Since June 17th 2024, Dr. Jiang Bian has been an applied scientist at Weather Science Team, Microsoft. Previously, he served as an R&D engineer (2021--2024) in Big Data Laboratory, Baidu Research. 

Dr. Jiang Bian received his Ph.D. degree at the University of Central Florida supervised by Prof.Zhishan Guo (co-supervised by Prof. Haoyi Xiong, Microsoft Core Search & AI). The first two years of his Ph.D. are in the Computer Science Department of Missouri University of Science and Technology. In advance of stepping into doctoral research, he received my B.Eng degree in Logistics Systems Engineering from Huazhong University of Science and Technology, and earned his M.Sc degree in Industrial Systems Engineering from the University of Florida.

   Email: bj911125{AT}yahoo{DOT}com

• Internet of Things

• Human-Subject Data Learning 

• Ubiquitous Computing

• Intelligent Cyber Physical Systems 

2024

[NMI] Ning Wang*, Jiang Bian*, Xuhong Li, Yuchen Li, Shahid Mumtaz, Linge Kong, Haoyi Xiong*. Multi-purpose RNA Language Modeling with Motif-aware Pre-training and Type-guided Fine-tuning. Nature Machine Intelligence, 2024.

[TSC] Haoyi Xiong, Jiang Bian, Yuchen Li, Xuhong Li, Mengnan Du, Shuaiqiang Wang, Dawei Yin, and Sumi Helal. When Search Engine Services meet Large Language Models: Visions and Challenges. IEEE Transactions on Services Computing, 2024. 

[CIKM] Xuewu Jiao, Xinsheng Luo, Miao Li, Jiang Bian, Junchao Yang, Wei Hu, Mingqing Hu, Weipeng Lu, Shikun Feng, Danlei Feng, Dongxu Yang, Haoyi Xiong, Shuanglong Li and Lin Liu. A Multi-Node Multi-GPU Distributed GNN Training Framework for Large-Scale Online Advertising. ACM International Conference on Information and Knowledge Management, 2024. (a joint work between Baidu and NVIDIA on the next generation of AI for Ads)

[TSC] Dianhai Yu*, Liang Shen, Hongxiang Hao, Weibao Gong, Huachao Wu, Jiang Bian, Lirong Dai, Haoyi Xiong. MoESys: A Distributed and Efficient Mixture-of-Experts Training and Inference System for Internet Services. IEEE Transactions on Service Computing, 2024.

2023

[DSAA'23] Yuchen Li, Haoyi Xiong, Linghe Kong, Jiang Bian, Shuaiqiang Wang, Guihai Chen and Dawei Yin. GS2P: A Generative Pre-trained Learning to Rank Model with Over-parameterization for Web-Scale Search. IEEE 10th International Conference on Data Science and Advanced Analytics, Best Paper Award, 2023.

[MLJ] Yuchen Li, Haoyi Xiong, Linghe Kong, Jiang Bian, Shuaiqiang Wang, Guihai Chen, and Dawei Yin. GS2P: A Generative Pre-trained Learning to Rank Model with Over-parameterization for Web-Scale Search. Machine Learning (MLJ for DSAA 2023 Journal Track), 2023.  

[TOMM] Jiang Bian, Xuhong Li, Tao Wang, Qingzhong Wang, Jun Huang, Chen Liu, Jun Zhao, Feixiang Lu, Dejing Dou, and Haoyi Xiong. P2ANet: Large-Scale Benchmark for Dense Action Detection from Table Tennis Match Broadcasting Videos. ACM Transactions on Multimedia Computing Communications and Applications, 2023.  

[TSC] Jiang Bian, Jizhou Huang, Shilei Ji, Yuan Liao, Xuhong Li, Qingzhong Wang, Jingbo Zhou, Yaqing Wang, Dejing Dou, and Haoyi Xiong. Feynman: Federated Learning-based Advertising for Ecosystems-Oriented Mobile Apps Recommendation. IEEE Transactions on Service Computing, 2023.

[TKDE] Yuchen Li, Haoyi Xiong, Qingzhong Wang, Linghe Kong, Hao Liu, Haifang Li, Jiang Bian, Shuaiqiang Wang, Guihai Chen, Dejing Dou, Dawei Yin. COLTR: Semi-supervised Learning to Rank with Co-training and Over-parameterization for Web Search. IEEE Transactions on Knowledge and Data Engineering, 2023.

