Wanglong Lu currently serves as a Senior Data Scientist in AI/Analytics at Nasdaq, Canada, and is based in St. John’s, NL, Canada. His research output totals 30 scholarly works (author-reported), including 6 published first-author papers, co-first-authored DocPure, and corresponding-authored EchoSR. The linked catalogue below includes preprints and a dissertation and is not the complete accepted-paper count.

Education

• 2021-2025 Ph.D. Computer Science, Memorial University of Newfoundland.
• 2018-2021 M.Eng. (Master of Engineering), Computer Software and Theory, Wenzhou University.
• 2014-2018 B.Eng. (Bachelor of Engineering), Digital Media Technology, Communication University of Zhejiang.

Interests

• Computer Vision, Pattern Recognition, Generative Models, Parameter-Efficient Fine-Tuning, Multimodal AI Systems, and Financial AI.

Publications

• DocPure: Prompt-Free Unified Document Restoration via Degradation-Aware Structure-Guided Wavelet Modulation
  Lingming Su, Wanglong Lu, Tao Wang, Kaihao Zhang, Nan Zhang, Liyan An, Hanli Zhao
  IEEE Transactions on Circuits and Systems for Video Technology, 2026 · Co-first author
  [paper] [pdf] [arXiv] [html] [doi] [code]
• Tuning-Free Latent Diffusion Models for Ultrahigh-Resolution Image Editing
  Wanglong Lu, Lingming Su, Kaijie Shi, Minglun Gong, Xiaogang Jin, Hanli Zhao, Xianta Jiang
  IEEE Transactions on Neural Networks and Learning Systems, 1-15, 2026 · First author
  [paper] [pdf] [html] [doi] [code]
• UHDRes: Ultra-High-Definition Image Restoration via Dual-Domain Decoupled Spectral Modulation
  Shihao Zhao, Wanglong Lu, Binhao Wang, Tao Wang, Kaihao Zhang, Hanli Zhao
  IEEE Transactions on Circuits and Systems for Video Technology, 2026
  [paper] [pdf] [html] [code]
• Simulation-Driven Imitation Learning for Biosignals-Free Shared-Autonomy Prosthetic Grasping
  Kaijie Shi, Wanglong Lu, Han Chen, Vinicius Prado da Fonseca, Ting Zou, Hanli Zhao, Xianta Jiang
  arXiv preprint arXiv:2606.07389, 2026
  [paper]
• EchoSR: Efficient Context Harnessing for Lightweight Image Super-Resolution
  Hanli Zhao, Binhao Wang, Shihao Zhao, Tao Wang, Kaihao Zhang, Wanglong Lu∗
  Information Fusion 135, 104471, 2026 · Corresponding author (sixth author)
  [paper] [pdf] [arXiv] [html] [doi] [code]
• AdaMSS: Adaptive Multi-Subspace Approach for Parameter-Efficient Fine-Tuning
  Jingjing Zheng, Wanglong Lu, Yiming Dong, Chaojie Ji, Yankai Cao, Zhouchen Lin
  NeurIPS 2025 · Second author
  [paper] [pdf] [doi] [code] [project]
• GRIG: Data-Efficient Generative Residual Image Inpainting
  Wanglong Lu, Xianta Jiang, Xiaogang Jin, Yong-Liang Yang, Minglun Gong, Kaijie Shi, Tao Wang, Hanli Zhao
  Computational Visual Media 11(6), 1329-1361, 2025 · First author
  [paper] [pdf] [arXiv] [doi] [project]
• StDDPM: Sequential Financial Synthetic Data Generation using T-distribution based Diffusion Model
  Omid Tarkhaneh, Hamideh Mehri, Wanglong Lu, Farzaneh Shoeleh, Vinicius Veloso de Melo
  Research Square preprint, 2025 · Submitted
  [paper] [pdf] [doi] [code]
• Toward Biosignals-Free Autonomous Prosthetic Hand Control via Imitation Learning
  Kaijie Shi, Wanglong Lu, Hanli Zhao, Vinicius Prado da Fonseca, Ting Zou, Xianta Jiang
  IEEE Transactions on Neural Systems and Rehabilitation Engineering 33, 3544-3554, 2025
  [paper] [pdf] [arXiv] [doi] [project]
• Real-time dual-eye collaborative eyeblink detection with contrastive learning
  Hanli Zhao, Yu Wang , Wanglong Lu, Zili Yi, Jun Liu∗, Minglun Gong
  Pattern Recognition, 2025
  [paper]
• Visual style prompt learning using diffusion models for blind face restoration
  Wanglong Lu, Jikai Wang, Tao Wang, Kaihao Zhang, Xianta Jiang, Hanli Zhao*
