Yan Zheng

Principal Research Scientist, Fundamental AI

Research Areas: Representation Learning, Time Series Analysis, Recommendation, Visualization, Large Language Model with Transaction Data

Yan Zheng, Visa Research scientist.

Biography

Dr. Yan Zheng joined Visa Research in 2017 as a Staff Research Scientist, advancing to Senior Staff Research Scientist in 2019 and Principal Research Scientist in 2022. She earned her Ph.D. in Computer Science from the University of Utah in 2017.

Dr. Zheng's research spans Representation Learning, Time Series Analysis, Recommendation Systems, Visualization, and Model Explanations. She has authored numerous published papers and holds several patents, with notable contributions to conferences such as ICLR, ICDM, SDM, KDD, PacificVis and SIGIR.

Her paper “Denoising Self-Attentive Sequential Recommendation” won Best Paper at Recommender Systems 2023, while “How Does Attention Work in Vision Transformers? A Visual Analytics Attempt” received an Honorable Mention at PacificVis 2023. Additionally, her paper “EmbeddingTree: Hierarchical Exploration of Entity Features in Embedding” won the Best Visualization Notes Award at PacificVis 2023.

Dr. Zheng has also made significant practical contributions, notably in the development of Visa Deep Authorization (VDA), which enhances fraud detection and customer benefits. VDA's success is projected to generate approximately $100 million revenue over the next five years and has been featured in various publications.

