Chenggang Li

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Education

• 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

Publication

1. 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.

Experience

• 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

Awards

• 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

Past Projects

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.

AutoExavator, 2018
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
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
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

Contact

School Email: chenggan#usc.edu
Personal Email: Execute below command to find out.
openssl enc -base64 -d <<< b3NjYXJ4dml0YUBnbWFpbC5jb20K