Research Projects

Probabilistic programming languages and Bayesian inference

• Bayesian Logic (BLOG) and its inference system.

Time series learning

• Intracranial modeling
• Human motion and motion capture analysis (finished) natural motion stitching
• data center monitoring (finished)
• Tensor time series

Parallel/Distributed machine learning

• Parallel algorithms for graphical model on multicore : (finished)

Network analysis

• social network and social media analysis
• CDEM :fly embryo gene pattern mining. (finished)

Talks and Tutorial

• EMNLP 2019 Tutorial on Discreteness in NLP.
• CCF-ADL107/NLPCC 2019 Tutorial on Deep Generative Models for Text Generation.
• BLOG language and compiled inference. Computer Science department, Stanford University, Tsinghua University, 2015.
  
• 2015 Invited Keynote at China Computer Federation Young Computer Scientists and Engineers Forum: Deep Learning – Towards More Intelligent Machines.
  
• 2014 PPAML Summer School, lecture on BLOG .
• 2013 TAMU Fish Bowl Seminar
• KDD 2010 Tutorial on Time Series
• Parsimonious Linear Fingerprinting for time series, Machine learning lunch seminar, CMU, Nov, 2010. [ PPT ]
  
• Fast Algorithms for Mining Co-evolving Time Series. SMU, NUS, SJTU, Dec 2009. [ PPT ]
• Fast Algorithms for Mining and Summarizing Co-evolving Sequences, HKUST. 2009.[ Poster ]
• Machine Learning Lunch seminar, CMU, Oct 6, 2008. [ PPT ]