I am an associate professor of Computer Science at Tsinghua University. My research focuses on developing statistical machine learning methods to understand complex scientific and engineering data. My current interests are in latent variable models, large-margin learning, Bayesian nonparametrics, and sparse learning in high dimensions.

• Welcome to visit my new page! After spending three wonderful years, I have moved from the Machine Learning Department in Carnegie Mellon University to join the Department of Computer Science and Technology in Tsinghua University as an associate professor, since last September.

• I will co-host the dragon star machine learning lectures given by Dr. Kai Yu and Prof. Tong Zhang, from August 6th to August 10th, 2012.

• Jun Zhu, Amr Ahmed, and Eric P. Xing. MedLDA: Maximum Margin Supervised Topic Models, Journal of Machine Learning Research, 2012, in press.

• Jun Zhu. Max-Margin Nonparametric Latent Feature Models for Link Prediction, To Appear in International Conference on Machine Learning, Edinburgh, Scotland, 2012.

• Yuandong Tian and Jun Zhu. Learning from Crowds in the Presence of Schools of Thought, To Appear in SIGKDD, Beijing, China, 2012.

• Ning Chen, Jun Zhu, Fuchun Sun, and Eric P. Xing. Large-margin Subspace Learning for Multi-view Data Analysis, IEEE Trans. on PAMI, 2012, in press.

• Jun Zhu, Ning Chen, and Eric P. Xing. Infinite Latent SVM for Classification and Multi-task Learning, Advances in Neural Information Processing Systems (NIPS), 2011.

• Jun Zhu, and Eric P. Xing. Sparse Topical Coding, Uncertainty in Artificial Intelligence (UAI), 2011.

• Jun Zhu, Ni Lao, Ning Chen, and Eric P. Xing. Conditional Topical Coding: an Efficient Topic Model Conditioned on Rich Features, SIGKDD International Conference on Knowledge Discovery and Data Mining, 2011.

• Jun Zhu, Ning Chen, and Eric P. Xing. Infinite SVM: a Dirichlet Process Mixture of Large-margin Kernel Machines, International Conference on Machine Learning (ICML), 2011.