Li, Yi ()

I am an assistant professor in the Divison of Mathematical Sciences of the School of Physical and Mathematical Sciences at Nanyang Technological University.

Office: SPMS-MAS-05-17
Postal address:

Division of Mathematical Sciences
Nanyang Technological University
SPMS-MAS-05-17, 21 Nanyang Link
Singapore 637371

Email: yili@nt?.edu.sg, where ? represents exactly one character.

Previously, I obtained my PhD from University of Michigan in 2013, under the supervisor of Martin Strauss. Afterwards I was a postdoc at the Simons Institute for the Theory of Computing, Max-Planck Institute for Informatics and Harvard University (supervised by Jelani Nelson).

Research Interests

Papers

Teaching

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
  • 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.
  • Miscellaneous

    Functional Analysis Exercises