[KDD'23] Xuewu Jiao, Weibin Li, Xinxuan Wu, Wei Hu, Miao Li, Jiang Bian, Siming Dai, Xinsheng Luo, Mingqing Hu, Zhengjie Huang, Danlei Feng, Junchao Yang, Shikun Feng, Haoyi Xiong, Dianhai Yu, Shuanglong Li, Jingzhou He, Yanjun Ma, Lin Liu. PGLBox: Multi-GPU Graph Learning Framework for Web-Scale Recommendation.  The 29th SIGKDD Conference on Knowledge Discovery and Data Mining, 2023.

[AAAI'23] Qingrui Jia*, Xuhong Li*, Lei Yu, Jiang Bian, Penghao Zhao, Shupeng Li, Haoyi Xiong, and Dejing Dou. Learning from Training Dynamics: Identifying Mislabeled Data Beyond Manually Designed Features. In Proceedings of the Thirty-Seven AAAI Conference on Artificial Intelligence, 2023. 

[TMM] Fei Wu*, Qingzhong Wang*, Jiang Bian*, Ning Ding, Feixiang Lu, Jun Cheng, Dejing Dou, and Haoyi Xiong. A Survey on Video Action Recognition in Sports: Datasets, Methods and Applications. IEEE Transactions on Multimedia, 2023.

[TITS] Nicholas Gray*, Megan Moraes*, Jiang Bian*, Alex Wang*, Allen Tian, Kurt Wilson, Yan Huang, Haoyi Xiong, and Zhishan Guo. GLARE: A Dataset for Traffic Sign Detection in Sun Glare. IEEE Transactions on Intelligent Transportation Systems, 2023.

[ISBI'23] Yuxuan Zhang, Qingzhong Wang, Jiang Bian, Yi Liu, Yanwu Xu, Dejing Dou, and Haoyi Xiong. Video4MRI: An Empirical Study on Brain Magnetic Resonance Image Analytics with CNN-based Video Classification Frameworks. IEEE International Symposium on Biomedical Imaging, 2023. 

[MIUA'23] Ziqi Wen*, Qingzhong Wang*, Jiang Bian, Xuhong Li, Yi Liu, and Haoyi Xiong. Context Matters: Cross-domain Cell Detection in Histopathology Images via Contextual Regularization. 27th Conference on Medical Image Understanding and Analysis, 2023. 

2022

[TMC] Jiang Bian*, Haoyi Xiong*, Zhiyuan Wang, Jingbo Zhou, Shilei Ji, Hongyang Chen, Daqing Zhang, Dejing Dou. AFCS: Aggregation-Free Spatial-Temporal Mobile Community Sensing. IEEE Transaction on Mobile Computing, 2022. 

[KAIS] Xuhong Li, Haoyi Xiong, Xingjian Li, Xuanyu Wu, Xiao Zhang, Jiang Bian, and Dejing Dou. Interpretable Deep Learning: Interpretations, Interpretability, Trustworthiness, and Beyond. Knowledge and Information Systems, 2022. 

[DataPerf'22] Qingrui Jia, Xuhong Li, Lei Yu, Jiang Bian, Penghao Zhao, Shupeng Li, Haoyi Xiong, Dejing Dou. Learning from Training Dynamics: Identifying Mislabeled Data Beyond Manually Designed Features. DataPerf workshop at ICML, 2022. 

[IOTJ] Jiang Bian*, Abdullah Al Arafat*, Haoyi Xiong, Jing Li, Li Li, Hongyang Chen, Jun Wang, Dejing Dou, Zhishan Guo. Machine Learning in Real-Time Internet of Things(IoT) Systems: A Survey. IEEE Internet of Things Journal, 2022. 

[DMKD] Ashkan Farhangi*, Jiang Bian*, Arthur Huang, Haoyi Xiong, Jun Wang, Zhishan Guo. AA-Forecast: Anomaly-Aware Forecast for Extreme Events. Data Mining and Knowledge Discovery (ECML Journal Track), 2022. 

2021

[MLJ] Junjie Shi, Jiang Bian, Jakob Richter, Kuan-Hsun Chen, Jörg Rahnenführer, Haoyi Xiong, Jian-Jia Chen. MODES: Model-based Optimization on Distributed Embedded Systems. Machine Learning (ECML Journal Track), 2021. 

[TKDD] Kafeng Wang*, Haoyi Xiong*, Jiang Bian*, Zhanxing Zhu, Qian Gao, Zhishan Guo, Cheng-Zhong Xu, Jun Huan. Sampling Sparse Representations with Randomized Measurement Langevin Dynamics. ACM Transactions on Knowledge Discovery from Data, 2021. 