  Pattern Recognition 161, 111312, 2025 · First author
  [paper] [doi] [code]
• Degradation-Aware Frequency-Separated Transformer for Blind Super-Resolution
  Hanli Zhao, Binhao Wang, Wanglong Lu*, Juncong Lin
  International Conference on Computational Visual Media, 2025
  [paper]
• TextDoctor: Unified Document Image Inpainting via Patch Pyramid Diffusion Models
  Wanglong Lu, Lingming Su, Jingjing Zheng, Vinícius Veloso de Melo, Farzaneh Shoeleh, John Hawkin, Terrence Tricco, Hanli Zhao, Xianta Jiang
  arXiv preprint, 2025 · First author · Submitted to Engineering Applications of Artificial Intelligence (EAAI)
  [paper]
• Do Inpainting Yourself: Generative Facial Inpainting Guided by Exemplars
  Wanglong Lu, Hanli Zhao, Xianta Jiang, Xiaogang Jin, Yongliang Yang, Min Wang, Jiankai Lyu, and Kaijie Shi
  Neurocomputing 617, 128996, 2025 · First author
  [paper] [doi] [code]
• Generative Models for Semantic Facial Image Editing: Multimodal Approaches
  Wanglong Lu
  PhD thesis, Memorial University of Newfoundland, 2025
  [paper]
• FACEMUG: A Multimodal Generative and Fusion Framework for Local Facial Editing
  Wanglong Lu, Jikai Wang, Xiaogang Jin, Xianta Jiang, and Hanli Zhao∗
  IEEE Transactions on Visualization and Computer Graphics 31(9), 5130-5145, 2025 (online 2024) · First author
  [paper] [pdf] [arXiv] [doi]
• Handling the Non-smooth Challenge in Tensor SVD: A Multi-objective Tensor Recovery Framework
  Jingjing Zheng, Wanglong Lu, Wenzhe Wang, Yankai Cao*, Xiaoqin Zhang, and Xianta Jiang
  ECCV, 2024
  [paper]
• Promptrr: Diffusion models as prompt generators for single image reflection removal
  Tao Wang, Wanglong Lu, Kaihao Zhang, Wenhan Luo, Tae-Kyun Kim, Tong Lu, Hongdong Li, Ming-Hsuan Yang
  ArXiv, 2024
  [paper]
• TEG: image theme recognition using text-embedding-guided few-shot adaptation
  Jikai Wang, Wanglong Lu, Yu Wang, Kaijie Shi, Xianta Jiang, Hanli Zhao
  Journal of Electronic Imaging 33(1), 013028, 2024
  [paper] [doi]
• Restoring Vision in Hazy Weather with Hierarchical Contrastive Learning
  Tao Wang, Guangpin Tao, Wanglong Lu, Kaihao Zhang, Wenhan Luo, Xiaoqin Zhang, Tong Lu.
  Pattern Recognition Volume 145, January 2024, 109956
  [paper] [doi] [cite]
• Detecting Blinks from Wearable Cameras using Spatial-Temporal-Aware Deep Network Learning
  Yu Wang, Wanglong Lu, Hanli Zhao, Xianta Jiang∗, Bin Zheng, M. Stella Atkins.
  ETRA 23, 2023
  [paper] [doi] [cite]
• 基于多尺度特征先验的图像拼接篡改检测
  吕建凯, 卢望龙, 王敏, 刘影, 史开杭, 黄辉, 赵汉理
  China Sciencepaper 17(11), 2022 · Second author
• Generative image inpainting with enhanced gated convolution and Transformers
  Min Wang, Wanglong Lu, Jiankai Lyu, Kaijie Shi, Hanli Zhao.
  Displays 76, 102321, 2022
  [paper] [doi] [cite]
• Efficient Generative Face Completion with Perceptual Deblurring
  Hanli Zhao, Ying Liu, Wanglong Lu, Xiaogang Jin, Hui Huang, Kaijie Shi
  Journal of Computer-Aided Design & Computer Graphics 34(9), 1420-1431, 2022
• Probability-Based Channel Pruning for Depthwise Separable Convolutional Networks
  Han-Li Zhao, Kai-Jie Shi, Xiaogang Jin, Ming-Liang Xu, Hui Huang, Wang-Long Lu, Ying Liu.
  Journal of Computer Science and Technology 37, 584-600, 2022
  [paper] [doi]
• Category-consistent deep network learning for accurate vehicle logo recognition
  Wanglong Lu, Hanli Zhao, Qi He, Hui Huang, Xiaogang Jin.
  Neurocomputing 463, 623-636, 2021 · First author
  [paper] [doi] [cite] [code]
• High‐quality retinal vessel segmentation using generative adversarial network with a large receptive field
  Hanli Zhao, Xiaqing Qiu, Wanglong Lu, Hui Huang, Xiaogang Jin.
  International Journal of Imaging Systems and Technology 30(3), 828-842, 2020
  [paper] [doi]

