I am now an assistant professor in the Divison of Mathematical 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:

- Two
**one-year postdoc**vacancies are available to work on topics related to data stream algorithms, low distortion metric embeddings and randomized numerical linear algebra. The duration of the posts will end before December 2025 with a flexible starting date. Renewals are possible and will be based on performance and the funding situation. Travel support is available. The salary is expected to be 78000 SGD per year. The tax rate in Singapore is low, which is about 4% for the aforesaid salary level. Please contact me if you are interested. - One funded
**PhD student**position is available.The research area is expected to be related to data stream algorithms, low distortion metric embeddings and randomized numerical linear algebra. The anticipated start date is August 2023. If you are interested, please contact me so we can know more about each other. The application deadline is 31 January 2023. Please visit the official website of the Division of Mathematical Sciences for more information of the PhD programme (including how to apply).

Low-distortion metric embeddings

Compressive sensing and signal processing

Theoretical computer science

2010 - 2013 | Ph. D. in Computer Science and Engineering,
University of Michigan. |

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. |

- Cheng Chen, Yi Li, Yiming Sun. Online Active Regression.

arXiv:2207.05945

(This version supersedes, and significantly improves, [C31]) - Yi Li, Honghao Lin and David P. Woodruff. Learning-Augmented Sketches for Hessians.

arXiv:2102.12317 - Yi Li and Mingmou Liu. Higher Lower Bound for Sparse Oblivious Subspace Embeddings.

arXiv:2212.02913

- Zhengyang Guo, Yi Li, and Shaoyu Pei. Expected Size of Random Tukey Layers and Convex Layers.
*Computational Geometry: Theory and Applications*103, Article No. 101856, Apr 2022. pdf - Yi Li, Ruosong Wang, and David Woodruff. Tight Bounds for the Subspace Sketch Problem with Applications.
*SIAM J. Comp.***50**(4), pp 1287--1335, 2021. pdf

(This version supersedes [C19]) - Yi Li and Vasileios Nakos. Sublinear-Time Algorithms for Compressive Phase Retrieval.
*IEEE Trans. Info. Theory*,**66**(11), pp 7302--7310, 2020. pdf

(This paper supersedes, and is radically different from, [C14]) - Yi Li, Huy Le Nguyen, and David Woodruff. On Approximating Matrix Norms in a Stream.
*SIAM J. Comput.*,**48**(6), pp 1643--1697, 2019. pdf

(This version supersedes [C4], [C9] and part of [C11]) - Sudipto Guha, Yi Li, and Qin Zhang. Distributed Partial Clustering.
*ACM Transactions on Parallel Computing***6**(3), pp 11:1--11:20, October 2019. (Special issue on SPAA 2017) pdf

(This version supersedes [C12]) - Anna Gilbert, Yi Li, Ely Porat, and Martin Strauss.
For-all Sparse Recovery in Near-Optimal Time.

*ACM Transactions on Algorithms***13**(3), pp 32:1--32:26, August 2017. pdf

(This version supersedes [C6]) - Petros Boufounos, Volkan Cevher, Anna Gilbert, Yi Li, and Martin Strauss. What's the Frequency, Kenneth?: Sublinear Fourier Sampling Off the Grid.

*Algorithmica***73**(2), pp 261-288, 2015. pdf

(This version supersedes [C2])

Update: A small tweak in the hashing lemma shows that diluting S^1 by*k*/*η*, instead of 1/*η*, would be enough. The sampling duration can be brought down to 1/*η*from*k*/*η*. - Anna Gilbert, Yi Li, Ely Porat, and Martin Strauss. Approximate Sparse Recovery: Optimizing Time and Measurements.

*SIAM J. Comput.***41**(2), pp 436-453, 2012. pdf

(This version supersedes [C1])

- Yi Li, Honghao Lin, and David P. Woodruff. The
*ℓ*-Subspace Sketch Problem in Small Dimensions with Applications to Support Vector Machines._{p}

Proceedings of*SODA*2023, to appear. arXiv:2211.07132 - Yi Li, Honghao Lin, David Woodruff, and Yuheng Zhang. Streaming Algorithms with Large Approximation Factors.

Proceedings of APPROX/RANDOM 2022,*LIPIcs*Vol. 245, pp 13:1--13:23. arXiv:2207.08075 - Cheng Chen, Yi Li, and Yiming Sun. Online Active Regression.

