M.Sc. Data Science in CCDS
Nanyang Technological University, Singapore
After leading teams, earning recognition, and operating in my comfort zone at POI-TECH, I chose to step away. I knew AI was reshaping everything, and I wanted to be on the right side of that shift. Singapore, CCDS, and a deep dive into data science felt like the only honest next step.
Academic Projects
PythonRaBitQPCAK-Means
High-Performance Vector Search System on DBLP Dataset via RaBitQ
100k+ docs
Processed via byte-stream parsing with 384-d semantic embeddings
1-bit quantization
RaBitQ + Popcount — memory reduced to tens of MBs
66% compute cut
PCA 384→128 dims while preserving recall > 90% variance
- ◆Processed 100k+ documents via byte-stream parsing and generated 384-d semantic embeddings.
- ◆Designed IVF + K-Means index to reduce search space and improve query efficiency.
- ◆Applied RaBitQ quantization (1-bit) with Popcount acceleration, reducing memory to tens of MBs.
- ◆Optimized with PCA (384→128), cutting compute by 66% while preserving recall >90% variance.
PythonLLM EvaluationData Analysis
Safety Evaluation of Generative Autonomous Driving Videos
100+ videos
Labeled dataset for driving video safety evaluation
Multi-level errors
Semantic, logical, and decision-level failure detection
LLM-powered
Automated prompts for safety scoring at scale
- ◆Built a safety evaluation pipeline for generative driving video models, detecting semantic, logical, and decision-level errors.
- ◆Created a labeled dataset of 100+ videos and developed LLM-based prompts for automated safety evaluation.
- ◆Conducted failure mode analysis to quantify and analyze safety issue distributions.
PostgreSQLPython
Large-Scale DBLP Database System: Parsing, Modeling and Optimization
PostgreSQL
Robust relational schema for academic publication data
XML → SQL
Full pipeline from raw DBLP XML to structured tables
Indexing study
Scalability experiments across different DB sizes
- ◆Architected a robust PostgreSQL relational database for large-scale academic publication data.
- ◆Parsed and transformed the DBLP XML dataset into structured tables for analysis.
- ◆Evaluated query performance and scalability by experimenting with different database sizes and indexing strategies.