• Improved the end-to-end development and lifecycle management of NLP-driven solutions supporting enterprise payment screening and sanctions risk solutions, including model development, validation support, production readiness, and post-deployment monitoring.
• Supported model governance and audit readiness by preparing structured documentation, assisting with validation and QA processes, and addressing review findings through testing, analysis, and controlled release practices.
• Improved operational efficiency and alert quality by refining rules and model components through historical back-testing and performance analysis, while maintaining strong risk and compliance standards.
• Participated in ongoing model monitoring and periodic QA activities, supporting stability across system or data changes and assisting with issue investigation and resolution.
• Explored automation opportunities in AML operations using generative AI techniques, collaborating with stakeholders to prototype tools that support investigator workflows under appropriate controls.
• Worked on large-scale text and entity representation approaches (e.g., embeddings) to support screening, risk prioritization, and time-sensitive analytical requests.
• Contributed to cloud-based ML workflows using platforms such as Google Cloud Vertex AI, supporting experimentation, reproducibility, and transitions toward more scalable ML infrastructure.
• Took part in internal innovation and learning initiatives (including AI-focused workshops and bootcamps), contributing to early prototypes in areas such as KYC agents, sanctions-related NLP, and AI-assisted AML analytics.
• Co-supported academic–industry engagement initiatives, including involvement in a university case competition focused on AI in AML, contributing to problem design, technical guidance, and evaluation of student projects. Produced high-fidelity synthetic datasets (10M+ records) using diffusion models to enable responsible data innovation.

Conducted research in financial optimization and risk management under Prof. Roy Kwon’s supervision (Financial Optimization and Risk Management FORM Laboratory).

Courses TAed include:

• MIE1624 Introduction to Data Science and Analytics
• MIE1622 Computational Finance and Risk Management
• MIE424 Optimization in Machine Learning
• MIE1621 Nonlinear Optimization
• STA457/STA2202 Time Series Analysis
• STA414/STA2104 Statistical Methods for Machine Learning II
• STA260 Probability and Statistics II
• STA302/STA1001 – Methods of Data Analysis I
• ACTB40 Fundamentals of Investment & Credit
• ESC180 Introduction to Computer Programming