CV

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Education

• Ph.D in Computer Science, University College Dublin, 2024 (expected)
• M.B.A. and M.S. in Business Analytics, Arizona State University, 2018
• B.S. in Maritime Studies, Nanyang Technological University, 2012

Research

• Doctoral Student (01/2020 - present) @ University College Dublin
  • Research on Explainable AI and Time Series Analysis under supervision of Dr. Georgiana Ifrim
  • Investigate Reliability and Robustness of post-hoc Deep Learning based XAI methods in Time Series Classification tasks
  • Devise model-agnostic evaluation metrics to evaluate, measure, and compare quality of explanation across XAI algorithms

Work Experiences

• Data Scientist (08/2018 - 07/2019) @ Trusting Social
  • Credit Score Modeling using Mobile Data:
    • Researched and Optimized performance of Credit Score model for 60+ million of unbanked customers using Python and PySpark; Proposed and Engineered new features
    • Tuned model hyperparameters, achieving 30% increase in Gini of back-testing datasets.
  • Data Quality Monitoring:
    • Automated quality monitoring workflow on 100+ TB of data with real-time dashboard using Redash and mySQL on AWS, improving reliability and saving 10+ hours weekly for analytics team.
    • Evaluated, back-tested the Credit Scoring model; Advised optimal use of credit score for different products based on model back-test result
• Data Science Capstone (09/2017 - 05/2018) @ FedEx
  • Proposed the idea of combining machine learning techniques and time series analysis to make prediction
  • Gathered, cleaned, analyzed, engineered features from multiple sources to build predictive model that saved time and human efforts of doing manual budgeting
  • Delivered a prediction model using Random Forest and Time Series Analysis that achieved Mean Absolute Percent Error (MAPE) of under 5% on 3-month data test data <!–
• Research Assistant (08/2016 - 05/2018) @ Arizona State University
  • Performed large-scale data pre-processing and visualization on edX database with Python and R
  • Explored behavior-based patterns driving metrics using principal component analysis and factor analysis
  • Conducted feature importance analysis with Random Forest and Logistics Regression based on success metrics such as course completion and student retention –>
• Senior Pricing Analyst, Bulk Commodity Transportation (09/2012 - 06/2016) @ Shun Shing Group
  • Led a market research analyst team to analyze, predict, and offer future prices to commodity traders
  • Designed experiments to diagnose features driving contract pricing; Performed testing of independent variables to confirm statistical significance

Professional Activities

• Reviewer, European Conference on Machine Learning (ECML), 07/2022
• Reviewer, International Workshop on Advanced Analytics & Learning on Temporal Data (AALTD), 07/2022
• Co-supervisor, Undergraduate Final Year Research Project, University College Dublin, 05/2021

Skills

• Programming: Python, R
• Big Data: PySpark 2.1
• Database: MySQL, PostgreSQL
• Software: Tableau, Redash, LATEX
• Libraries
  • Python: TensorFlow, PyTorch, Pandas, Numpy, Matplotlib, Scikit-learn
  • R: caret, dplyr, ggplot2