Da Tang's world

Dream for future

Short Bio

I am a third year Ph.D. student at the Machine Learning Lab of Columbia University (under the supervision of Prof. Tony Jebara). Previously, I was an undergraduate student at Institute for Interdisciplinary Information Sciences, Tsinghua University (under the supervision of Prof. Jun Zhu). I am interested in Machine Learning and Artificial Intelligence as well as their applications to related fields, like Computer Vision and Natual Language Processing.

To contact me, please email me at qltedxtc@gmail.com or datang@cs.columbia.edu.

Education Background

Time (or Expected Time) Degree Level Major Second Major School
2015-2020 Doctoral Degree Computer Science Columbia University
2011-2015 Bachelor's Degree Computer Science Pure and Applied Math Tsinghua University

Work Experiences

1. Research Intern, instructed by Dr. Jianfeng Gao, Dr. Chong Wang, Dr. Lihong Li, and Mr. Xiujun Li, Microsoft Corporation, Redmond, United States.

2. Software Engineering Intern, instructed by Dr. Lan Nie and Dr. Sajid Siddiqi, Google Inc., Mountain View, United States.

3. Research Intern, instructed by Prof. Tong Zhang, Big Data Lab, Baidu Research, Beijing, China.

For more information about my research experience, please look at my CURRICULUM VITAE.

Publications

1. Da Tang and Rajesh Ranganath, Natural Gradients via the Variational Predictive Distribution, Advances in Approximate Bayesian Inference (AABI) Workshop, Advances in Neural Information Processing Systems (NIPS), 2017 (Spotlight) [PDF]

2. Da Tang and Tony Jebara, Initialization and Coordinate Optimization for Multi-way Matching, Artificial Intelligence and Statistics (AISTATS), 2017 [PDF]

3. Da Tang and Tong Zhang, On the Duality Gap Convergence of ADMM Methods, arXiv preprint arXiv:1508.03702, 2015 [PDF]

4. Tianlin Shi, Da Tang, Liwen Xu and Thomas Moscibroda, Correlated Compressive Sensing for Networked Data, Uncertainty in Artificial Intelligence (UAI), 2014 [PDF]