Gang Wu

Research Scientist 2

San Jose

Gang Wu joined Adobe Research as Research Scientist in December, 2017. His research spans different machine learning fields including statistical modeling, optimization, deep learning, and generative modeling, with data science applications such as digital marketing, user behavior modeling, recommender systems, and computer vision applications such as image compression, video understanding, etc.

Prior to joining Adobe, he worked on probabilistic methods for matrix completion during my PhD in Electrical & Computer Engineering Department at Iowa State University, advised by Prof. Ratnesh Kumar. He also interned at Adobe Research conducting comprehensive research on recommender systems and user engagement maximization (see “Meet the Intern Who Knows What Videos You Want to Watch”).

More information about him is available on his personal site.

Publications

Click, Type, Repeat: A Comprehensive Survey on GUI Agents

Nguyen, Dang., Chen, Jian., Wang, Yu., Wu, Gang., Park, Namyong., Hu, Zhengmian., Lyu, Hanjia., Wu, Junda., Aponte, Ryan., Xia, Yu., Li, Xintong., Shi, Jing., Chen, Hongjie., Lai, Viet., Xie, Zhouhang., Kim, Sungchul., Zhang, Ruiyi., Yu, Tong., Tanjim, Mehrab., Ahmed, Nesreen., Mathur, Puneet., Yoon, David., Yao, Lina., Kveton, Branislav., Kil, Jihyung., Nguyen, Thien., Bui, Trung., Zhou, Tianyi., Rossi, Ryan., Dernoncourt, Franck. (Aug. 1, 2025)

ACL 2025 Findings

Token-level adversarial prompt detection based on perplexity measures and contextual information

Hu, Zhengmian., Wu, Gang., Mitra, Saayan., Zhang, Ruiyi., Sun, Tong., Huang, Heng., Swaminathan, Vishy. (Mar. 5, 2025)

ICLR Workshop on Building Trust in Language Models and Applications

GUI-Bee: Align GUI Action Grounding to Novel Environments via Autonomous Exploration

Fan, Yue., Zhao, Handong., Zhang, Ruiyi., Shen, Yu., Wang, Xin., Wu, Gang. (Jan. 23, 2025)

arXiv

Copiloting Creative 3D Scene Modeling and Visualization with Generative Agents

Petrangeli, Stefano., Shen, Yu., Wu, Gang., Gadelha, Matheus., Nguyen, Cuong., Petrangeli, Petrangeli. (Dec. 14, 2024)

Neural Information Processing Systems (NeurIPS)

AutoDAN: interpretable gradient-based adversarial attacks on large language models

Zhu, Sicheng., Zhang, Ruiyi., An, Bang., Wu, Gang., Barrow, Joe., Wang, Zichao., Huang, Furong., Nenkova, Ani., Sun, Tong. (Aug. 1, 2024)

COLM 2024

Content-aware Progressive Image Compression and Syncing

Wu, Junda., Wang, Haoliang., Yu, Tong., Zhao, Handong., Wu, Gang., Petrangeli, Stefano., Kim, Sungchul., Swaminathan, Vishy. (Dec. 11, 2023)

IEEE International Symposium on Multimedia (ISM)

Active Context Modeling for Efficient Image and Burst Compression

Li, Yang., Wu, Gang., Petrangeli, Stefano., Wang, Haoliang., Rossi, Ryan., Swaminathan, Vishy. (Dec. 11, 2023)

ISM 2023

GPU-accelerated Lossless Image Compression with Massive Parallelization

Shen, Yu., Wu, Gang., Swaminathan, Vishy., Wang, Haoliang., Petrangeli, Stefano., Yu, Tong. (Dec. 11, 2023)

ISM 2023

VaQuitA: Enhancing alignment in llm-assisted video understanding

Wang, Yizhou., Zhang, Ruiyi., Wang, Haoliang., Bhattacharya, Uttaran., Fu, Yun., Wu, Gang. (Dec. 4, 2023)

arXiv

Task-Oriented Near-Lossless Burst Compression

Jiang, Weixin., Wu, Gang., Swaminathan, Vishy., Petrangeli, Stefano., Wang, Haoliang., Rossi, Ryan., Lipka, Nedim. (Dec. 5, 2022)

IEEE International Symposium on Multimedia (ISM)

Show Me What I Like: Detecting User-Specific Video Highlights Using Content-Based Multi-Head Attention

Bhattacharya, Uttaran., Wu, Gang., Petrangeli, Stefano., Swaminathan, Vishy., Manocha, Dinesh. (Oct. 10, 2022)

ACM International Conference on Multimedia (ACMMM), 2022

One-pass algorithms for map inference of nonsymmetric determinantal point processes

Reddy, Aravind., Rossi, Ryan., Song, Zhao., Rao, Anup., Mai, Tung., Lipka, Nedim., Wu, Gang., Koh, Eunyee., Ahmed, Nesreen. (Mar. 28, 2022)

International Conference on Machine Learning (ICML)

Efficient Decentralized Stochastic Gradient Descent Method for Nonconvex Finite-Sum Optimization Problems

Zhan, Wenkang., Wu, Gang., Gao, Hongchang. (Jan. 29, 2022)

AAAI Conference on Artificial Intelligence (AAAI)

From closing triangles to higher-order motif closures for better unsupervised online link prediction

Rossi, Ryan., Rao, Anup., Kim, Sungchul., Koh, Eunyee., Ahmed, Nesreen., Wu, Gang. (Oct. 26, 2021)

ACM International Conference on Information & Knowledge Management (CIKM)

HighlightMe: Detecting Highlights From Human-Centric Videos

Bhattacharya, Uttaran., Wu, Gang., Petrangeli, Stefano., Swaminathan, Vishy., Manocha, Dinesh. (Oct. 10, 2021)

IEEE/CVF International Conference on Computer Vision (ICCV), 2021

Provable distributed stochastic gradient descent with delayed updates

Gao, Hongchang., Wu, Gang., Rossi, Ryan. (Apr. 29, 2021)

SIAM International Conference on Data Mining (SDM)

Structured Policy Iteration for Linear Quadratic Regulator

Park, Youngsuk., Rossi, Ryan., Wen, Zheng., Wu, Gang., Zhao, Handong. (Jul. 31, 2020)

International Conference on Machine Learning (ICML)

Linear Quadratic Regulator for Resource-Efficient Cloud Services

Park, Youngsuk., Mahadik, Kanak., Rossi, Ryan., Wu, Gang., Zhao, Handong. (Nov. 21, 2019)

ACM Symposium on Cloud Computing

Scalable Bid Landscape Forecasting in Real-time Bidding

Ghosh, Aritra., Mitra, Saayan., Sarkhel, Somdeb., Xie, Jason., Wu, Gang., Swaminathan, Vishy. (Sep. 16, 2019)

ECML-PKDD 2019

Digital content recommendation system using implicit feedback data

Wu, Gang., Swaminathan, Vishy., Mitra, Saayan., Kumar, Ratnesh. (Dec. 11, 2017)

IEEE BigData 2017

Context-aware video recommendation based on session progress prediction

Wu, Gang., Swaminathan, Vishy., Mitra, Saayan., Kumar, Ratnesh. (Oct. 7, 2017)

IEEE ICME 2017

Context-Aware Video Recommendation using Session Progress

Wu, Gang., Swaminathan, Vishy., Mitra, Saayan., Kumar, Ratnesh. (Jul. 10, 2017)

IEEE International Conference on Multimedia and Expo (ICME)