Successfully manage NLP project alone, using NLP method manipulate unstructured medical pathological data into a structured format. Using regular expression, TD-IDF and HMM on segmenting and organizing text data into meaningful entities. Design and train the Bi-LSTM model to classify entities into structured format. Using Ensemble Methods, cross-validation and Hyperparameter Tuning to optimizing model to achieve 90% Recognition Rate. Evaluated the model with different metrics such as precision, recall, F1-score, and accuracy. Validate the model's robustness by testing it on different dataset. Assist physicians in designing clinical trials and conducting follow-ups. Applied CDISC standards to ensure the compliance and integrity of clinical trial data. Conducted statistical analysis on Phase IV clinical trial data, providing valuable insights to support decision-making processes. Designed and maintained databases for clinical trial data, optimizing data accessibility and usability for research purposes. Developed statistical models and methodologies to analyze healthcare data by using SAS, R, Python. Implement medical data mining, such as conducting Moving Epidemic Method analysis incorporating internet data, Organ Transplant Willingness META analysis, and Transplant Rejection BLAST analysis based on transcriptomic data. Collaborating with multiple departments, develop a medical data governance model involving the development of a large data warehouse utilizing ROLAP and data pipeline development, as well as metadata management.

Participate in pre-research for scientific projects on knowledge graphs and intelligent question-answering systems, utilizing algorithms such as Markov chains, NLP, Bi-LSTM, Transformer, etc. Develop data warehouse for managing text data and encoding data. Extract named entities from text data and construct knowledge graphs based on triples. Develop deep learning models to analyze and recognize subject-verb relationships and entities in question sentences. Develop question-answering programs by categorizing questions based on identified patterns and entity types, and constructing answer rules.

Provide technical support and solutions for clients on Azure data platform and machine learning platform. Guide data analysis projects, including data collection, data analysis, deep learning, and training of statistical machine learning models. Configure and manage SQL Server databases, including database recovery and performance tuning. Develop data ETL pipelines using Hadoop, Spark (Databricks), SQL, etc. Build cloud service solutions, including configurations and management of cloud computing units, networks, routes, databases, services, etc.

Assist client (insurance company) in designing property insurance BI products, based on thematic data modeling, constructing HOLAP data cubes. Develop data warehouse and data migration, configure SSIS pipelines, and utilize SQL for development. Assist client (center for disease control) in medical and health data mining, participate in investigations and research on health life expectancy analysis methods. Utilize SAS for developing data management steps and analysis steps.