Suri (Suyu) Chen Email & Phone Number

New York, United States

Purchase, New York, Us

Purchase, New York, Us

Purchase, New York, Us

Purchase, New York, Us

New York, Ny, Us

Tw

• Collected 1 million data of ICO fundraising, supply, social media news, historical price from different websites. Perform data cleaning by Python Pandas, Numpy and Scipy.• Conducted the hypothesis test to analyze features significances, such as team member, white paper and geographical data.• Predicted cryptocurrency project ROI before its release using extreme Gradient Boosting Model (Python XGBoost)

• Created a Machine Learning Model with a high dimensional dataset to predict the gross revenue of up-coming movies for investment. Achieved more than 90% accuracy in both training and test data.• Used Python web scrapping to collect data of more than 30 features from 5 websites. • Designed, validated and tested multiple classification models (Logistic Regression, SVM, Random Forest, Gradient Boosting etc.). Used Lasso and PCA to screen out insignificant indicators.• Built data report for clients including data visualization, interpreted the indicators analysis, predicting results and made the recommendations.

Bonn, Nrw, De

• Maximized profits for DHL service center by optimizing the work flow process. Re-engineered and enhanced the inbound sorting process, decreased sorting time by 48%.• Utilized Python and R to extract, clean and analyze data. Identified key problems and generated interpretable data report for multifunctional team based on recorded and processed data.• Increased quality of customer service by the development of a customer service management dashboard. Enabled center to analyze the customers behavior by data visualization and deliver customized service.

Xiamen, Fuj, Cn

Worked in different offices under the port operations department, hand on experience in Operations, Berth planning, Yard planning, and Empty Container planning

Hsinchu, Taiwan, Tw

Research in the decision of green traffic signals time preventing the Braess' paradox-Worked with Professor Cho () in calculating the green traffic signal time that prevents the Braess' paradox-In real life, a new transportation construction project will often lead to the Braess' paradox, our mission is to minimize the system cost, which is estimated by a formulation related to the time of the green signal, by balancing the user equilibrium and system optimization.-In this Algorithm, multiple sub-projects are involved: DSF method to generate the OD matrix, Label Setting Algorithm to simulate the shortest path routes and Frank-Wolfe algorithm to solve the equilibrium arc flow, and Tobin's model to calculate sensitivity.-Conducted Frank-Wolfe algorithm test by using C++ and Matlab

Master Of Science - Ms, Operations Research

Exchange, Business Administration, Management

Bachelor Of Science - Bs, Transportation And Logistics Management