ac8zyy@r.postjobfree.com Yuxi Jiang

linkedin.com/in/yuxi-jiang-130509166/

857-***-**** youtube.com/channel/UCxDjgnY67DSPwjNRInU0IiA 1079 Commonwealth Ave apt 416 Boston MA Github.com/jiangcici Summary

Seeking a full-time software engineer position. Strong experience in web application development, machine learning, mobile application development, image processing and cloud computing. Skilled coding in Java, Python, MATLAB, C# and Go. Quick learner and good at both teamwork and individual work. Education

Boston University, Boston, MA

Master of Science, Electrical and Computer Engineering Sep 2017 – Jan 2019

Beijing Institute of Technology, Beijing, China

Bachelor of Science, Automation

Study Abroad: ESIEE – Amiens, Amiens, France

Sep 2013 – Jun 2017

Mar 2017 – May 2017

Related Courses: Data Structures and Algorithms, Object Oriented Programming, Cloud Computing, Fundamentals of Computer Engineering, Deep Learning, Machine Learning, Client-server Software System, Advanced Image Processing Project Experiences

Around: A Geo-index based social network - Go Web Service and Google Cloud Front End:

̈ Used React JS framework to implement an interactive web, with features such as “Create Post”, “Nearby Posts as Gallery” and “Nearby Posts in Map” with Ant Design, Geo-Location API and Google Map API. ̈ Implemented basic token-based authentication (registration, login and logout) flow with React Router v4 Back End:

̈ Built a scalable web service in Go to handle posts and deployed to Google Cloud (GAE flex) for better scaling ̈ Utilized ElasticSearch (GCE) to provide geo-location-based search functions such that users can search any location nearby posts within certain distance (e.g. 200km)

̈ Used Google Dataflow to build a daily dump pipeline that reads data from BigTable and Write to BigQuery table for offline analysis

̈ Leveraged Google Cloud ML API and TensorFlow to train a face detection model and integrated with Go service Ticket+: Event Search and Ticket Recommendation - Java Web Service Development Front End:

̈ Developed an interactive web application for users to search events (HTML, CSS and JavaScript) ̈ Improved personalized business recommendation based on user’s search history and favorite records Back End:

̈ Created Java servlets with RESTful APIs to handle HTTP requests and responses ̈ Built relational and NoSQL databases (MySQL, MongoDB) to capture real business data from Ticketmaster API ̈ Designed algorithms (e.g., content-based recommendation) to implement business recommendation Outlier Color Identification for Search and Rescue - Image Processing ̈ Developed an outlier color detection algorithm that can identify significantly different colors (2 x 2 pixel) from a still image (1200 x 1200 pixel) which represents forest, ocean or desert ̈ Made use of three Algorithms, which are Chrominance, Reed-Xiaoli Detector and DWEST (Dual Window-based Eigen Separation Transform), to develop three detectors and compared their performance ̈ Converted the RGB image to LAB color space and calculated detection result based on three algorithms, compared the result to threshold to decide whether it is an outlier Smart Wardrobe: Outfit Recommendation mobile Application - iOS Development and Machine Learning ̈ Designed an iOS application (XCode, Swift) which could recognize the category of clothes updated by the user and save the clothes’ information to the local database (MySQL) ̈ Trained a machine learning model using CNN (convolutional neural network) to recognize clothes categories ̈ For each category (including T-shirt, jacket, trousers, dress, coat and short), used 500 images as training data and 50 images as testing data and achieved an accuracy of 90.2% ̈ Achieved the function of recommending the outfit of today by picking clothes randomly from user’s local database according to the daily temperature got from Yahoo weather Skills

Programming Language Java, Python, Go, C#, HTML, React, JavaScript Software and tools Google cloud, AWS, MATLAB, Android Studio, XCode, Eclipse, IntelliJ, MySQL, MongoDB Data Science Supervised and unsupervised learning, Reinforcement learning, Data preprocessing