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Welcome to My GitHub. πŸ‘‹

I'm YoungDon Choi, a principal researcher at K-water AI research Lab ( https://github.com/Kwater-AILab) . I have worked at K-water (https://www.kwater.or.kr/eng/about/sub02/kwaterPage.do?s_mid=1099) since 2003 with many experiences such as dam operation, water resources survey and planning, water technology strategy, and water information system. Currently, I'm working at K-water AI research Lab to apply AI in water resources fields.

I did my PhD from 2017 to 2021 at the UVA Hydroinformatics research group (https://uvahydroinformatics.org/team/) in University of Virginia (https://www.virginia.edu/). This is my Dissertation (https://doi.org/10.18130/g9tg-0c69), google scholar(https://scholar.google.com/citations?user=VCyCE5QAAAAJ&hl=en) and Resume(https://github.com/DavidChoi76/profile/blob/main/YD_Choi_17June2022.pdf)

These are my current research. πŸ€“ Focusing πŸ€”

  1. πŸ”­ Application of neuralhydrology and other AI technologies for upstream and downstream analysis for dam operation
  1. 🌱 Long-Term Water Demand Forecasting

  2. πŸ‘― Satellite Rainfall Distribution using Machine Learning

  3. πŸ”­ Urban Inundation Forecasting using Machine Learning as Surrogate Model

  4. 🌱 Application of NeRF and 3DGS in Water Infrastructures

  5. πŸ‘― Drought Quantification using Social data such as Newspapers

Study for Deeper Understanding. πŸ€“ Focusing πŸ€”

  1. Differentiable Modeling

Study HydroMT. πŸ€“ Focusing πŸ€”

  1. hydromt: https://github.com/DavidChoi76/hydromt
  2. hydromt_wflow: https://github.com/DavidChoi76/hydromt_wflow
  3. hydromt_delwaq: https://github.com/DavidChoi76/hydromt_delwaq
  4. hydromt_sfincs: https://github.com/DavidChoi76/hydromt_sfincs
  5. hydromt_fiat: https://github.com/DavidChoi76/hydromt_fiat
  6. hydromt_delft3dfm: https://github.com/DavidChoi76/hydromt_delft3dfm

YoungDon Choi's Projects

tf2_course icon tf2_course

Notebooks for my "Deep Learning with TensorFlow 2 and Keras" course

the-turing-way icon the-turing-way

Host repository for The Turing Way: a how to guide for reproducible data science

timeseries icon timeseries

Implementation of deep learning models for time series in PyTorch.

timeseries-rnn icon timeseries-rnn

Time-series forecasting with 1D Conv model, RNN (LSTM) model and Transformer model. Comparison of long-term and short-term forecasts using synthetic timeseries. Sequence-to-sequence formulation.

tods icon tods

TODS: An Automated Time-series Outlier Detection System

ulmo icon ulmo

clean, simple and fast access to public hydrology and climatology data.

uncertainpy icon uncertainpy

Uncertainpy: a Python toolbox for uncertainty quantification and sensitivity analysis, tailored towards computational neuroscience.

vertex-ai-mlops icon vertex-ai-mlops

Google Cloud Platform Vertex AI end-to-end workflows for machine learning operations

vicresopt icon vicresopt

VIC-ResOpt: Optimizing water reservoir Operations in the Variable Infiltration Capacity model

vqrf icon vqrf

Official implementation of our arxiv paper "Compressing Volumetric Radiance Fields to 1 MB"

water-forecast icon water-forecast

Machine learning models applied to water demand forecasting in the City of London.

webglearth2 icon webglearth2

[UNMAINTAINED] WebGL Earth 2 - the source code of the project

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