PhD Student @ JHU CS

Jun 2016 I will give a talk at NSF Algorithm in the Field Workshop for Software-defined Networking

May 2016 CS@JHU and UMD are hosting 2016 Capital Area Theory Day, please register to attend.

May 2016 UnivMon work to appear in SIGCOMM'16

Apr 2016 I will attend AT&T Research Academic Summit. Rethinking Network Flow Monitoring (Update: Best Poster Award)

Oct 2015 Universal Monitoring framework accepted to HotNets'15

Hi! I am currently a PhD student in Computer Science at Johns Hopkins University working with Prof. Vladimir Braverman. Prior to JHU, I got my B.S. degree from Southeast University.

My research interests include streaming algorithms, sublinear algorithms for 'big data', practical systems and algorithms for computer networks. In particular, I have broad interests in Software-defined Networking and Network Function Virtualization.

New Bounds for the CLIQUE-GAP Problem using Graph Decomposition Theory

Vladimir Braverman, **Zaoxing Liu**, Tejasvam Singh, N.V. Vinodchandran and Lin Yang

Full version in Algorithmica 2017

One Sketch to Rule Them All: Rethinking Network Flow Monitoring with UnivMon

**Zaoxing Liu**, Antonis Manousis, Greg Vorsanger, Vyas Sekar, Vladimir Braverman

In Proc. of ACM SIGCOMM 2016

GPU Accelerated Streaming Algorithms for Halo Finders

Preprint

Enabling a "RISC" Approach for Software-Defined Monitoring using Universal Streaming

**Zaoxing Liu**, Greg Vorsanger, Vladimir Braverman, Vyas Sekar

In Proc. of ACM HotNets 2015

Streaming Algorithms for Halo Finders

**Zaoxing Liu**, Nikita Ivkin, Lin F. Yang, Mark Neyrinck, Gerard Lemson, Alexander S. Szalay, Vladimir Braverman, Tamas Budavari, Randal Burns, and Xin Wang

In Proc. of IEEE eScience 2015

New Bounds for the CLIQUE-GAP Problem using Graph Decomposition Theory

Vladimir Braverman, **Zaoxing Liu**, Tejasvam Singh, N.V. Vinodchandran and Lin Yang

In Proc. of MFCS 2015

Faster big data processing system

Universal monitoring system based on programmable switches

Clustering for Massive Datasets and Applications (project webpage)

Efficient streaming algorithms for analyzing high dimensional data from cosmological simulation

600.463 Introduction to Algorithms/Algorithms I.

Office Hours: 9:30-11:00am Friday, Malone 239.

Notice: We are using Gradescope. Please contact me for entry code if you currently don't have the course access. For course related discussions, we use Piazza.

Material:

HW2 [PDF, LaTex, Brief Sol], due on 5pm, 2/14/2017 via Gradescope (now extended to 2/17/2017)

HW5 [PDF, LaTex, Brief Sol], due on 11:59pm, 3/18/2017 (now extended to 3/20/2017)

HW6 [PDF, LaTex, Brief Sol], due on 11:59pm, 4/06/2017 (now extended to 4/07/2017)

Quiz 1 [Brief Sol]

Quiz 2 [Brief Sol]

Extras - Johnson and Lindenstrauss[Paper]

For fun (please ignore):

This course is about the analysis of algorithms. However, for those who are interested, I will irregularly post some interesting (at least I think interesting) coding problems here. Just for fun. Explanations or solutions are not guaranteed though :)

"Who Wins the Election?" [txt]

Email: zaoxing AT jhu.edu

Secure Email Welcome >> GPG key