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- July. 2019 - Current, Ph.D Student in Computer Science at University of Southern California.
- Jun. 2018 - Aug. 2018, Summer Session at Stanford University.
- Feb. 2017 - Feb. 2018, Full Gap Year at Microsoft Research.
- Sep. 2015 - 2019(Gap year included), Bachelor of Engineering in Computer Science and Technology, Northeastern University, Shenyang
- Oct. 2014 - Aug. 2015, Digital Media and Technology, Northeastern University, Shenyang
Predicting Node Failure in Cloud Service Systems, Qingwei Lin et al. FSE/ESEC 2018.
In recent years, many traditional software systems have migrated to cloud computing platforms and are provided as online services. A cloud service system typically contains a large number of computing nodes. In reality, nodes may fail and affect service availability. In this paper, we propose a failure prediction technique, which can predict the failure-proneness of a node in a cloud service system based on historical data, before node failure actually happens. The ability to predict faulty nodes enables the allocation and migration of virtual machines to the healthy nodes, therefore improving service availability.
Cross Platform UI Test Migration. In submission to ASE 2021
- Incoming Ph.D. SDE Intern at eBay. 2021.5- 2021.8
- Teaching Assistant, University of Southern California. 2021.1-Current
- Research Assistant, University of Southern California. 2019.7- 2020.5
- Research Intern, Beijing BizSeer Technology Co., Ltd. 2019.1-2019.6
- Research Intern, Beijing iRootech Technology Co., Ltd 2018.9-2018.12
- Visiting Student at UIUC, Automated Software Engineering Group, Prof. Tao Xie. Aug. 2018 - Oct. 2018,
- Research Intern, Microsoft Research, Feb. 2017 - Feb. 2018
- Microsoft Ability Bootcamp at Redmond Campus, Microsoft, Jan 2017
- Annenberg Fellowship, University of Southern California
- SIGSOFT CAPS Award, ACMSIGSOFT, Sep 2018
- MSRA Star of Tomorrow Award at Microsoft Research, Jan 2018
- Dean's List (1 of 10 awarded schoolwise), Northeastern University, Mar 2017
- Ability Award at Microsoft Imagine Cup World Final, Aug 2016
- Grand Prize Winner of Microsoft Imagine Cup China 2016 (World Citizenship), Apr 2016
- Star of Innovation and Entrepreneurship, Northeastern University, 2014 & 2015 & 2016
- Grand Prize- 11th Up-Tech Cup National College Student Embedded System Design Regional Contest, 2014
Research & Projects
Cross Platform UI Test Migration (Ongoing, Co-author), 2020-2021
Novel approach for bidirectional transfer of usage-based tests across different mobile platforms, with no source code required on either platform.
Our approach takes as input the binaries of the app-under-test written for both iOS and Android, as well as the existing tests for one of these platforms, and automatically generates such tests for the corresponding app on the other platform.
Anomaly Detection and Log Analysis, Spring 2019
Worked as an research intern at Beijing Bizseer Technologies to develop Deep learning based Anomaly Detection and Log Analysis Algorithms to help major commercial banks in china find out Anomaly in daily data and uncover root cause from massive heterogeneous data and log reports of their complex softwares and critical IT infrastructure.
As enterprise IT systems growing larger in size, there has been increasing complexity, large amount of log data, and emerging failures of all kinds. The difficulty of ensuring efficient and reliable operation of systems has increased dramatically. Anomaly Detection has been widely used in monitoring
infrastructure, however using static filter in Anomaly Detection cause a lot of false positives to be reported and could not handle the case of off hours and holidays.
- Worked on log-based anomaly detection and alert clustering for several major banks' infrastructure (China Construction Bank, etc) in China.
- Designed algorithms that handles problems in anomaly detection such as spikes on Holidays, finding Periodic patterns.
- Implemented a Tokenization method for Chinese Log Parsing and Alert clustering.
AutoExavator is an R&D project in iRootech Technology Co., Ltd and SANY, which enables autonomous driving and construction for heavy equipment
Azure Capacity Management at Microsoft Research Asia, 2017-2018
Predict capacity days-to-exhaustion and Develop Buffer Capacity Management strategy to reserve the empty node/core buffer to fit the tenant upgrade needs.
- Use machine learning to predict days-to-exhaustion.
- Work on feature engineering and data preprocessing.
Compute and Storage Node Fault Prediction for Cloud Platforms, 2017
Proactive downtime prediction: our node fault and hardware fault prediction service can proactively reduce VM downtime, through guiding new VM allocation and removing risky nodes from rotation. Validation result shows our prediction technology can add 10+% more node fault reduction on top of existing advanced allocation strategy. The top 1,000 nodes with disk failures we predicted causes 21K+ min VM downtime within a month.
- Co-authored a Paper: Predicting Node Failure in Cloud Service Systems accepted at FSE/ESEC 2018.
- Work on Data Analytcis, and developed an effective ensemble model for production.
- Carried out all experiments and evaluated using different models (i.e. DF,DNN and RNN) on the dataset.
- Developed and Maintained tool chains for Machine Learning
- Improved Azure VM availability (reduced downtime) for Compute Node Failure Prediction.
BoneyCare is designed to help people with speech disorders improve their confidence and speaking quality. The App records, transcribes and analyzes a users speech patterns, which speech pathologists can then use to improve and accelerate their diagnoses and treatment plans. This project is a collaboration between 2nd year computer science students from two Chinese universities and UC Berkeley.
- First App targeting stutter with cloud-based machine learning, voice recognition, wave analysis, and emotion recognition technology.
- Provide a new way to help speech pathologists connect and track their patients status.
- help people with speech disability learn, communicate, improve confidence and speaking quality.
- Grand Prize Winner at Imagine Cup 2016 China.
- Ability Award Winner at Imagine Cup World Final
LightItUp is a hackathon solution based on MITM(man-in-the-middle) attack that helps late-owl students gain access over their dorm electricity meter and bypass enforcement of dorm electricity off after 23:00.
- Sucessfully gained remote control of school electricity command and control device.
- Conducted Proof Of Concept Attack and controlled 30s of black out across the whole dorm building
School Email: chenggan#usc.edu
Personal Email: Execute below command to find out.
openssl enc -base64 -d <<< b3NjYXJ4dml0YUBnbWFpbC5jb20K