Product demand forecasting

Data transfer, machine learning modeling, migration.

• Designed and implemented AI applications using encoder-based Large Language Models (LLMs) like Clinical BERT, effectively training and fine-tuning for Named Entity Recognition (NER) within healthcare data, which led to accurate ICD-9 code extraction from patient notes.

• Developed a FastAPI backend paired with a React frontend, incorporating AWS DynamoDB for data storage and retrieval. Utilized OpenAI GPT to auto-generate Python functions from MIPS rule files, enabling real-time patient rule verification.

• Designed a React frontend and FastAPI backend to construct a chatbot utilizing OpenAI's GPT API. This chatbot efficiently schedules doctor appointments and can answer patient-specific questions like copays or patient’s functional scores based on integrated patient files.

• Built the susceptible-exposed-infected-recovered (SEIR) model via Python to predict the Covid-19 cases. Developed C19 Explorer platform and C19 Vaccine tool.

* 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