I obtained my Ph.D from Department of Computer Science at UC Berkeley, where I worked with Professor John Canny.
Prior to Berkeley, I studied Computer Science at Tsinghua UniversityYou can download my CV here
Email: bjiang[at]cs.berkeley.edu
We have intern/full-time positions for student to work on challenge research/industry problems.
Please drop me an email with your resume if you are interested.
New! We are organizing a summit on AI System/Framework (in Chinese). My slides (Eng)
New! We are hosting the 3rd Workshop on Deep Learning Practice for High-Dimensional Sparse Data with KDD 2021
I shared our experience of online inference optimization at DataFunTalk 2020. My slides (Chn)
We hosted the 2nd Workshop on Visualization for Deep Learning at ICML2017
Research Interest
Machine learning algorithm and system (deep or not), Data Visualization
I am interested in building toolkits for modern data scientists who will usually work on prototyping
new models or running experiments on large scale dataset. Our methodology includes but not limit
to using hardware accelerations like GPU, providing implementation framework for machine learning
algorithms, building visual interface for real-time control and monitoring.
I am also interested in interpreting deep learning algorthims (Either their behavior or training process).
Check out our BIDMach project and X-DeepLearning project.
Recent Papers
Towards Understanding the Overfitting Phenomenon of Deep Click-Through Rate Prediction Models
Zhao-Yu Zhang, Xiang-Rong Sheng, Yujing Zhang, Biye Jiang, Shuguang Han, Hongbo Deng, Bo Zheng [CIKM 2022]
Truncation-Free Matching System for Display Advertising at Alibaba
Jin Li, Jie Liu, Shangzhou Li, Yao Xu, Ran Cao, Qi Li, Biye Jiang, Guan Wang, Han Zhu, Kun Gai and Xiaoqiang Zhu [2021]
DCAF: A Dynamic Computation Allocation Framework for Online Serving System
Biye Jiang, Pengye Zhang, Rihan Chen, Binding Dai, Xinchen Luo, Yin Yang, Guan Wang, Guorui Zhou, Xiaoqiang Zhu and Kun Gai [2020]
COLD: Towards the Next Generation of Pre-Ranking System
Zhe Wang, Liqin Zhao, Biye Jiang, Guorui Zhou, Xiaoqiang Zhu and Kun Gai [2020]
XDL: an industrial deep learning framework for high-dimensional sparse data
Biye Jiang, Chao Deng, Huimin Yi, Zelin Hu, Guorui Zhou, Yang Zheng, Sui Huang, Xinyang Guo, Dongyue Wang, Yue Song, Liqin Zhao, Zhi Wang, Peng Sun, Yu Zhang, Di Zhang, Jinhui Li, Jian Xu, Xiaoqiang Zhu, Kun Gai [2019]
Diagnostic Visualization for Deep Neural Networks Using Stochastic Gradient Langevin Dynamics
Biye Jiang, David M. Chan, Tianhao Zhang, John F. Canny [2018]