Li, Yi ()

I am now an assistant professor in the Divison of Mathematial Sciences at Nanyang Technological University.

Previously, I was a postdoc at Harvard University (supervised by Jelani Nelson), a postdoc at the Max-Planck Institute for Informatics in Saarbruecken, Germany and a research fellow at the Simons Institute for the Theory of Computing.

Email:

Education

2010 - 2013 Ph. D. in Computer Science and Engineering, University of Michigan.
Adviser: Prof. Martin Strauss
2008 - 2010 M. Sc. in Computer Science and Engineering, University of Michigan.
2004 - 2008 B. Eng. in Computer Science (ACM Honoured Class), Shanghai Jiao Tong University.

Papers

Talks (excluding conference presentations)

  • Estimating the Schatten Norms in Streaming Model. NII Shonan Meeting "Processing Big Data Streams", 2017.
  • Improved Sparse Recovery Algorithms. Dagstuhl Seminar 17181 "Theory and Applications of Hashing", 2017.
  • Sublinear-time Algorithms for the Sparse Recovery Problem. Workshop on Sparse Representations & Compressive Sensing, 2017.
  • Estimating the Schatten Norms in Streaming Model. DIMACS Workshop on E+M=C2, 2017.
  • Introduction to the Data Stream Algorithms. Xiamen University, 2016
  • Introduction to the Sparse Recovery Problem. Fuzhou University, 2016
  • Introduction to the Data Stream Algorithms. Math Colloquium, Nanyang Technological University, 2016.
  • Data Streaming Algorithms. MAS Seminar, Nanyang Technological University, 2015.
  • For-all Sparse Recovery in Near-Optimal Time. Theory of Computation Seminar, Harvard University, 2015.
  • A Brief Introduction to the Sublinear-time Sparse Recovery Problem. MPI for Informatics, 2014.
  • Sublinear Fourier Sampling Off the Grid. Workshop on Sparse Fourier Transform, MIT, 2013.
  • Approximate Sparse Recovery: Optimizing Time and Measurements. Minisymposium on Combinatorics and Data Science, Shanghai Jiaotong University, 2011.
  • Approximate Sparse Recovery: Optimizing Time and Measurements. DIMACS Workshop on Network Data Streaming and Compressive Sensing, 2010.
  • Teaching

    Functional Analysis Exercises