中文版

Zihui Liu (刘梓晖)

Guangzhou, China
Email: kingiw@hotmail.com

Education

August 2016 - June 2020
Sun Yat-Sen University,
Undergraduate Major: Computer Science and Technology
GPA: 4.2 Rank: 3/212

Scholarship

National Scholarship(2017), First Prize Scholarship(2017, 2018), Second Prize Scholarship(2019).

Selected Courses

Probability and Statistics(100, rank1), Data Structures and Algorithms(98, rank1), Advanced Algebra(97, rank1), Principles of Artificial Intelligence(99), Principles of Operation Systems(97), Mobile Internet Programming Project(97), Mathematical Analysis(95), Parallel and Distributed Computing(93), Principles of Computer Organization(93)…


Research Interest

I have broad fields of interests, including but not limited to cybersecurity, HPC, distributed systems, data mining and computer vision. I am glad to participate in the research and development of any fields related to computer science.


Personal Experience

July 2019 - Present

Full-time intern at Microsoft Research Asia, supervised by Yang Luo and Yongqiang Xiong. My work mainly focuses on:

  • Developing a web-based platform that facilitates the collection, logging, analysis and visualizaition of human mouse and touch behaviors in webpages. The project is based on Beego and React, and it has been open-sourced. Link
  • Research on network bot detection algorithm and bot behavior analysis. Including: (1) Validity check for HTTP/HTTPS requests header fields. (2) Use machine learning methods to unearth regular patterns for bot network traffic. (3) Maintaining a few Bot-Detection module in Azure Front Door Service.
  • Developing a module, based on Azure Cosmos DB, to extract and preprocess targeting fields in daily network traffic data. This module has been ported to the internal data streaming pipeline.

May 2019 - June 2019

Participated in ISC-Student Cluster Competition and got Achievement Award. I was responsible for increasing the training efficiency by utilizing Horovod and deploying Tiramisu exscale cimate analytics deep model on multi-node server. I also enhanced the prediction accuracy via minor modification on the model. (Supervisor: Prof. Yunfei Du)

Feb. 2019 - Apr. 2019

Worked as a research assistant in Tianhe-2 Center. Participated in Asia Student Supercoputer Challenge and won the First Prize (Rank 3 in total scores), ePrize(Best CESM Performance), Group Application Prize(Best Fluidity performance). I mainly focused on using deep models to increase the perceptual index in the single image super-resolution challenge, and the compilation optimization and deployment of Fluidity. I was also involved in other scientific applications’ optimization and deployment on multi-node server. (Supervisor: Prof. Yunfei Du)

Oct. 2018 - June 2019

Worked as a student research assistant in Intelligence Science System Lab(ISEE) in SYSU, supervised by Prof. Weishi Zheng. I participated in the following two research fields:

  • Person and group re-identification via DNN.
  • Lightweight deep networks.

June 2018 - Oct. 2018

Developed a web-based project, CO-RAD, for synthetic biology community. The application has powerful functionalities including synchronous presenting board, visualizing canvas for bio-circuit construction, support for transmitting and storing SBOL format data and a search engine for syn-bio information. I worked as a web full-stack developer. The project was awarded with silver medal in software track of the International Genetically Engineered Machine (iGEM 2018). Link

Coursework Project

MIPS single- and multi-cycle processor on FPGA. (FPGA, Verilog)
Online file storage and sharing system. (Express, MySQL, Semantic UI)
Parallel optimization for Canny operator. (SIMD, MPI, OpenMP)
Chat room in Unix terminals. (C socks programming)
Route system for Guangzhou metro. (Qt, C++)
Simple recommendation system based on collaborative filtering. (Hadoop in Python)
Public discussion platform for Online Judge. (Django, Sqlite3, Bootstrap)


Technical Skills

  • Proficient in web full-stack development. Familiar with Android application development.
  • Proficient in diverse machine learning algorithms and classic deep models. Proficient in some deep learning frameworks like Tensorflow and Pytorch.
  • Good at parallel computation(SIMD) and distributed systems. Familiar with GPU programming.
  • Experienced in both Linux and Windows .NET environments. Proficient in Git.
  • Programming language: Proficient in Python, Javascript(ES6 & CommonJS), C#, C++, Golang, familiar with C, Typescript, Java and some database query languages. Experienced in functional programming.