CHAO GAN
Fords,New Jersey
Summary
Seeking Quantitative Researcher position that utilizes my expertise in Mathematics, Machine Learning, Statistics and Optimization.
Overview
5
5
years of professional experience
Work History
Manager, Analytics Consultant /
Catalina Marketing
06.2021 - Current
- Getting, Cleaning Data and Extract Features using SQL from historical record order information from Yellowbrick Database
- Used SMOTE (Synthetic Minority Over-sampling Technique) to balance classes and generate synthetic data to train Different model (Random Forest, Neural Network, Logistic Regression etc.) , and use Cross-validation to evaluate predictive models
- To make the model more adaptive to big dataset, use AIC and other methods to reduce the number of features, while maintain the high accuracy
- Developed Predictive Model by Time Series method like ARIMA to predict the future.
- Develop corresponding strategy to promote the sales according to the analysis
Research Assistant
Penn State University
09.2016 - 12.2020
- Worked on topics in machine learning and related application
- Proposed a novel Cost-Aware Cascading Bandits Model, which can be applied to webpage ranking, Recommend Shopping List or any other Recommender System
- Propose CC-UCB Algorithm and prove its optimality in long term rewards
- Investigated non-convex optimization based approaches for beam alignment and tacking in communications.
Education
PhD - Electrical Engineering
Penn State University - - State College
12.2020
Bachelor of Science - Statistics
University of Science and Technology of China
06.2015
Skills
- Machine Learning: Recommender System, Large Scale Reinforcement Learning, Change Point Detection, Classification, Regression, Clustering, Natural Language Processing, Artificial Intelligence, Computer Vision
- Programming Languages: Python, R, SQL, Matlab, Mathematica, C, Excel
- Statistics: Compressed Sensing, Linear Inverse Problems, Time-Series Analysis, A/B testing, Hypothesis Testing, Group Testing
- Optimization: Convex Optimization, Large Scale Linear Optimization, Stochastic Optimization, Non-Convex optimization
- Sales and Marketing: Content Management System, Data Science
- Mathematical calculations: Real Analysis, Complex Analysis, Differential Equations
Accomplishments
Awards
- National Mathematics Competition, 1st Prize
- Outstanding Students, 2012,2014
- Above and Beyond Award, 2022
Publications
Online Learning with Diverse User Preferences
- C. Gan, J. Yang, R. Zhou and C. Shen, IEEE International Symposium on Information Theory (ISIT), Paris, France, July 2019
Cost-aware Cascading Bandits
- R. Zhou, C. Gan, J. Yang and C. Shen, The 27th International Joint Conference on Artificial Intelligence (IJCAI), Stockholm, Sweden, July 2018(Acceptance rate: 710/3470 = 20.4%)
Graph-based Multiple-Line Outage Identification in Power Transmission Systems
- B. Wang, C. Gan, J. Yang, C. Hedge and J. Wu, IEEE PES General Meeting, Chicago, IL, July 2017, Sequential Recommendation Based on Users’ Information Feedback
Projects
Sequential Recommendation for Users
Oct 2018 – Dec 2018
- Based on users’ feedback, develop automatic recommender system to recommend shipping list to the users based on user’s feedback
- By using implicit learning to help maximize the users’ satisfaction, test the algorithm by using data from Kaggle, promote the total users’ satisfaction significantly
Modified CoSaMP for Tree-Structured Sparse System
Feb 2018 – May 2018
- Designed a new algorithm by modifying Compressive Sampling Matching Pursuit algorithm (CoSaMP) to quickly find sparse solution in the tree-structured communication system
- Compared the numerically experiment with classic CoSaMP and other first-order gradient-descent algorithm, our solution can save time over 70% on average
Timeline
Manager, Analytics Consultant /
Catalina Marketing
06.2021 - Current
Research Assistant
Penn State University
09.2016 - 12.2020
PhD - Electrical Engineering
Penn State University - - State College
Bachelor of Science - Statistics
University of Science and Technology of China
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