[TMM] Baoxin Zhao*, Haoyi Xiong*, Jiang Bian, Zhishan Guo, Cheng-Zhong Xu, and Dejing Dou. COMO: Widening Deep Neural Networks with COnvolutional MaxOut. IEEE Transactions on Multimedia, 2021. 

[TETCI] Sudharsan Vaidhun, Zhishan Guo, Jiang Bian, Haoyi Xiong, Sajal K. Das. Dynamic Path Planning for Unmanned Aerial Vehicles Under Deadline and Sector Capacity Constraints. IEEE Transactions on Emerging Topics in Computational Intelligence, 2021. 

2020

[TKDD] Jiang Bian*, Haoyi Xiong*, Yanjie Fu, Jun Huan, Zhishan Guo. MP2SDA: Multi-Party Parallelized Sparse Discriminant Learning. ACM Transactions on Knowledge Discovery from Data, 2020. 

[TETCI] Jiang Bian, Sijia Yang, Haoyi Xiong, Licheng Wang, Yanjie Fu, Zeyi Sun, JunWang, Zhishan Guo. CRLEDD: Regularized Causalities Learning for Early Detection of Diseases Using Electronic Health Record (EHR) Data. IEEE Transactions on Emerging Topics in Computational Intelligence, 2020. 

[ICACI'20] Sudharsan Vaidhun, Zhishan Guo, Jiang Bian, Haoyi Xiong, Sajal K. Das. Priority-based Multi-Flight Path Planning with Uncertain Sector Capacities. Proceedings of the 12th International Conference Advanced Computational Intelligence, 2020. 

2019

[RTSS'19 BP] Ashkan Farhangi*, Jiang Bian*, Jun Wang, and Zhishan Guo. A Deep Learning Strategy for I/O Scheduling in Storage Systems. Proceedings of the 40th IEEE Real-Time Systems Symposium, BP Session, 2020. 

[BigData'19] Jiang Bian, Weibo Wang, Xiang Zhang, Wei Wang, Arthur Huang, Zhishan Guo. On Generating Dominators of Customer Preferences. Proceedings of IEEE International Conference on Big Data, 5th Special Session on Intelligent Data Mining, 2019. 

[AAAI'19] Haoyi Xiong*, Kafeng Wang*, Jiang Bian*, Zhanxin Zhu, Chengzhong Xu, Zhishan Guo, Jun Huan. SpHMC: Spectral Hamiltonian Monte Carlo. Proceedings of the 33nd AAAI Conference on Artificial Intelligence (AAAI), 2019. 

2018

[TNNLS] Haoyi Xiong, Wei Cheng, Jiang Bian, Wenqing Hu, Zeyi Sun, Zhishan Guo. DBSDA: Lowering the Bound of Misclassification Rate for Sparse Linear Discriminant Analysis via Model Debiasing. IEEE Transactions on Neural Networks and Learning Systems, 2018. 

[IJCAI'18] Haoyi Xiong, Wei Cheng, Yanjie Fu, Wenqing Hu, Jiang Bian, Zhishan Guo. De-Biasing Covariance-Regularized Discriminant Analysis. Proceedings of the 27th International Joint Conferences on Artificial Intelligence (IJCAI), 2018. 

[AAAI'18] Jiang Bian*, Haoyi Xiong*, Yanjie Fu, Sajal K. Das. CSWA: Aggregation-Free Spatial-Temporal Community Sensing. Proceedings of the 32nd AAAI Conference on Artificial Intelligence (AAAI), 2018. 

2017

[ICDM'17] Jiang Bian, Haoyi Xiong, Wei Cheng, Yanjie Fu, Wenqing Hu, Zhishan Guo. Multi-Party Sparse Discriminant Learning. Proceedings of the 17th IEEE International Conference on Data Mining (ICDM), 2017. 

[ICDM'17] Haoyi Xiong, Wei Cheng, Wenqing Hu, Jiang Bian, Zhishan Guo. AWDA: An Adaptive Wishart Discriminant Analysis. Proceedings of the 17th IEEE International Conference on Data Mining (ICDM), 2017. 

[BHI'17] Jiang Bian, Laura E. Barnes, Guanling Chen, Haoyi Xiong. Early Detection of Diseases using Electronic Health Records Data and Covariance-Regularized Linear Discriminant Analysis. Proceedings of IEEE International Conference on Biomedical and Health Informatics (BHI), 2017. 

*equal contribution