Yang Yang

PhD Student Computational Biology Department, School of Computer Science Carnegie Mellon University Address: 5000 Forbes Ave, GHC 7707, Pittsburgh PA 15213, USA Email: yy3 [at] cs [dot] cmu [dot] edu

I am a fifth-year PhD student in the School of Computer Science at Carnegie Mellon University, supervised by Dr. Jian Ma. I recevied my M.S. degree in Control Science and Engineering and B.E. degree in Automation from Tsinghua University in China. My primary research area is Machine Learning and its applications in Biomedicine. My research focus is on developing novel algorithms to solve challenging biomedical problems.

My PhD research has been primarily focused on developing computational methods to study three-dimensional (3D) genome organization and comparative genomics. I have worked on developing probabilistic models to provide the new generic frameworks for comparing 1D and 3D multi-species continuous-trait genomic features, respectively. A copy of my CV can be found here.

Education

• PhD student in Computational Biology (Jan. 2016 - Present)
  School of Computer Science, Carnegie Mellon University
  Advisor: Dr. Jian Ma

• MS student in Machine Learning (Mar. 2019 - Present)
  School of Computer Science, Carnegie Mellon University
  (secondary degree program)

• PhD student in Computer Science (Aug. 2015 - Dec. 2015)
  Department of Computer Science, University of Illinois at Urbana-Champaign
  Advisor: Dr. Jian Ma

• M.S. in Control Science and Engineering (Sept. 2012 - July 2015)
  Department of Automation, Tsinghua University
  Advisor: Dr. Xiangyang Ji

• B.E. in Automation (Aug. 2008 - July 2012)
  Department of Automation, Tsinghua University

Recent Publications

• Yang Yang, Yang Zhang, Bing Ren, Jesse R. Dixon, Jian Ma. (2019). "Comparing 3D genome organization in multiple species using Phylo-HMRF". Cell Systems 8(6):494-505.e14. [pdf] [source code]

  • Early version appeared in Proceedings of the 23rd Annual International Conference on Research in Computational Molecular Biology (RECOMB 2019).

• Shashank Singh, Yang Yang, Barnabas Poczos, Jian Ma. (2019). "Predicting Enhancer-Promoter Interaction from Genomic Sequence with Deep Learning". Quantitative Biology, 7(2):122-137. [pdf] [source code]

• Yang Yang, Quanquan Gu, Yang Zhang, Takayo Sasaki, Julianna Crivello, Rachel J. O'Neill, David M. Gilbert, Jian Ma. (2018). "Continuous-trait probabilistic model for comparing multi-species functional genomic data". Cell Systems 7(2):208-218.e11. [pdf] [source code]

  • Early version appeared in Proceedings of the 22nd Annual International Conference on Research in Computational Molecular Biology (RECOMB 2018).

• Ruochi Zhang, Yuchuan Wang, Yang Yang, Yang Zhang, Jian Ma. (2018). "Predicting CTCF-mediated chromatin loops using CTCF-MP". In Proceedings of the 26th Conference on Intelligent Systems for Molecular Biology (ISMB 2018), Bioinformatics, 34(13):i133-i141. [pdf]

• Yang Yang, Ruochi Zhang, Shashank Singh, Jian Ma. (2017). "Exploiting Sequence-based Features for Predicting Enhancer-Promoter Interactions". In Proceedings of the 25th Conference on Intelligent Systems for Molecular Biology (ISMB 2017), Bioinformatics, 33(14), i252-i260. [pdf] [source code]

• Yue Deng*, Feng Bao*, Yang Yang, Xiangyang Ji, Mulong Du, Zhengdong Zhang, Meiling Wang, Qionghai Dai. (2017). "Information transduction capacity reduces the uncertainties in annotation-free isoform discovery and quantification", Nucleic acids research, 45(15), e143. (*: equal contribution)