About
With broad exposure to classical and modern statistical approaches, I specialize in developing solutions with machine learning (ML) under various frameworks like PyTorch, Keras, and Scikit-learn. In the past, I have worked on HVAC energy optimization, video analytics, text-to-SQL generation, predictive modeling, anomaly detection, physics-guided ML, and survival analysis, etc.
As a member of LIGO Scientific Collaboration, I have also contributed to academic research in black-hole physics under the Bayesian framework. Specifically, I have worked on identifying strongly lensed gravitational-wave signals, and parameter estimation of ancestors of black holes in Pair-instability Mass Gap. Other than that, recently, I was lucky enough to give a talk at the 10th anniversary of PyCon Hong Kong.
What I do
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Data Science
Data analytics and modeling for real-world challenges.
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Software Development
Backend development, cloud integration, and API design.
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MLOps
Pipeline for model training, deployment, and monitoring.
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Astrophysics
Cool things in the universe that we do not understand well.
Major Tech Stack
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IDE:
Visual Studio CodeLanguage:
Python / SQLTools:
Docker / poetry / git / pylint / mypy / black / isort / pytest / pre-commit / PySparkDeep Learning:
PyTorch Lightning / PyTorch / Keras
Other Technical Skills
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Language:
C++ / C / Go / Bash / R / JavaScriptDevOps:
Podman / ansible / Jenkins / Helm / GitHub ActionsAWS:
Athena / Redshift / SageMaker / VPC / EMR / Lightsail / Bedrock
