / Venue / Authors
2021	J	`jnl`	LF-UNet - A novel anatomical-aware dual-branch cascaded deep neural network for segmentation of retinal layers and fluid from optical coherence tomography images. Comput. Medical Imaging Graph. Da Ma, Donghuan Lu, Shuo Chen, Morgan Heisler, Setareh Dabiri, Sieun Lee, Hyunwoo Lee, Gavin Weiguang Ding, Marinko V. Sarunic, Mirza Faisal Beg
2020	J	`jnl`	CDT: Cascading Decision Trees for Explainable Reinforcement Learning. CoRR Zihan Ding, Pablo Hernandez-Leal, Gavin Weiguang Ding, Changjian Li, Ruitong Huang
2020	—	`conf`	Cascade Dual-branch Deep Neural Networks for Retinal Layer and fluid Segmentation of Optical Coherence Tomography Incorporating Relative Positional Map. MIDL Da Ma, Donghuan Lu, Morgan Heisler, Setareh Dabiri, Sieun Lee, Gavin Weiguang Ding, Marinko V. Sarunic, Mirza Faisal Beg
2020	A*	`conf`	MMA Training: Direct Input Space Margin Maximization through Adversarial Training. ICLR Gavin Weiguang Ding, Yash Sharma, Kry Yik Chau Lui, Ruitong Huang
2020	A	`conf`	On Minimax Optimality of GANs for Robust Mean Estimation. AISTATS Kaiwen Wu, Gavin Weiguang Ding, Ruitong Huang, Yaoliang Yu
2019	J	`jnl`	Cascaded Deep Neural Networks for Retinal Layer Segmentation of Optical Coherence Tomography with Fluid Presence. CoRR Donghuan Lu, Morgan Heisler, Da Ma, Setareh Dabiri, Sieun Lee, Gavin Weiguang Ding, Marinko V. Sarunic, Mirza Faisal Beg
2019	J	`jnl`	Deep-learning based multiclass retinal fluid segmentation and detection in optical coherence tomography images using a fully convolutional neural network. Medical Image Anal. Donghuan Lu, Morgan Heisler, Sieun Lee, Gavin Weiguang Ding, Eduardo Navajas, Marinko V. Sarunic, Mirza Faisal Beg
2019	A*	`conf`	On the Effectiveness of Low Frequency Perturbations. IJCAI Yash Sharma, Gavin Weiguang Ding, Marcus A. Brubaker
2019	J	`jnl`	On the Effectiveness of Low Frequency Perturbations. CoRR Yash Sharma, Gavin Weiguang Ding, Marcus A. Brubaker
2019	—	`conf`	On the Sensitivity of Adversarial Robustness to Input Data Distributions. CVPR Workshops Gavin Weiguang Ding, Kry Yik Chau Lui, Xiaomeng Jin, Luyu Wang, Ruitong Huang
2019	—	`conf`	On the Sensitivity of Adversarial Robustness to Input Data Distributions. ICLR (Poster) Gavin Weiguang Ding, Kry Yik Chau Lui, Xiaomeng Jin, Luyu Wang, Ruitong Huang
2019	J	`jnl`	On the Sensitivity of Adversarial Robustness to Input Data Distributions. CoRR Gavin Weiguang Ding, Kry Yik Chau Lui, Xiaomeng Jin, Luyu Wang, Ruitong Huang
2019	J	`jnl`	advertorch v0.1: An Adversarial Robustness Toolbox based on PyTorch. CoRR Gavin Weiguang Ding, Luyu Wang, Xiaomeng Jin
2018	A*	`conf`	Dimensionality Reduction has Quantifiable Imperfections: Two Geometric Bounds. NeurIPS Kry Yik Chau Lui, Gavin Weiguang Ding, Ruitong Huang, Robert J. McCann
2018	J	`jnl`	Dimensionality Reduction has Quantifiable Imperfections: Two Geometric Bounds. CoRR Kry Yik Chau Lui, Gavin Weiguang Ding, Ruitong Huang, Robert J. McCann
2018	—	`conf`	Improving GAN Training via Binarized Representation Entropy (BRE) Regularization. ICLR (Poster) Yanshuai Cao, Gavin Weiguang Ding, Kry Yik-Chau Lui, Ruitong Huang
2018	J	`jnl`	Improving GAN Training via Binarized Representation Entropy (BRE) Regularization. CoRR Yanshuai Cao, Gavin Weiguang Ding, Kry Yik-Chau Lui, Ruitong Huang
2018	J	`jnl`	Max-Margin Adversarial (MMA) Training: Direct Input Space Margin Maximization through Adversarial Training. CoRR Gavin Weiguang Ding, Yash Sharma, Kry Yik Chau Lui, Ruitong Huang
2018	J	`jnl`	Multiscale deep neural network based analysis of FDG-PET images for the early diagnosis of Alzheimer's disease. Medical Image Anal. Donghuan Lu, Karteek Popuri, Gavin Weiguang Ding, Rakesh Balachandar, Mirza Faisal Beg
2017	J	`jnl`	Multimodal and Multiscale Deep Neural Networks for the Early Diagnosis of Alzheimer's Disease using structural MR and FDG-PET images. CoRR Donghuan Lu, Karteek Popuri, Gavin Weiguang Ding, Rakesh Balachandar, Mirza Faisal Beg
2017	—	`conf`	Multiple instance learning for age-related macular degeneration diagnosis in optical coherence tomography images. ISBI Donghuan Lu, Gavin Weiguang Ding, Andrew B. Merkur, Marinko V. Sarunic, Mirza Faisal Beg
2017	J	`jnl`	Retinal Fluid Segmentation and Detection in Optical Coherence Tomography Images using Fully Convolutional Neural Network. CoRR Donghuan Lu, Morgan Heisler, Sieun Lee, Gavin Weiguang Ding, Marinko V. Sarunic, Mirza Faisal Beg
2014	J	`jnl`	Automatic Cycle Averaging for Denoising Approximately Periodic Spatiotemporal Signals. IEEE Trans. Medical Imaging Gavin Weiguang Ding, Eric Lin, Amanda Ribeiro, Marinko V. Sarunic, Glen F. Tibbits, Mirza Faisal Beg
2013	—	`conf`	Automatic detection of subretinal fluid and sub-retinal pigment epithelium fluid in optical coherence tomography images. EMBC Gavin Weiguang Ding, Mei Young, Serge Bourgault, Sieun Lee, David A. Albiani, Andrew W. Kirker, Farzin Forooghian, Marinko V. Sarunic, Andrew B. Merkur, Mirza Faisal Beg
2013	—	`conf`	On identification of sinoatrial node in zebrafish heart based on functional time series from optical mapping. EMBC Gavin Weiguang Ding, Eric Lin, Amanda Ribeiro, Marinko V. Sarunic, Glen F. Tibbits, Mirza Faisal Beg

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.