Shubham Jain
Data Engineer - Sr. Consultant level
Team: Artificial Intelligence
Research Areas: Artificial Intelligence, Deep Learning, Generative AI, Sequence Modeling, Computer Vision
Shubham Jain joined Visa Research as a Senior Software Engineer in June 2019. Shubham received his M.S. in Computer Science from University of Illinois at Urbana-Champaign in 2019, and received his B.T. in Computer Science and Engineering from Indian Institute of Technology Kanpur in 2017. His master’s thesis focused on using landmarks for enhancing cloth retrieval. Prior to joining Visa, Shubham was a Software Engineer Intern at NVIDIA, working on deep learning research. Before working at NVIDIA, he was a Research Intern at Adobe and a Visiting Student Researcher at Montreal Institute of Learning Algorithms (MILA) under Prof. Yoshua Bengio.
As a member of the GenAI Foundational Team, his research interests include artificial intelligence, deep learning, generative AI, sequence modeling and computer vision, with a focus on developing generative AI models for payments and fraud detection. He has published research papers in leading international venues like ICLR, ACM CIKM, IEEE TVCG and IEEE BigData.
Publications
- L Wang, S Jain, Y Dou, J Wang, CCM Yeh, Y Fan, Y Zheng, X Dai, Z Zhuang, US Saini, W Zhang, M Das, Follow the Crowd but Keep Myself: Understanding the Role of Crowd Wisdom and Individual User Taste in Rating Prediction. International Conference on Computational Science and Computational Intelligence 2024.
- J Wang, L Wang, Y Zheng, CCM Yeh, S Jain, W Zhang, Learning-From-Disagreement: A Model Comparison and Visual Analytics Framework, IEEE Transactions on Visualization and Computer Graphics 2023.
- Zhang, D., Wang, L., Dai, X., Jain, S., Wang, J., Fan, Y., Yeh, C.-C.M., Zheng, Y., Zhuang, Z., Zhang, W, Fata-trans: Field and time-aware transformer for sequential tabular data, ACM International Conference on Information and Knowledge Management 2023.
- L Wang, J Wang, Y Zheng, S Jain, CCM Yeh, Z Zhuang, J Ebrahimi, and W Zhang, Learning from Disagreement for Event Detection. IEEE International Conference on Big Data 2022.
- S Mehri, K Kumar, I Gulrajani, R Kumar, S Jain, J Sotelo, A Courville, Y Bengio, SampleRNN: An Unconditional End-to-End Neural Audio Generation Model, International Conference on Learning Representations 2017.
Patents
- Y Zheng, W Zhang, M Yeh, L Wang, J Wang, S Jain, Z Zhuang (2025), “System, method, and computer program product for feature analysis using an embedding tree”, U.S. Patent No. 12,253,991. United States Patent and Trademark Office.
- D Gelda, S Jain, AM McGloin, W Zhang, H Yang, L Wang (2024), “System, method, and computer program product for determining fraud”, U.S. Patent No. 11,922,422. United States Patent and Trademark Office.