Wanglong Lu

// applied generative vision and multimodal AI

Generative vision researcher turned applied ML engineer.

I work on production AI systems for financial applications at Nasdaq, while continuing research collaborations in generative vision, image restoration, image editing, and parameter-efficient adaptation.

My current direction is toward scalable multimodal and generative AI systems that connect robust model design with deployable machine learning products.

Generative Models Computer Vision Image Restoration Image Editing Parameter-Efficient Fine-Tuning Financial AI Systems

// experience

Nasdaq

Senior Data Scientist, AI/Analytics · 2025 - Present

Building and applying machine learning systems for financial AI products in production settings.

Nasdaq Verafin

AI Research Intern · 2024 - 2025

Worked on image verification and delivered research progress presentations to cross-functional audiences.

Research Collaboration

Memorial University of Newfoundland · Wenzhou University

Collaborating with and mentoring Ph.D. and Master's students with Prof. Xianta Jiang and Prof. Hanli Zhao.

// education

Memorial University of Newfoundland

Ph.D. in Computer Science · 2025

Wenzhou University

M.Sc. in Computer Software and Theory · 2021

Communication University of Zhejiang

B.Sc. in Digital Media Technology · 2018

// research overview

My research started from image recognition and restoration, then moved toward generative image editing, document restoration, face restoration, and multimodal generative systems. Recent work includes ultra-high-resolution image editing, dual-domain restoration, lightweight super-resolution, and adaptive parameter-efficient fine-tuning. In parallel, my industry work emphasizes robust ML systems that can survive real production constraints.

Document image restoration research teaser

// selected publications

view all publications →

ArXiv

TextDoctor: Unified Document Image Inpainting via Patch Pyramid Diffusion Models

Wanglong Lu, Lingming Su, Jingjing Zheng, Vinicius Veloso de Melo, Farzaneh Shoeleh, John Hawkin, Terrence Tricco, Hanli Zhao, Xianta Jiang

ArXiv, 2025

A diffusion-based document image inpainting framework for restoring damaged or corrupted document regions.

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, 2025

A diffusion-guided restoration method that learns visual style prompts for blind face restoration.

Paper Code

TVCG

FACEMUG: A Multimodal Generative and Fusion Framework for Local Facial Editing

Wanglong Lu, Jikai Wang, Xiaogang Jin, Xianta Jiang, Hanli Zhao

IEEE Transactions on Visualization and Computer Graphics, 2024

A multimodal framework for local facial editing through generative modeling and feature fusion.

Paper

Degradation-aware blind super-resolution teaser

CVM

Degradation-Aware Frequency-Separated Transformer for Blind Super-Resolution

Hanli Zhao, Binhao Wang, Wanglong Lu, Juncong Lin

Computational Visual Media Conference, 2025

A blind super-resolution model that separates frequency information while adapting to image degradation.

Paper

// current news

Now I am currently working at Nasdaq as a Senior Data Scientist.
Jul. 2026 Our paper "Tuning-Free Latent Diffusion Models for Ultrahigh-Resolution Image Editing" has been published in IEEE Transactions on Neural Networks and Learning Systems, 1-15.
Jul. 2026 Our paper "UHDRes: Ultra-High-Definition Image Restoration via Dual-Domain Decoupled Spectral Modulation" has been published in IEEE Transactions on Circuits and Systems for Video Technology. Congratulations to Shihao. Source code is available on GitHub.
Jun. 2026 Our paper "Simulation-Driven Imitation Learning for Biosignals-Free Shared-Autonomy Prosthetic Grasping" was released as an arXiv preprint, arXiv:2606.07389. Congratulations to Kaijie.
May 2026 Our paper "EchoSR: Efficient Context Harnessing for Lightweight Image Super-Resolution" has been published in Information Fusion, 104471. Cheers to Binhao.
Apr. 2026 AdaMSS has been integrated into the Hugging Face PEFT package. GitHub

More News (2025)

On Dec. 4, 2025, our paper "AdaMSS: Adaptive Multi-Subspace Approach for Parameter-Efficient Fine-Tuning" has been presented at NeurIPS 2025. GitHub
On Jun. 12, 2025, our paper "Towards Biosignals-Free Autonomous Prosthetic Hand Control via Imitation Learning" was released. Congratulations to Kaijie. This project was also interviewed by the CBC. Check the main page for more information.
On April 26, 2025, our paper "Degradation-Aware Frequency-Separated Transformer for Blind Super-Resolution" was successfully published at the Computational Visual Media Conference. Congratulations to Binhao Wang.
On March 6, 2025, our paper "TextDoctor: Unified Document Image Inpainting via Patch Pyramid Diffusion Models" was released.
On Feb. 15, 2025, our paper "Real-time dual-eye collaborative eyeblink detection with contrastive learning" has been successfully published in Pattern Recognition. Congratulations to Yu Wang.
On Feb. 05, 2025, I served as a guest lecturer for Bio-Inspired Robotics (ENGI 9986), delivering a 150-minute course on "Deep Generative Models and Applications" to 10 graduate students. I am grateful to Dr. Ting Zou for the invitation.
On Jan. 31, 2025, I completed my internship at Nasdaq Verafin and delivered a presentation on our recent progress in image verification to an audience of 39 attendees.

More News (2024)

On Dec. 29, 2024, our paper Visual Style Prompt Learning Using Diffusion Models for Blind Face Restoration was published at Pattern Recognition. Page
On November 28, 2024, our paper has been published in Neurocomputing after a three-year review process. It was the starting point of my research and was finally accepted on the morning of my thesis defense.
On November 21, 2024, I successfully defended my Ph.D. thesis. I am deeply grateful to my supervisors, Dr. Xianta Jiang, Dr. Hanli Zhao, and Dr. Yuanzhu Chen, and to my committee members, collaborators, and peers at Memorial University of Newfoundland, Wenzhou University, and Nasdaq.
On Nov. 14, 2024, I gave an oral presentation at the 33rd NECEC conference for our recent document image restoration algorithm, with an audience of 30 attendees.
On Sep. 23, 2024, I gave a talk to share my experience in university and postgraduate study life at Digital Media Technology, Communication University of Zhejiang, with an audience of 120 attendees.
On August 30, 2024, I gave a talk on our recent work in text document restoration at Nasdaq Verafin, with an audience of 45 attendees.
On July 11, 2024, our paper titled "Handling The Non-Smooth Challenge in Tensor SVD: A Multi-Objective Tensor Recovery Framework" was accepted at ECCV.

// academic service

Invited Reviewer

2026

Invited Reviewer