Conferences and Journals

  1. Yeh, C. C. M., Der, A., Saini, U. S., Lai, V., Zheng, Y., Wang, J., Dai, X., Zhuang, Z., Fan, Y., Chen, H., Aboagye, P. O., Wang, L., Zhang, W., Keogh, E. “Matrix Profile for Anomaly Detection on Multidimensional Time Series” ICDM 2024
  2. Der, A., Yeh, C.-C. M., Dai, X., Chen, H., Zheng, Y., Fan, Y., Zhuang, Z., Lai, V., Wang, J., Wang, L., Zhang, W., Keogh, E. “A Systematic Evaluation of Generated Time Series and Their Effects in Self-Supervised Pretraining” CIKM 2024
  3. Yeh, C. C. M., Fan, Y., Dai, X., Saini, U. S., Lai, V., Aboagye, P. O., Wang, J., Chen, H., Zheng, Y., Zhuang, Z., Wang, L., Zhang, W. “RPMixer: Shaking Up Time Series Forecasting with Random Projections for Large Spatial-Temporal Data” KDD 2024
  4. Chen, H., Xu, Z., Yeh, C. C. M., Lai, V., Zheng, Y., Xu, M., Tong, H. “Masked Graph Transformer for Large-Scale Recommendation” SIGIR 2024
  5. Wang, J., Yeh, C. C. M., Fan, Y., Dai, X., Zheng, Y., Wang, L., Zhang, W. “PromptLandscape: Guiding Prompts Exploration and Analysis with Visualization” PacificVis 2024
  6. Li, Y., Wang, J., Aboagye, P., Yeh, C. C. M., Zheng, Y., Wang, L., Zhang, W., Ma, K. L. “Visual Analytics for Efficient Image Exploration and User-Guided Image Captioning” IEEE Transactions on Visualization and Computer Graphics
  7. Der, A., Yeh, C. C. M., Zheng, Y., Wang, J., Zhuang, Z., Wang, L., Zhang, W., Keogh, E. “Pupae: Intuitive and actionable explanations for time series anomalies” SDM 2024
  8. Der, A., Yeh, C. C. M., Zheng, Y., Wang, J., Chen, H., Zhuang, Z., Wang, L., Zhang, W., Keogh, E. “Time series synthesis using the matrix profile for anonymization” BigData 2023
  9. Yeh, C. C. M., Chen, H., Dai, X., Zheng, Y., Fan, Y., Lai, V., Wang, J., Der, A., Zhuang, Z., Wang, L., Zhang, W. “Temporal Treasure Hunt: Content-based Time Series Retrieval System for Discovering Insights” BigData 2023
  10. Yeh, C. C. M., Chen, H., Fan, Y., Dai, X., Zheng, Y., Lai, V., Wang, J., Zhuang, Z., Wang, L., Zhang, W., Keogh, E. “Ego-network transformer for subsequence classification in time series data” BigData 2023
  11. Yeh, C. C. M., Dai, X., Zheng, Y., Wang, J., Chen, H., Fan, Y., Der, A., Zhuang, Z., Wang, L., Zhang, W. “Multitask Learning for Time Series Data with 2D Convolution” ICMLA 2023
  12. 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” CIKM 2023
  13. Fan, Y., Yeh, C. C. M., Chen, H., Zheng, Y., Wang, L., Wang, J., Dai, X., Zhuang, Z., Zhang, W. “Spatial-temporal graph boosting networks: Enhancing spatial-temporal graph neural networks via gradient boosting” CIKM 2023
  14. Yeh, C. C. M., Dai, X., Chen, H., Zheng, Y., Fan, Y., Der, A., Lai, V., Zhuang, Z., Wang, J., Wang, L., Zhang, W. “Toward a foundation model for time series data” CIKM 2023
  15. Yeh, C. C. M., Chen, H., Dai, X., Zheng, Y., Wang, J., Lai, V., Fan, Y., Der, A., Zhuang, Z., Wang, L., Zhang, W., Phillips, J. M. “An efficient content-based time series retrieval system” CIKM 2023
  16. Fan, Y., Yeh, C. C. M., Chen, H., Wang, L., Zhuang, Z., Wang, J., Dai, X., Zheng, Y., Zhang, W. “Spatial-Temporal Graph Sandwich Transformer for Traffic Flow Forecasting” PKDD 2023
  17. Chen, H., Zhou, K., Lai, K. H., Yeh, C. C. M., Zheng, Y., Hu, X., Yang, H. “Hessian-aware Quantized Node Embeddings for Recommendation” Recommender Systems 2023
  18. Chen, H., Li, X., Lai, V., Yeh, C. C. M., Fan, Y., Zheng, Y., Das, M., Yang, H. “Adversarial Collaborative Filtering for Free” Recommender Systems 2023
  19. Chen, H., Zhou, K., Jiang, Z., Yeh, C. C. M., Li, X., Pan, M., Zheng, Y., Hu, X., Yang, H. “Probabilistic Masked Attention Networks for Explainable Sequential Recommendation” IJCAI 2023
  20. Chen, H., Yeh, C. C. M., Fan, Y., Zheng, Y., Wang, J., Lai, V., Das, M., Yang, H. “Sharpness-aware graph collaborative filtering” SIGIR 2023
  21. Li, Y., Wang, J., Dai, X., Wang, L., Yeh, C. C. M., Zheng, Y., Zhang, W., Ma, K. L. “How does attention work in vision transformers? A visual analytics attempt” IEEE Transactions on Visualization and Computer Graphics. Best Paper Honorable Mention in PacificVis 2023
