JIAHONG XUE

EDUCATION AND CERTIFICATES

Coursera Certificate, Deep Learning and Neural Networks Mar 2019

• Link of Credential: http://bit.ly/2GoTwr2

University of Pittsburgh, Master of Library and Information Science GPA: 3.78 Dec 2018

• Data Stewardship

Michigan State University, BS in Physics May 2017

• Minored in Mathematics, Computer Science

TECHNICAL SKILLS

• Programming: SQL/MySQL, Python, PHP, C++, R, JavaScript.

• DBMS: Database Management, Lock and Recovery, Performance Optimization, Query Optimization.

• Data Science: Data Analytics, Data Mining, Machine Learning, Deep Learning and Neural Networks, NLP, Visualization, ETL, Pandas, TensorFlow, Matplotlib, Hadoop Hive, Spark, HBase, Keras, Tableau, Django. WORK EXPERIENCE

Deep Learning Intern at CTI-ONE Corp. May 2019 – present

• Prepared dataset and annotations for object detection, and trained with Yolov2, Yolov3 and VGG19.

• Algorithm design for autonomous driving path planning and object recognition.

• Redesigned existing UI with Django for computer vision detection functions.

• Developed database application for facial recognition system. Designed multiple UI for different group of users with different authorities.

• Wrote an API for facial recognition functions request, parameter setting, face database interaction, etc. Data Analyst remote Intern at Unibit, Inc. May 2019 – June 2019

• Web Scrapping and Crawling on financial and commercial data.

• Used sentiment analysis to filter out data that are ads. ACADEMIC PROJECTS

Data Analytics - Analysis on Gaming Data-Clash Royale Deck Analysis May 2018 – present

• Analyzed over 500K rows(5G) of JSON data with Python pandas scikit-learn and visualized with matplotlib.

• Data collected with clashroyale API. Data cleansing and built a pipeline to facilitate future ETL process.

• Transformed cleaned deck data into one-hot matrix for training.

• Trained a model to predict winner by deck information.

• Conducted classification models including Bayesian Network, Random Forest, Neural Networks.

• Link: https://github.com/JiahongXue/Clash-Royale-Card-Usage-Analysis Convolutional Neural Network: Object Detection with YOLOv2 Mar 2019

• Implemented YOLOv2 to detect objects with bounding boxes in streaming video with Keras and TensorFlow.

• Implemented non-max suppression to select the objects in the outputs with their probability scores.

• The algorithm can run in real time streaming videos for object detection. The resulting videos will show objects with their bounding boxes and the probability score associated. Data Mining – Predict the profitability of a movie making Feb 2018 – Apr 2018

• Trained a Random Forest Classifier in Python to classify movies’ profitability. (profitable and non-profitable)

• Conducted correlation analysis to select most relevant features.

• Dealt with imbalanced outputs between positive and negative cases, by taking macro-precision as our evaluation parameter. And the macro-precision of the model was at 0.69.

• The model gives movie makers an idea whether the movie is going to be profitable before filming. Database application - Online bookstore implementation Jan 2018 – May 2018

• Developed an e-commerce bookselling website, used JavaScript for frontend and Java for backend API.

• Implemented AJAX HTTP request to query data from front end to backend.

• The website’s functionality includes: browsing, searching and filtering, account system, virtual purchasing ready.

• Used aggregation function to achieve “top selling books over last week” query.

• The resulting website is extensible and can be modified for other e-commerce business. Phone: 517-***-****

ac96wp@r.postjobfree.com

1375 Lick Ave. Apt 522

San Jose, CA, 95110

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