Patents

Co-inventor on 5 granted Chinese invention patents. All grant certificates list Wenzhou University as the assignee. Titles below are English translations.

• Probability-based channel pruning for MobileNetV1. ZL202110903135.9; granted 2023-07-25; inventor position 4/5.
• Category-consistent deep learning for image recognition. ZL202110408724.X; granted 2023-06-30; inventor position 2/4.
• CNN-based intelligent vehicle-logo detection. ZL202010139068.3; granted 2021-09-03; inventor position 2/2.
• GAN-based intelligent retinal-vessel image segmentation. ZL201910884346.5; granted 2021-07-06; inventor position 2/4.
• CNN deep-feature-based vehicle-logo recognition. ZL202010139043.3; granted 2021-05-11; inventor position 2/3.

Selected honors

• 2024-04 Student Member Computer Innovation and Entrepreneurship Award of Wenzhou Computer Federation (First Prize, Team Leader)
• 2023-04 Outstanding Research Award (Ph.D.) of The Department of Computer Science at Memorial University
• 2022-05 Mitacs Accelerate Award
• 2020-12 Outstanding Graduates of Wenzhou University
• 2019-12 National Post-Graduate Mathematical Contest in Modeling (Third Prize)
• 2019-07 College Students Programming Competition (CCPC)- Jiangxi College Students programming Competition Award, Jiangxi (Third Prize, Team Leader)
• 2018-06 Outstanding Graduates of Zhejiang Province
• 2017-12 Zhejiang Provincial Government Scholarship, Zhejiang
• 2017-07 The 10th Chinese College Students Computer Design Competition service outsourcing “Parking Treasure Development” (second prize)
• 2016-12 Zhejiang Provincial Government Scholarship, Zhejiang
• 2015-12 Excellent Student Cadre of Communication University of Zhejiang

