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Dr. Jianpeng Xu
Senior Manager II, Data Science @ Walmart Global Tech (Former WalmartLabs)
Personal Email: jianpeng.xu@gmail.com
Google Scholar
LinkedIn:
Short Biography
Jianpeng Xu is currently a Senior Manager of Data Science at Walmart Golbal Tech, focusing on the development and improvement of the recommendation and personalization models and products. Before joining WalmartLabs, Jianpeng worked at eBay on deals optimization, timeseries forecasting and anomaly detection for eCommerce metrics. Jianpeng Xu earned his Ph.D in CSE Department, Michigan State University (MSU) in 2017 Summer, under the supervision of Dr. Pang-Ning Tan. He received his MS in Computer Science, Harbin Institute of Technology (HIT) in 2010 and BS in Computer Science, Shandong University (SDU) in 2007. Jianpeng has a broad research interest in Data Mining and Machine Learning, which includes GeoSpatio-temporal data mining, anomaly detection, multi-task learning, online learning, and AI algorithms and their applications. He received the Best Poster Award from Doctoral Forum on SDM 2016 and Best Paper Award from IEEE BigData 2016. Jianpeng served as Program Committee members for multiple prestigious data mining and machine learning conferences and was invited as reviewers for Journals such as TKDE, TKDD, TNNLS and Pattern Recognition. He served as co-organizers for multiple workshops in recommender systems and information retrieval domains. He is also the Topic Editor for Research Topic on Industrial Recommender Systems, Journal of Frontiers in Big Data.
Click here for my full CV
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Recent News:
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SELECTED PEER-REVIEWED PUBLICATIONS
For complete list, please check my Google Scholar page.
- NEAT: A Label Noise-resistant Complementary Item Recommender System with Trustworthy Evaluation
Luyi Ma, Jianpeng Xu, Jason H.D. Cho, Evren Korpeoglu, Sushant Kumar, Kannan Achan
IEEE BigData2021 (Paper)[Github]
- PURE: Positive-Unlabeled Recommendation with Generative Adversarial Network
Yao Zhou, Jianpeng Xu, Jun Wu, Zeinab Taghavi Nasrabadi, Evren Korpeoglu, Kannan Achan, Jingrui He
KDD2021 (Paper)[Github]
- Spatio-temporal Multi-task Learning via Tensor Decomposition
Jianpeng Xu, Jiayu Zhou, Pang-Ning Tan, Xi Liu, Lifeng Luo
IEEE Transactions on Knowledge and Data Engineering (TKDE), 2019 (Paper)[Github]
- MUSCAT: Multi-Scale Spatio-Temporal Learning with Application to Climate Modeling
Jianpeng Xu, Xi Liu, Tyler Wilson, Pang-Ning Tan, Pouyan Hatami and Lifeng Luo
International Joint Conference on Artificial Intelligence (IJCAI), 2018 (Paper) [Github]
- Online Multi-task Learning Framework for Ensemble Forecasting
Jianpeng Xu, Pang-Ning Tan, Jiayu Zhou and Lifeng Luo
IEEE Transactions on Knowledge and Data Engineering (TKDE), 2017 (Paper) [Github]
- WISDOM: Weighted Incremental Spatio-Temporal Multi-Task Learning via Tensor Decomposition
Jianpeng Xu, Jiayu Zhou, Pang-Ning Tan, Xi Liu, Lifeng Luo
IEEE BigData2016 Best Paper Award (Paper)[Github]
- Multi-Task Feature Interaction Learning
Kaixiang Lin, Jianpeng Xu, Shuiwang Ji, Jiayu Zhou
KDD2016 (Paper)[Github]
- Synergies that Matter: Efficient Interaction Selection via Sparse Factorization Machine
Jianpeng Xu, Kaixiang Lin, Pang-Ning Tan and Jiayu Zhou
SDM2016 (Paper)[Github]
- GSpartan: a Geospatio-Temporal Multi-task Learning Framework for Multi-location Prediction
Jianpeng Xu, Pang-Ning Tan, Lifeng Luo and Jiayu Zhou
SDM2016 (Paper)[Github]
- FORMULA: FactORized MUlti-task LeArning for task discovery in personalized medical models
Jianpeng Xu, Jiayu Zhou and Pang-Ning Tan
SDM2015 (Paper)[Github]
- ORION: Online Regularized multI-task regressiON and its application to ensemble forecasting
Jianpeng Xu, Pang-Ning Tan and Lifeng Luo
ICDM2014 (Paper)[Github]
- HDminer: Efficient Mining of High Dimensional Frequent Closed Patterns from Dense Data and Its Application
Jianpeng Xu and Shufan Ji
ICDMW2014 on Scalable Data Analytics: Theory and Applications (Paper)
- Detecting Malicious Clients in ISP Networks Using HTTP Connectivity Graph and Flow Information
Lei Liu, Sabyasachi Saha, Ruben Torres, Jianpeng Xu, Pang-Ning Tan, Antonio Nucci, Marco Mellia
ASONAM2014 (Paper)
PATENT
- Detecting Malicious Endpoints Using Network Connectivity and Flow Information
Sabyasachi Saha, Lei Liu, Ruben Torres, Jianpeng Xu, Antonio Nucci
Publication Number: US8813236 B1 (Link)
Course Taught (Teaching Assistant)
CSE881: Data Mining
including: Data Preprocessing, Classification, Regression, Association Analysis, Clustering, Anomaly Detection, Network Mining, Data Stream Mining
CSE491/891: Computational Techniques for Large-Scale Data Analysis
including: Data Collection, Storage, and Preprocessing, Data Analysis (Classification, Regression, Clustering, etc.), Implementation (Programming based on Mapreduce, Hadoop, Hive, Pig, etc.), Case Study and Applications
Service
- Topic Editor for Research Topic on Industrial Recommender Systems, Journal of Frontiers in Big Data
- Workshop Organizer: IRS2020@KDD ,
IRS2021@KDD ,
ICML 2021 Workshop on Representation Learning for Finance and e-Commerce Applications ,
Workshop on Decision Making for Modern Information Retrieval System (WSDM'22)
- Program Committee Member for KDD 2018, 2019, 2020, 2021, NeurIPS 2020, AAAI 2019, SDM 2021, PAKDD 2019, IEEE BigData 2018, 2019, BIBM 2015, 2016, IJCAI 2015, MLRec 2015, 2016, 2017(in conjunction with SDM), BigTraffic 2018
- Reviewer for Journals: TKDE, TKDD, TNNLS, Pattern Recognition, Neurocomputing, BMC Bioinformatics, EURASIP
Awards:
- Best Paper Award: IEEE BigData 2016
- Best Poster Award: Doctoral Forum, SDM2016
- Student Travel Award: IEEE BigData 2016, SDM 2015, 2016, ICDM 2014, MSU Graduate School 2014
- Honorable Mention Award in Mathematical Contest in Modeling (MCM), 2006
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