Proceedings of Machine Learning Research 162:3320--3335, 2022. (Proceedings of*ICML*2022)**Long presentation**at ICML 2022. - Yi Li and Mingmou Liu. Lower Bounds for Sparse Oblivious Subspace Embeddings.

Proceedings of*PODS*2022, pp 251--260. arXiv:2112.10987 - Yi Li, Yan Song, and Qin Zhang. Learning to Cluster via Same-Cluster Queries.

Proceedings of*CIKM*2021, pp 978--987. arXiv:2108.07383 - Yi Li and David P. Woodruff. The Product of Gaussian Matrices is Close to Gaussian.

Proceedings of APPROX/RANDOM 2021,*LIPIcs*Vol. 207, pp 35:1--35:22. arXiv:2108.09887 - Yi Li, David P. Woodruff, and Taisuke Yasuda. Exponentially Improved Dimensionality Reduction for
*ℓ*_{1}: Subspace Embeddings and Independence Testing.

Proceedings of Machine Learning Research 134:3111--3195, 2021. (Proceedings of*COLT*2021) arXiv:2104.12946 - Yifei Jiang, Yi Li, Yiming Sun, Jiaxin Wang, and David Woodruff. Single Pass Entrywise-Transformed Low Rank Approximation.

Proceedings of Machine Learning Research 139:4982--4991, 2021. (Proceedings of*ICML*2021) arxiv:2107.07889 - Zhengyang Guo and Yi Li. Geometric Cover with Outliers Removal.

Proceedings of STACS 2021,*LIPIcs*Vol. 187, pp 39:1--39:15. pdf - Alexandr Andoni, Collin Burns, Yi Li, Sepideh Mahabadi, and David Woodruff. Streaming Complexity of SVMs.

Proceedings of APPROX/RANDOM 2020,*LIPIcs*Vol. 176, pp 50:1--50:22. arxiv:2007.03633 - Yi Li, Ruosong Wang, Lin Yang, and Hanrui Zhang. Nearly Linear Row Sampling Algorithm for Quantile Regression.

Proceedings of Machine Learning Research 119:1888--1898, 2020. (Proceedings of*ICML*2020). arxiv:2006.08397 - Yi Li and David Woodruff. Input-Sparsity Low Rank Approximation in Schatten Norm.

Proceedings of Machine Learning Research 119:11124--11132, 2020. (Proceedings of*ICML*2020). arxiv:2004.12646 - Yi Li and Vasileios Nakos. Deterministic Sparse Fourier Transform with an
*ℓ*_{∞}Guarantee.

Proceedings of ICALP 2020,*LIPIcs*Vol. 168, pp 77:1--77:14. arxiv:1903.00995 - Tanqiu Jiang, Yi Li, Honghao Lin, Yisong Ruan, and David Woodruff. Learning-Augmented Data Stream Algorithms.

Proceedings of*ICLR*2020. (No physical publication) Open Review link - Yi Li, Ruosong Wang, and David Woodruff. Tight Bounds for the Subspace Sketch Problem with Applications.

Proceedings of*SODA*2020, pp 1655--1674. arxiv:1904.05543 - Maria-Florina Balcan, Yi Li, David Woodruff, and Hongyang Zhang. Testing Matrix Rank, Optimally.

Proceedings of*SODA*2019, pp 727--746. arxiv:1810.08171 - Yi Li and Vasileios Nakos. Deterministic Heavy Hitters with Sublinear Query Time.

Proceedings of APPROX/RANDOM 2018,*LIPIcs*Vol. 116, pp 18:1--18:18. arxiv:1712.01971 - Yi Li, Vasileios Nakos, and David Woodruff. On Low-Risk Heavy Hitters and Sparse Recovery Schemes.

Proceedings of APPROX/RANDOM 2018,*LIPIcs*Vol. 116, pp 19:1--19:13. arxiv:1709.02919 - Vladimir Braverman, Stephen Chestnut, Robert Krauthgamer, Yi Li, David Woodruff, and Lin Yang. Matrix Norms in Data Streams: Faster, Multi-Pass and Row-Order.
*Proceedings of Machine Learning Research*80:648-657, 2018. (Proceedings of*ICML*2018) arxiv:1609.05885 - Yi Li and Vasileios Nakos. Sublinear-Time Algorithms for Compressive Phase Retrieval.