  22. Zheng, Y., Wang, J., Yeh, C. C. M., Fan, Y., Chen, H., Wang, L., Zhang, W. “EmbeddingTree: Hierarchical Exploration of Entity Features in Embedding” Best Note Award in PacificVis 2023
  23. Aboagye, P. O., Zheng, Y., Shunn, J., Yeh, C. C. M., Wang, J., Zhuang, Z., Chen, H., Wang, L., Zhang, W., Phillips, J. M. “Interpretable Debiasing of Vectorized Language Representations with Iterative Orthogonalization” ICLR 2023
  24. Li, H., Wang, J., Zheng, Y., Wang, L., Zhang, W., Shen, H.-W. “Compressing and interpreting word embeddings with latent space regularization and interactive semantics probing” Information Visualization 2023
  25. Aboagye, P. O., Zheng, Y., Yeh, C. C. M., Wang, J., Zhuang, Z., Chen, H., Wang, L., Zhang, W., Phillips, J. “Quantized Wasserstein Procrustes Alignment of Word Embedding Spaces” AMTA 2022
  26. Der, A., Yeh, C. C. M., Wu, R., Wang, J., Zheng, Y., Zhuang, Z., Wang, L., Zhang, W., Keogh, E. “Matrix Profile XXVII: A Novel Distance Measure for Comparing Long Time Series” ICKG 2022
  27. Wang, L., Wang, J., Zheng, Y., Jain, S., Yeh, C. C. M., Zhuang, Z., Ebrahimi, J., Zhang, W. “Learning from Disagreement for Event Detection” Big Data 2022
  28. Chen, H., Lin, Y., Pan, M., Wang, L., Yeh, C. C. M., Li, X., Zheng, Y., Wang, F., Yang, H. “Denoising self-attentive sequential recommendation” RecSys 2022
  29. Chen, H., Li, X., Yeh, C. C. M., Zheng, Y., Yang, H. “TinyKG: Memory-Efficient Training Framework for Knowledge Graph Neural Recommender Systems” RecSys 2022
  30. Wang, J., Wang, L., Zheng, Y., Yeh, C. C. M., Jain, S., Zhang, W. “Learning-From-Disagreement: A Model Comparison and Visual Analytics Framework” TVCG 2022
  31. Yeh, C. C. M., Gu, M., Zheng, Y., Chen, H., Ebrahimi, J., Zhuang, Z., Wang, J., Wang, L., Zhang, W. “Embedding Compression with Hashing for Efficient Representation Learning in Graph” KDD 2022
  32. Aboagye, P., Zheng, Y., Yeh, C. C. M., Wang, J., Zhang, W., Wang, L., Yang, H., Phillips, J. “Normalization of Language Embeddings for Cross-Lingual Alignment” ICLR 2022
  33. Yeh, C. C. M., Zheng, Y., Wang, J., Chen, H., Zhuang, Z., Zhang, W., Keogh, E. “Error-bounded Approximate Time Series Joins using Compact Dictionary Representations of Time Series” SDM 2022
  34. Wang, Y., Zheng, Y., Peng, Y., Yeh, C. C. M., Zhuang, Z., Das, M., Bendre, M., Li, F., Zhang, W., Phillips, J. M. “Constrained Non-Affine Alignment of Embeddings” ICDM 2021
  35. Rathore, A., Dev, S., Phillips, J. M., Srikumar, V., Zheng, Y., Yeh, C. C. M., Wang, J., Zhang, W., Wang, B. “An Interactive Visual Demo of Bias Mitigation Techniques” NeurIPS 2021 Demo
  36. Yeh, C. C. M., Zhuang, Z., Wang, J., Zheng, Y., Ebrahimi, J., Mercer, R., Wang, L., Zhang, W. “Online Multi-horizon Transaction Metric Estimation with Multi-modal Learning in Payment Networks” CIKM 2021
  37. Yeh, C. C. M., Zhuang, Z., Zheng, Y., Wang, L., Wang, J., Zhang, W. “Merchant category identification using credit card transactions” Big Data 2020
  38. Yeh, C. C. M., Gelda, D., Zhuang, Z., Zheng, Y., Gou, L., Zhang, W. “Towards a flexible embedding learning framework” ICDMW 2020
  39. Gao, Y., Phillips, J. M., Zheng, Y., Min, R., Fletcher, P. T., Gerig, G. “Fully Convolutional Structured LSTM Networks for Joint 4D Medical Image Segmentation” ISBI 2018
  40. Zheng, Y., Ou, Y., Lex, A., Phillips, J. M. “Visualization of Big Spatial Data using Coresets for Kernel Density Estimates” Visual Data Science (VDS) 2017
  41. Zheng, Y., Phillips, J. M. “Coresets for Kernel Regression” KDD 2017
  42. Zheng, Y., Phillips, J. M. “Subsampling in Smoothed Range Spaces” ALT 2015
  43. Zheng, Y., Phillips, J. M. “L∞ Error and Bandwidth Selection for Kernel Density Estimates of Large Dataset” KDD 2015
  44. Phillips, J. M., Wang, B., Zheng, Y. “Geometric Inference on Kernel Density Estimates” SOCG 2015
  45. Zheng, Y., Jestes, J., Phillips, J. M., Li, F. “Quality and Efficiency in Kernel Density Estimates for Large Data” SIGMOD 2013
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