• Built Python/SQL ETL + interactive dashboards for 10K+ financial records—accelerated M&A insights by 30%.
• Automated due-diligence report generation—standardized outputs, cutting analysis time by ~40%.
• Equity screening with scikit-learn surfaced undervalued securities; expanded pipeline by 25% and saved ~35 research hours/month.

• Built risk models (logistic regression & decision trees) improving high-risk detection by ~25%.
• Automated data cleaning in pandas/SQL—cut prep time ~40%.
• R-based scenario analysis & stress testing—recommended 3 policy enhancements.

• Automated Python contract generation for 3 major IT firms—reduced error rate ~15%.
• Trained anomaly-detection classifiers on transaction logs, achieving ~95% accuracy.
• Python ETL + KPI dashboards for cybersecurity—shortened policy reviews by ~25%.

• Shipped a Unity 2D framework (C#) to 20K+ installs with a 4.95 rating via steady maintenance & updates.
• Django-based internal social app—10K+ online users; 1M+ requests/month.
• In-game chat (Unity C# + Firebase)—scaled to 15K+ online at ~99% uptime.

• Focus: Quantitative finance, statistics, optimization.
• Activities: Trading/quant teams, research projects.

• Convolutional Neural Networks (CNNs) and transfer learning for image classification and object detection.
• Training in Vision Transformers (ViTs) and attention-based architectures for modern computer vision tasks.
• Practical modules on model deployment with Flask and Streamlit for building interactive AI applications.

• Olympiads, leadership, UNESCO initiatives.

• Organized Asian Economics Olympiad (2,500+ participants, 18+ countries); raised $50,000.
• Managed 1,750+ volunteers across 9 countries.
• Developed & sold an economics curriculum to 3 schools.

• 20+ charity fairs; $15,000+ raised.
• 80+ volunteers; 3,000+ trees planted.
• “Say No to Plastic” initiative (plastic waste ↓ ~60%).

• National team ranking 7/53.
• Training design & moderation liaison.

HKU

• MATH1013 – University Mathematics II: Limits, continuity, differentiability; functions & graphs, inverse functions; introductory linear algebra. Prepares students for advanced calculus and analysis.
• ACCT1101 – Introduction to Financial Accounting: Core principles of financial accounting, the accounting cycle, and preparation/interpretation of financial statements to support business decisions.
• COMP1117 – Computer Programming I: Intro to programming and problem solving: algorithms, data types, control flow, functions, arrays, and modular program design.
• ECON1210 – Basic Principles of Economics: Foundations of micro & macro: supply–demand, market structures, production & costs, national income, inflation, unemployment, money, and trade.
• CCAI9017 – AI and Human Creativity: How AI reshapes art, design, music, and literature; questions of authorship, ethics, and human–machine collaboration.
• CCGL9016 – The Global History of Capitalism: The origins, spread, regional varieties, and critiques of capitalism; globalization, inequality, and sustainability.

Corporate Finance Institute (CFI)

• Financial Modeling & Valuation Analyst (FMVA®): CFI's Financial Modeling & Valuation Analyst (FMVA®) Certification imparts vital financial analysis skills, emphasizing constructing effective financial models for confident business decisions. This comprehensive program ensures mastery in modeling, budgeting, forecasting, and overall competency in accounting and finance.

Coursera (DeepLearning.AI & Stanford University)

• Supervised Machine Learning: Regression and Classification: Created by DeepLearning.AI and Stanford University. Linear & logistic regression, cost functions, gradient descent, and model evaluation to build predictive ML models.
• Advanced Learning Algorithms: Created by DeepLearning.AI and Stanford University. Neural networks (incl. backprop), decision trees, ensemble methods, and regularization for stronger models.
• Unsupervised Learning, Recommenders, Reinforcement Learning: Created by DeepLearning.AI and Stanford University. Clustering & anomaly detection, recommendation systems, and RL fundamentals.

GitHub

• Convulational Neural Network: Convulational Neural Network Model for recognition of hand-written digits. The model uses sequential model involving 2d Conculational Layers and the result is obtained by Linear layers for classification purposes. The model is trained using CrossEntropyLoss with Adam optimizer.