Work experience

Nasdaq

St. John’s, NL, Canada

Senior Data Scientist, AI/Analytics | 2025.03-Present

• Designed cross-scale ensemble feature selection, removing 77.2% of input features while retaining competitive performance on cheque-fraud ML (CFML) data; presented the work to 60+ attendees.
• Delivered internal deployment and integration of MLP, a cross-team ML training platform, by bringing its existing UI/backend prototype into a SageMaker workspace, configuring network connectivity and IAM roles.
• Implemented PostgreSQL-backed user-state persistence and deployed FastAPI services to AWS Lambda using Mangum.
• MLP is at the internal deployment stage. Its cross-team scope includes data ingestion, preprocessing, distributed training, feature selection, evaluation, and an auditable model registry; my contribution is application deployment, integration, and job-submission tooling, not sole ownership of the platform.
• Built SageMaker Job Submitter as part of MLP, packaging scripts and dependencies for SageMaker Processing, Training, Hyperparameter Tuning, and Pipelines. Reduced the new-task configuration and submission-preparation cycle from 7 days to 1 day (about 86%), not model-training runtime.
• Designed a feature-engineering workflow that selects informative features using feature-label AUROC, with PyTorch/CUDA-accelerated computation. Used Amazon Bedrock to assess whether candidate features make semantic sense alongside their statistical signal.
• Developed PagerDuty RAG incident-response assistant v2 on the company’s GenAI platform, following the internal hackathon prototype. Now used internally and recognized in a company shout-out; retrieves incident context, troubleshooting guidance and resolution steps for on-call engineers.
• Mentored cheque OCR quality assessment and text extraction research. Identified a promising set of image-quality metrics consistent with human perception; the student completed a research presentation.
• Guided sequential tabular-data generation research leading to StDDPM, a submitted manuscript with a Research Square preprint. The Student-t diffusion/LSTM method was evaluated on 1.06 million Czech banking transaction records across 4,500 accounts [Paper] [Code].
• Mentored Seeam, a work-term student, on an input payload checker from June 2026, and Daniel, a Mitacs student, on graph neural networks (GNNs) for crime-ring detection from September 2026.

AI Algorithm Intern (two placements) | 2024.05-2025.01

• Proposed TextDoctor, combining structure-pyramid prediction and patch-pyramid diffusion for document/cheque inpainting. Implemented the method in Python/PyTorch and ran comparative experiments with AWS, SLURM, CUDA, and shell scripts. First-author manuscript submitted to Engineering Applications of Artificial Intelligence (EAAI) [Paper].
• Evaluated 7 document datasets without dataset-specific fine-tuning and demonstrated 8K inpainting on a 24GB RTX 3090. On FUNSD, TextDoctor (GSDM) achieved 55.38% PaddleOCR word accuracy vs. 45.24% for DocDiff (+10.14 percentage points) [Results, Tables I-II].
• Presented research after both internship placements: approximately 40-60 attendees at the earlier talk and 39 cross-functional attendees at the final talk.

Beaufort Solutions

St. John’s, NL, Canada

AI Intern | 2022.07-2022.11

• Led method design of TEG, a CLIP-based few-shot adaptation approach for personalized photo-book curation. Introduced a text-embedding-guided classifier and auxiliary classification loss to improve learning from limited labels.
• Designed the data-collection pipeline and led construction of Theme25: 35,655 annotated images across 25 themes [Dataset].
• Evaluated on Theme25, CIFAR100, and ImageNet using Python/PyTorch and AWS/SLURM; research published in Journal of Electronic Imaging 33(1), 013028 (2024) [Paper] [Code].

Zhongkong Hanlian

Hangzhou, China

AI Algorithm Intern | 2017.12-2018.08

• Designed ResNet-DenseNet fusion for vehicle-logo recognition with Python and C++.
• Developed Java annotation tools and constructed a vehicle-logo dataset for training and evaluation.
• Deployed trained models using Caffe for real-time inference at community security gates.

Selected Engineering Projects

• Local Agentic Code Editor: Nasdaq Internal Exploratory Prototype (2026)
  • Built a working local AI code-editor prototype connecting language-model APIs to an agentic loop that selects code generation, code review or shell-tool execution based on the task.
  • Supports bug diagnosis, code edits and automatic fixes, using execution feedback to iterate and determine the next action. This remains an exploratory internal prototype, not an approved production product.
• AI Headshot Generation Deployment
  • Implemented model invocation and application deployment for AI-generated headshots.

Teaching and mentorship

• Provided research mentorship to 12 master’s and Ph.D. students across generative vision, restoration, recognition and applied ML. Supported problem formulation, method design, experimental evaluation and paper writing; related work led to peer-reviewed publications.

• 2021.09-2021.12 Teaching assistant of Data Structures and Algorithms, Memorial University

• 2024.01-2024.04 Teaching assistant of Introduction to Machine Learning, Memorial University

Academic service

Invited reviewer for IEEE TPAMI, TIP, TMM, TCSVT, SPL, IEEE Journal of Biomedical and Health Informatics (JBHI), Pattern Recognition, Engineering Applications of Artificial Intelligence (EAAI), Knowledge-Based Systems, Neurocomputing, Applied Soft Computing, Scientific Reports, The Visual Computer, and ECCV 2026.