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COURSE PROJECTS
Professional Summary
Solid mathematical foundation and programming skills. Quickly master new software packages and hardware technologies. Have research and working experience on deep learning & artificial intelligence.
Education
Current
Bachelor of Science: Eletrical Engineering
Stanford University - City, State
Stanford University - City, State
- 3.8 GPA
2015
Bachelor of Science: Physics
Peking University - City
Peking University - City
- Recipient of Undergraduate Reasearch Award(2015), Sumitomo Scholarship(2013), Weiming Scholarship(2013,2014), Social Work Award(2013)
Work History
09/2016 to 12/2016
Course ProjectsStanford – City , STATE
- CS221 Artificial Intelligence: Deep Q-learning/ Q-learning agent for a scrolling shooter game.(Highest Score Project) I realized a Deep Q-learning platform on caffe.
- CS229 Machine Learning: Vehicle detection and model recognition. Used Faster-RCNN for car detection and feature extraction. Applied KNN for model recognition.
03/2016 to 08/2016
R&D Engineer(intern)SenseTime – City
- Built a training system for Xiaomi on-line face recognition service.To protect users' information, all the images for training are encrypted. This system decrypted images, cropped out faces and trained the network.
- Research on Faster-RCNN and SSD for self-driving car(traffic signs and small objects detection). Improved the Mean Average Precision by about 20%.
09/2015 to 02/2016
Research assistant, Advosor Prof. Yizhou WangLab Of Video Technology, School Of EECS – City , STATE
- Directly learned an end-to-end deep deconvolution neural network between low/hight-resolution images to achieve image Super-Resolution.(state-of-art)
- Used fast R-CNN to achieve cars detection in aerial and satellite images.
- Build a Bidirectional Recurrent Convolution Network for Multi-Frame Super-Resolution.
06/2014 to 08/2014
Research Assistant, Advisor Pro. Constance Chang-hasnainDepartment Of EECS, University Of California, Berkeley – City , STATE
- Simulation and analyzed the mode in the Nano-laser grown on silicon substrate
- Designed the cavity to achieve high Q factor and high coupling efficiency to the output waveguide
Skills
| Machine Learning/ Deep Learning Computer Vision/ Natural language Processing Solid mathematical background Pick up everything quickly with google |
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Resume Overview
School Attended
- Stanford University
- Peking University
Job Titles Held:
- Course Projects
- R&D Engineer(intern)
- Research assistant, Advosor Prof. Yizhou Wang
- Research Assistant, Advisor Pro. Constance Chang-hasnain
Degrees
- Bachelor of Science : Eletrical Engineering
Bachelor of Science : Physics
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