Daniel Ding

Scenario and Task: Leveraged Python, Go and TypeScript to migrate and validate data from SQL database to no-SQL Neo4j database Action and Result: 1. Designed Knowledge Graph for 31,000+ entities in Neo4j database, reducing database memory usage by 6GB+ 2. Set up a GraphQL server and developed over 60 back-end APIs using Python, Go and TypeScript, facilitating efficient communication between clients and the database 3. Formulated ETL process for Neo4j database streamlining data flow, in collaboration with 3 cross-functional teams

Scenario and Task: Conducted Feature Selection on Python to identify relevant features to forecast the closure time for contaminated sites Actions and Results: 1. Refined 30 features using Drop/Shuffled/SHAP Feature Importance, Benjamini-Hochberg Procedure, and Backward Feature Selection from 200+ constructed features relevant for closing contaminated sites 2. Enhanced the predictive ability of the in-house model using XGBoost by 3.87% with 70,000+ data in California

Scenario and Task: Assist in the course IEOR E4523 Data Analytics Actions and Results: 1. Collaborated with the professor to develop and deliver lectures, facilitate student learning, and design assessments, including quizzes and assignments 2. Supported students by addressing inquiries, identifying errors, and debugging the code to facilitate comprehension of coursework. 3. Evaluated and assessed all homework assignments, quizzes, and exams for over 50 students

Scenario and Task: Perform Data Analysis with Python to decrease carbon emission for client World Economic Forum (WEF) Actions and Results: 1. Implemented Python for Principal Component Analysis (PCA) on factory manufacturing data, and trained a Generalized Additive Model (GAM) on critical factors to fit emission data with over 0.95 Adjusted R Square under China's "2030 Carbon Peak & 2060 Carbon Neutrality" strategy, while excavating actionable measures to further cut over $3.36M cost 2. Performed aluminum industry research and case analysis of leading enterprises through public data collection, desk research, literature retrieval and expert interviews for the client World Economic Forum (WEF) 3. Presented on U.S.-China Workshop and published work in: Circular Economy Processes for CO2 Capture and Utilization (Elsevier Book, accepted)

Scenario and Task: Utilize Machine Learning Algorithms and Explainable Artificial Intelligence (XAI) for modeling Loan Fraud Actions and Results: 1. Collaborated with a team of six to build a DNN model on PyTorch with Python to predict Fraud and Money-Laundering likelihood, and the test-set accuracy exceeded 99.96%, AUC reached 0.974 and KS attained 0.870, saving over $1.367M cost annually 2. Delivered a new algorithm with statistical methods, Python and R substantiating Explainable Artificial Intelligence (XAI) and SHAP’s robustness in the credit risk field before in-bank implementation, and the algorithm yielded over 0.8 Adjusted R Square 3. Presented work as the first author of six in: Ding, Y., Gu B., He, Y., Li, C., Wang, G. and Yan L. Understanding the Black-box Models with Explainable Artificial Intelligence: A theoretical and Practical Perspective. Proceedings of the 15th China Summer Workshop on Information Management (CSWIM) 2022 (493-498), Ningbo, China

Scenario and Task: Develop Supervised Machine Learning tools for discerning Audit Fraud Actions and Results: 1. Utilized Python to build a Logistic Regression model for examining the credibility of financial data provided by clients, and helped to judge whether Audit Fraud exists 2. Conducted wineries industry research and field visit to investigate the state of operation and quantity in stock, and mastered all the A1-level work (employees having worked for one year) within 3 months

• Courseworks: Data Analytics (Graduate Teaching Assistant), Marketing Analytics (A/B Testing, Cluster/Factor Analysis), Business Analytics (Difference in Difference), Machine Learning in Practice, Analysis of Algorithms • Scholarships: Business Analytics Graduate Fellowship (Top 1%)

• Courseworks: Machine Learning, Regression Analysis, Database and Big Data, Business Analytics and Data Mining • Scholarships: Samsung Co., Ltd Scholarship (Top 1%); Weichai Power Co., Ltd Scholarship (Top 5%) • Activities: Leader of Department of Technology and Innovation, SJTU; Exchange Student of SJTU-UT China-Japan Youth Elite Program; Exchange Student of U21 Global Citizenship March 2021

• Scholarships: Shanghai International Studies University Class A Scholarship (Top 1%)