Chenggang Li
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Education
- Jun. 2019 - Current, Ph.D Student 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 in Computer Science and Technology, Northeastern University, Shenyang
- Oct. 2014 - Aug. 2015, Bachelor in Digital Media and Technology, Northeastern University, Shenyang
Publication
- Predicting Node Failure in Cloud Service Systems, Qingwei Lin et al. FSE/ESEC 2018.
Experience
- Research Intern, Beijing BizSeer Technology Co., Ltd.
- Research Intern, Microsoft Research, Feb. 2017 - Feb. 2018
- Member of Microsoft Student Partner(MSP) Leader Team in China.
Awards
- SIGSOFT CAPS Award, ACMSIGSOFT, Sep 2018
- MSRA Star of Tomorrow Award at Microsoft Research, Jan 2018
- Principal Medal(1/10), 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, 2014 & 2015 & 2016
- Grand Prize- 11th Up-Tech Cup National College Student Embedded System Design Regional Contest, 2014
Research & Projects
Past Projects
AutoExavator
AutoExavator is an R&D project in iRootech Technology Co., Ltd, which enables autonomous driving and construction for heavy equipment
NL to SQL(In collaboration with UIUC Prof.XIE)
Ongoing Project on researching and exploring better approach on NL2SQL.
Azure Capacity Management at Microsoft Research Asia
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
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.
- Carried out all experiemnts and evaluated using different models (i.e. DF,DNN and RNN) on the dataset.
- Developed and Maintained Toolchains 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 electicity 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
Email: oscarxvita#gmail.com
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