Shubham Jain
Data Engineer IV
Research Areas: Computer Vision, Deep Learning and Machine Learning
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 Risk Modeling team, his research interests are in computer vision, deep learning and machine learning. His paper titled “SampleRNN: An Unconditional End-to-end Neural Audio Generation Model” was published at International Conference on Learning Representations in 2017.
Publications
- 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 2022.
- 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, Y. Bengio, SampleRNN: An Unconditional End-to-End Neural Audio Generation Model, International Conference on Learning Representations 2016.
- 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, International Conference on Information and Knowledge Management 2023 (CIKM 2023)