Tao Yang
Ph.D. Student
School of Computing,
University of Utah
Address:
50 S. Central Campus Drive
School of Computing, University of Utah
Salt Lake City, UT, 84112
Email: taoyang [at] cs [dot] utah [dot] edu
[CV]
[Google scholar]
I am a third-year Ph.D. student, advised by Prof. Qingyao Ai in School of Computing, University of Utah. I received my B.Eng. in Engineering Mechanics from Wuhan University (2016) and M.Eng in Engineering Mechanics from Zhejiang University (2019).
My research mainly focuses on Information Retrieval and Machine Learning related topics. Currently I'm working on applying deep learning techniques on IR problems including product search/recommendation and learning to rank.
Experience
- Applied Scientist Intern, in Amazon A9, Palo Alto, CA, USA, May 2021 - August 2021.
- University of Utah, Research Assistant, advised by Prof. Qingyao Ai, Salt Lake City, UT, USA, Sept. 2019 - Now
- Zhejiang University, Research Assistant, advised by Prof. Tiefeng Li . Hangzhou, China, Sept. 2016 - June 2019
- Zhejiang University,M.S., Department of Engineering Mechanics, Hangzhou, China, Sept. 2016 - July 2019
- Wuhan University,B.S., Department of Engineering Mechanics, Wuhan, China, Sept. 2012 - July 2016
Awards and Honors
- WWW'2021 Student Travel Grant; CIKM'2020 Student Travel Grant;
- Zhejiang University Nandu Second-class Scholarship(2017), Scholarship in honor of Haojiang Ding(2017), Outstanding student Prize(2017)
- the Sixth National Collegiate Mathematics Competition, China, 2015
- Wuhan University Second-class Scholarship(2013,2014,2015),Outstanding Student prize(2013,2014,2015)
Publications
2021
- ULTRA: An Unbiased Learning To Rank Algorithm Toolbox [code]
by Anh Tran, Tao Yang, Qingyao Ai
CIKM (2021) - Maximizing Marginal Fairness for Dynamic Learning to Rank
[code]
by Tao Yang, Qingyao Ai
The Web conference 2021 - Unbiased Learning to Rank: Online or Offline? [code]
by Qingyao Ai, Tao Yang, Huazheng Wang, Jiaxin Mao
In ACM Transactions on Information Systems (TOIS) - Global vision-based formation control of soft robotic fish swarm
by Zhen Zhang, Tao Yang, Tianhao Zhang, Fanghao Zhou, Nuo Cen, Tiefeng Li, Guangming Xie
In Soft Robotics
2020
- Analysis of multivariate scoring functions for automatic unbiased learning to rank [code]
by Tao Yang, Shikai Fang, Shibo Li, Yulan Wang, Qingyao Ai
CIKM (2020) - Anisotropic electroactive elastomer for highly maneuverable soft robotics
by Youhua Xiao, Jie Mao, Yejie Shan, Tao Yang, Zheqi Chen, Fanghao Zhou, Jin He, Youqing Shen, Junjie Zhao, Tiefeng Li, Yingwu Luo
The Nanoscale
2018
- A soft artificial muscle driven robot with reinforcement learning
by Tao Yang, Youhua Xiao, Zhen Zhang, Yiming Liang, Guorui Li, Mingqi Zhang, Shijian Li, Tuck-Whye Wong, Yong Wang, Tiefeng Li, Zhilong Huang
Scientific reports - Artificial muscle driven soft hydraulic robot: electromechanical actuation and simplified modeling
by Mingqi Zhang, Guori Li, Xuxu Yang, Youhua Xiao,Tao Yang, Tuck-Whye Wong, Tiefeng Li
Smart Materials and Structures - Scar-Like Self-Reinforced and Failure-Tolerant Dielectric Elastomer Actuator With AgNWs Electrode
by Mingqi Zhang, Yuhan Xie, Tingge Yao, Xunuo Cao, Zhen Zhang, Guorui Li, Zipeng Ma, Jie Mao, Tao Yang, Yingwu Luo, Tiefeng Li
Journal of Applied Mechanics
Projects
- ULTRA: Unbiased Learning to Rank Algorithms (ULTRA) [project page]
This is an Unbiased Learning To Rank Algorithms (ULTRA) toolbox, which provides a codebase for experiments and research on learning to rank with human annotated or noisy labels. With the unified data processing pipeline, ULTRA supports multiple unbiased learning-to-rank algorithms, online learning-to-rank algorithms, neural learning-to-rank models, as well as different methods to use and simulate noisy labels (e.g., clicks) to train and test different algorithms/ranking models.