Proceedings of*ISIT*2018, pp 2301--2305. - Yi Li and David Woodruff. Embeddings of Schatten Norms with Applications to Data Streams.

Proceedings of*ICALP*2017, pp 60:1--60:14. pdf - Sudipto Guha, Yi Li, and Qin Zhang. Distributed Partial Clustering.

Proceedings of*SPAA*2017, pp 143--152. Co-winner of the**Best Paper award**. - Yi Li and David Woodruff. Tight Bounds for Sketching the Operator Norm, Schatten Norms, and Subspace Embeddings.

Proceedings of APPROX/RANDOM 2016,*LIPIcs*Vol. 60, 39:1--39:11. arXiv:2202.09797 - Yuqing Ai, Wei Hu, Yi Li, and David Woodruff. New Characterizations in Turnstile Streams with Applications.

Proceedings of*CCC*2016, pp 20:1--20:22. pdf - Yi Li and David Woodruff. On Approximating Functions of the Singular Values in a Stream.

Proceedings of*STOC*2016, pp 767--780. - Yi Li, Xiaoming Sun, Chengu Wang, and David Woodruff.
On The Communication Complexity of Linear Algebraic Problems in the Message Passing Model.

Proceedings of*DISC*2014, pp 499--513. Full version: arxiv:1407.4755 - Yi Li, Zhengyu Wang, and David Woodruff. Improved Testing of Low Rank Matrices.

Proceedings of*SIGKDD*2014, pp 691--700.**One of nine best papers.** - Anna Gilbert, Yi Li, Ely Porat, and Martin Strauss.
For-all Sparse Recovery in Near-Optimal Time.

Proceedings of*ICALP*2014,*LNCS*8572, pp 538--550 - Yi Li, Huy Le Nguyen, and David Woodruff. Turnstile
Streaming Algorithms Might as Well Be Linear Sketches.

Proceedings of*STOC*2014, pp 174--183. pdf - Yi Li, Huy Le Nguyen, and David Woodruff. On Sketching
Matrix Norms and the Top Singular Vector.

Proceedings of*SODA*2014, pp 1562--1581. - Yi Li and David Woodruff. A Tight Lower
Bound for High Frequency Moment Estimation for Small
Error.

Proceedings of APPROX/RANDOM 2013,*LNCS*8906, pp 623--638. pdf of full version - Petros Boufounos, Volkan Cevher, Anna Gilbert, Yi Li, and
Martin Strauss. What's the Frequency, Kenneth?: Sublinear
Fourier Sampling Off the Grid.

Proceedings of APPROX/RANDOM 2012,*LNCS*7408, pp 61-72. - Anna Gilbert, Yi Li, Ely Porat, and Martin Strauss.
Approximate Sparse Recovery: Optimizing Time and
Measurements.

Proceedings of*STOC*2010, pp 475-484.

- MOE AcRF Tier 2. Feb 2023 -- Jan 2026. Amount awarded: 489,600 SGD. (to be finalized)
- MOE AcRF Tier 1. Mar 2022 -- Aug 2024. Amount awarded: 189,000 SGD.
- MOE AcRF Tier 2. Jan 2019 -- Mar 2022. Amount awarded: 453,060 SGD + 140,000 SGD for 1 scholarship.

- At Nanyang Technological University
- MH1812. Discrete Mathematics.
- Autumn 2020*, 2021*, 2022*. (* denotes co-teaching with Jian Guo)
- MH2500. Introduction to Probability and Statistics.
- Autumn 2017*, 2018*, 2019. (* denotes co-teaching with Chan Song Heng)
- MAS723. Topics in Probability and Statistics I: Probability in High-dimensional Spaces
- Spring 2017, 2018, 2019, 2020, 2021, 2022, 2023.
- MH2401. Algorithms and Computing III.
- Autumn 2016. (co-teaching with Fedor Duzhin)
- At Shanghai Jiaotong University
- Summer 2018, 2021, 2022. Probability and Computing.

- Conference programme committee: ISAAC'18, FOCS'20, RANDOM'21
- Editor of the SICOMP special issue for FOCS'20
- Workshop organizer:
- May-June 2022. Algorithms and Foundations for Data Science at NUS-IMS. (co-organizing with David Woodruff)