Product demand forecasting

Data transfer, machine learning modeling, migration.

* Built deep convolutional neural network to estimate age, gender, emotion of drivers and passengers

* Used detected features of customers in-camera as cold starts to build a news feed application

* Predicted the city-level car sales volume based by use of different time series models

* Stored the car testing data into Big table on google cloud platform and tested the robustness of big data lake system

* Designed efficient A/B testing frameworks which involved collaboration network and bucket imbalance problems

* Retrieved relevant articles of protein-protein interaction (PPI) from BioGrid database via python language.

* Built deep convolutional neural network to determine which sentences contain information of PPI and aim to find new interactive protein pairs

Finished Courses: Introduction of Financial Math, Financial Engineering, Measure and Integrity, Investment, Computational Finance，Monte Carlo Method and so on

Passed qualify exams: complex analysis I and II, Monte Carlo method, PDE I