Client Dependent GMM-SVM Models for Speaker Verification. - Quan Le; Samy Bengio (ICANN, 2003)

Burst-mode transmitter for 1.25Gb/s Ethernet PON applications [passive optical networks]. - Yong-Hun Oh; Quan Le; Sang-Gug Lee 001; Nguyen Duy Bien Yen; Ho-Yong Kang; Tae-Whan Yoo (ESSCIRC, 2004)

A burst-mode receiver for 1.25-Gb/s ethernet PON with AGC and internally created reset signal. - Quan Le; Sang-Gug Lee 001; Yong-Hun Oh; Ho-Yong Kang; Tae-Whan Yoo (IEEE J. Solid State Circuits, 2004)

A CMOS burst-mode optical transmitter for 1.25-Gb/s ethernet PON applications. - Yong-Hun Oh; Sang-Gug Lee 001; Quan Le; Ho-Yong Kang; Tae-Whan Yoo (IEEE Trans. Circuits Syst. II Express Briefs, 2005)

A 95-dB linear low-power variable gain amplifier. - Quoc-Hoang Duong; Quan Le; Chang-Wan Kim; Sang-Gug Lee 001 (IEEE Trans. Circuits Syst. I Regul. Pap., 2006)

A CMOS Burst-Mode TIA with Step AGC and Selective Internally Created Reset for 1.25Gb/s EPON. - Quan Le; Sang-Gug Lee 001; Ho-Yong Kang; Sang-Hoon Chang (ISSCC, 2007)

Burst-mode optical transmitter with DC-coupled burst-enable signal for 2.5-Gb/s GPON system. - Sang Hyun Park; Mikko Karppinen; Quan Le; Bin Young Yoon (Microelectron. J., 2008)

Energy-Efficient Low-Complexity CMOS Pulse Generator for Multiband UWB Impulse Radio. - Anh-Tuan Phan; Jeong-Seon Lee; Vladimir Krizhanovskii; Quan Le; Seok-Kyun Han; Sang-Gug Lee 001 (IEEE Trans. Circuits Syst. I Regul. Pap., 2008)

An Optical Transimpedance Amplifier Using an Inductive Buffer Stage Technique. - Sang Hyun Park; Quan Le; Bo-Hun Choi (IEICE Trans. Commun., 2009)

Protein multiple sequence alignment benchmarking through secondary structure prediction. - Quan Le; Fabian Sievers; Desmond G. Higgins (Bioinform., 2017)

Deep learning at the shallow end: Malware classification for non-domain experts. - Quan Le; Oisín Boydell; Brian Mac Namee; Mark Scanlon (Digit. Investig., 2018)

Using Text Classification Methods to Detect Malware. - Eoghan Cunningham; Oisín Boydell; Cormac Doherty; Benjamin Roques; Quan Le (AICS, 2019)

Automated Artefact Relevancy Determination from Artefact Metadata and Associated Timeline Events. - Xiaoyu Du 003; Quan Le; Mark Scanlon (Cyber Security, 2020)

Identifying Internet of Things software activities using deep learning-based electromagnetic side-channel analysis. - Quan Le; Luis Miralles-Pechuán; Asanka P. Sayakkara; Nhien-An Le-Khac; Mark Scanlon (Digit. Investig., 2021)

Enhancing the insertion of NOP instructions to obfuscate malware via deep reinforcement learning. - Daniel Gibert; Matt Fredrikson; Carles Mateu; Jordi Planes; Quan Le (Comput. Secur., 2022)

Fusing feature engineering and deep learning: A case study for malware classification. - Daniel Gibert; Jordi Planes; Carles Mateu; Quan Le (Expert Syst. Appl., 2022)

Certified Robustness of Static Deep Learning-based Malware Detectors against Patch and Append Attacks. - Daniel Gibert; Giulio Zizzo; Quan Le (AISec@CCS, 2023)

Towards a Practical Defense Against Adversarial Attacks on Deep Learning-Based Malware Detectors via Randomized Smoothing. - Daniel Gibert; Giulio Zizzo; Quan Le (ESORICS Workshops (2), 2023)

A Wolf in Sheep's Clothing: Query-Free Evasion Attacks Against Machine Learning-Based Malware Detectors with Generative Adversarial Networks. - Daniel Gibert; Jordi Planes; Quan Le; Giulio Zizzo (EuroS&P Workshops, 2023)

Towards a Framework for the Global Assessment of Sensitive Attribute Bias Within Binary Classification Algorithms. - Adrian Byrne; Ivan Caffrey; Quan Le (EWAF, 2023)

American Stories: A Large-Scale Structured Text Dataset of Historical U.S. Newspapers. - Melissa Dell; Jacob Carlson; Tom Bryan; Emily Silcock; Abhishek Arora 003; Zejiang Shen 001; Luca D'Amico-Wong; Quan Le; Pablo Querubin; Leander Heldring (NeurIPS, 2023)

Query-Free Evasion Attacks Against Machine Learning-Based Malware Detectors with Generative Adversarial Networks. - Daniel Gibert; Jordi Planes; Quan Le; Giulio Zizzo (CoRR, 2023)

Using GitHub Analytics to Assess the Quality of Collaboration in Software Engineering Teams. - Quan Le; Kiet Phan; Bowen Hui; Adara Putri (FIE, 2024)

Insights from the Participatory Design of a Virtual Reality Spatial Navigation Application for Veterans with a History of TBI. - Lila Bozgeyikli; Evren Bozgeyikli; Ryu Funakoshiya; Quan Le; Kyle Walker; L. Matthew Law; Daniel R. Griffiths; Arne D. Ekstrom; Jonathan Lifshitz (VR Workshops, 2024)

Adversarial Robustness of Deep Learning-Based Malware Detectors via (De)Randomized Smoothing. - Daniel Gibert; Giulio Zizzo; Quan Le; Jordi Planes (IEEE Access, 2024)

A Robust Defense against Adversarial Attacks on Deep Learning-based Malware Detectors via (De)Randomized Smoothing. - Daniel Gibert; Giulio Zizzo; Quan Le; Jordi Planes (CoRR, 2024)

Certified Adversarial Robustness of Machine Learning-based Malware Detectors via (De)Randomized Smoothing. - Daniel Gibert; Luca Demetrio; Giulio Zizzo; Quan Le; Jordi Planes; Battista Biggio (CoRR, 2024)

Assessing the Impact of Packing on Machine Learning-Based Malware Detection and Classification Systems. - Daniel Gibert; Nikolaos Totosis; Constantinos Patsakis; Giulio Zizzo; Quan Le (CoRR, 2024)

Assessing the impact of packing on static machine learning-based malware detection and classification systems. - Daniel Gibert; Nikolaos Totosis; Constantinos Patsakis; Quan Le; Giulio Zizzo (Comput. Secur., 2025)

Thyroid nodule segmentation in ultrasound images using transformer models with masked autoencoder pre-training. - Yi Xiang; U. Rajendra Acharya; Quan Le; Jen Hong Tan; Chiaw-Ling Chng (Frontiers Artif. Intell., 2025)

A Framework to Assess the Persuasion Risks Large Language Model Chatbots Pose to Democratic Societies. - Zhongren Chen; Joshua Kalla; Quan Le; Shinpei Nakamura-Sakai; Jasjeet S. Sekhon; Ruixiao Wang 001 (CoRR, 2025)