Third-year Data Science at the Royal University of Phnom Penh (RUPP). Architecting predictive time-series models, biomedical signal processing pipelines, and spatial remote sensing telemetry.
Currently
Data Science
Royal University of Phnom Penh (RUPP)
Featured Lab // Pinned 01
CODE ↗ECG Signal Analysis
Biomedical DSP & QRS Peak Detection · SciPy, 2026
At a Glance // Telemetry
From noisy multi-source ingestion to distributed feature extraction and sub-millisecond production inference.
Automated ingestion of multi-source telemetry, geospatial satellite datasets, and web streams into PostgreSQL & BigQuery data lakes.
Matrix transformations, missing value imputation, polynomial expansions, and PCA dimensional reductions on cluster runtimes.
Deep learning model training with Bayesian hyperparameter optimization, learning rate schedules, and cross-entropy loss minimization.
Model packaging via ONNX runtime, asynchronous FastAPI endpoints, automated drift monitoring, and Dockerized edge deployment.
ADAM OPTIMIZER CONVERGED WITHOUT OVERFITTING. REGULARIZATION: L2 WEIGHT DECAY (1e-4) WITH EARLY STOPPING.
From a January 2025 admission at RUPP to Cambodia’s flagship developer stages — the build log, in real repo dates pulled from GitHub.
Started the Data Science & Engineering programme at the Royal University of Phnom Penh — Python, statistical inference, data structures, linear algebra and discrete mathematics foundations.
Joined the IEEE Cambodia Subsection Landmark Community Gathering with students, developers and researchers, touring RUPP’s advanced laboratories alongside global engineering leadership.
Opened the public GitHub record in January 2026 and shipped the first wave: a February analytics sprint across sales, air-quality, gold-price and book-price data, ECG signal analysis, then JavaScript and Flutter mini-apps.
Serving as an event volunteer for the Cambodia Blockchain Summit community — a regional forum on digital public infrastructure, fintech innovation and decentralised architecture.
Built and iterated the Ahnajak top-up platform line, Aureon AI and JamTlai in TypeScript, plus a Flutter churn-prediction app — alongside distributed data coursework in Apache Spark, Kafka event ingestion, Docker and automated CI/CD.
Published the applied data-science trio: EduRiskAnalysis student early-warning dashboard with 30 unit tests and GitHub Actions CI, the Kasekor-Vision Cambodian agri-data crop optimizer, and the 11-year Phnom Penh precipitation forecast evaluation.
Joined 3,000+ tech professionals at Cambodia’s largest developer conference to explore the tools, stacks and platforms shaping the AI era.
Shortlisted through the global registration screening and advanced with my team to the in-person Pre-Event Meetup in Phnom Penh — 100+ local innovators aligning teams and digging into NASA’s open space-data frameworks.
Finalizing the RUPP Data Science Capstone: high-density vector database embeddings (RAG), sub-millisecond edge runtimes, and real-time predictive intelligence.
Real-world data science systems, biomedical signal processing, agricultural remote sensing, and meteorological time-series predictive pipelines pinned on his official GitHub.
Biomedical digital signal processing on electrocardiogram (ECG) waveforms. Implements baseline wander removal, bandpass filtering, Pan-Tompkins QRS complex peak detection, and cardiac arrhythmia pattern classification.
Financial econometric time-series regression and historical gold commodity price trend forecasting. Evaluates moving averages (SMA/EMA), exponential smoothing, rolling volatility metrics, and predictive regression errors.
Student early-warning academic risk scoring dashboard built with Streamlit, Pandas, and Altair. Engineered transparent risk prediction rules, automated unit test suites with 30 passing tests, and GitHub Actions CI pipelines.
Empowering Cambodian agriculture with spatial data intelligence. Recommends optimal crop species, seed varieties, and planting density based on geographical coordinates, soil chemistry, and provincial climate factors via an interactive map.
11-year monthly precipitation time-series analysis and forecasting evaluation in Phnom Penh (2015–2025). Investigates seasonal monsoon variations, climate telemetry patterns, ARIMA/SARIMA lag structures, and predictive rainfall error bounds.
Engineered for the NASA Space Apps 2026 challenge: Harmonizing NASA MODIS and VIIRS satellite active-fire detections into a calibrated burning calendar, heat radiance clustering, and geospatial wildfire risk telemetry.
Explore additional utility libraries, mobile architectures, web engines, and data pipelines on his GitHub.
| REPOSITORY NAME | LANGUAGE / STACK | DOMAIN / SCOPE | ACCESS |
|---|---|---|---|
|
JamTlai (ចាំតម្លៃ)
|
TypeScript / PWA | Ultra-fast offline-first PWA price checker with dual retail/wholesale pricing in KHR for Cambodian stores | VIEW ↗ |
|
Aureon-Ai
|
TypeScript / AI | Autonomous agent runtime and interactive intelligent interface | VIEW ↗ |
|
Churn-Prediction
|
Dart / Flutter | Customer churn classification and mobile-enabled predictive telemetry | VIEW ↗ |
|
AQ-Data-Analysis
|
Jupyter Notebook | Air Quality index (AQI) data analysis, PM2.5 particulate modeling, and environmental time trends | VIEW ↗ |
|
Books-Price
|
Jupyter Notebook | Commercial pricing regression models and book market exploratory data analysis (EDA) | VIEW ↗ |
|
Sales-Data-Analysis
|
Jupyter Notebook | Retail revenue optimization, inventory cycle clustering, and seasonal sales forecasting | VIEW ↗ |
Six frames from outside the terminal. Roads, rivers and windows — the places that reset the head before the next sprint.
The stack I actually work in — built through coursework, lab reports and small data products that had to ship.
Cleaning, querying and visualising real datasets — from a messy CSV to a chart a decision can actually be made from.
The maths underneath the models, and the models themselves: distributions, gradients, and a classifier that still holds up on unseen data.
Getting the work out of the notebook — schema design, APIs, containers, version control, and the languages the apps are written in.
Open for machine learning engineering collaborations, academic research, and high-performance data systems.
Faculty of Engineering, Department of Information Technology and Engineering & Data Science and Engineering.
Russian Federation Blvd, Toul Kork, Phnom Penh, Cambodia.