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@cryogars @snowex-hackweek @uwhackweek @geo-smart @CryoInTheCloud

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Ibrahim-Ola/README.md

Hello!

About Me

My name is Ibrahim Alabi. I am an experienced data scientist with a profound passion for data-related problem-solving. My expertise lies in building end-to-end Machine Learning pipelines for solving real-life problems. I am currently a Ph.D. candidate in Computer Science with a Data Science Emphasis at Boise State University. My research focuses on using Machine Learning to improve snow products.

Research Interest

  • Machine Learning.
  • Deep Learning.
  • Computer Vision.
  • Geospatial Analysis.
  • Snow Science.
  • LLM Applications.
  • Remote Sensing.
  • Natural Language Processing.

🔧 Technologies & Tools

Python Logo Anaconda Logo FastAPI Logo Flask Logo Jupyter Logo Git Logo GitHub Logo Kaggle Logo Latex Logo Linux Logo Markdown Logo Numpy Logo Opencv Logo Pandas Logo Pycharm Logo R Logo RStudio Logo Sqlite Logo TensorFlow Logo VScode Logo PyTorch Logo Bash Logo GCP Logo Azure Logo AWS Logo Matlab Logo OpenAI Logo

Publications

  1. Meloche, Julien, Lemmetyinen, Juha, Meyer, Kaitlin, Alabi, Ibrahim, Vuyovich, Carrie, Stuefer, Sveta, Marshall, Hans-Peter, Durand, Michael, & Langlois, Alexandre. (2023). SnowEx23 Laser Snow Microstructure Specific Surface Area Data, Version 1 [dataset]. NASA National Snow and Ice Data Center Distributed Active Archive Center. https://doi.org/10.5067/BSEP59ADC6XN

  2. Joachim Meyer, Anthony Arendt, Scott Henderson, Megan Mason, Zachary Keskinen, Evi Ofekeze, Ibrahim Alabi, Micah Johnson, Xiaolan Xu, Naheem Adebisi, Jack Tarricone, Micah Sandusky, Gail Reckase, Melissa Wrzesien, c-ackroyd, dylan boyd, HP Marshall, Eli Holmes, Romina Piunno, & Jessica Scheick. (2023). snowex-hackweek/website2022: SnowEx Hackweek 2022 (Version 20220725). Zenodo. https://doi.org/10.5281/zenodo.7616208

  3. Henderson, S., Arendt, A., Meyer, J., Setiawan, L., Marshall, H.-P., Johnson, M., Mason, M., Lundquist, J., Pestana, S., Shean, D., Durand, M., Wrzesien, M., McAndrew, B., Ofekeze, E., Alabi, I., Tarricone, J., Meehan, T., Webb, R., McGrath, D., … Koh, J. (2021). SnowEx Hackweek JupyterBook Tutorials. Zenodo. https://doi.org/10.5281/ZENODO.5590433

  4. Median Survival Time and the Predictors of Malaria Mortality Among Under-Five Children: An Analysis of Tudun Murtala Primary Health Center – Kano State, Nigeria (Submitted).

Selected Conferences

  1. Alabi, I. O., Marshall, H. P., Mead, J., Trujillo, E., & Ofekeze, E. (2023). Harnessing L-Band InSAR and Lidar Data Through Machine Learning for Accurate Snow Depth Estimation in Grand Mesa, Colorado. AGU23.

  2. Ofekeze, E., Marshall, H. P., Mead, J., Trujillo, E., & Alabi, I. O. (2023). Advancing Snow Water Equivalent Estimation with SWESARR. AGU23.

  3. Alabi, I. O., Marshall, H. P., Mead, J., & Ofekeze, E. (2022, December). How Transferable are Our Models? A Case Study of Idaho SNOTEL Sites. In AGU Fall Meeting Abstracts (Vol. 2022, pp. C52C-0365).

  4. Ofekeze, E., Marshall, H. P., Mead, J., & Alabi, I. O. (2022, December). A Machine Learning Framework for Active and Passive Microwave Observation from Snow Water Equivalent Synthetic Aperture Radar And Radiometer (SWESARR) for Snow Depth Estimation. In AGU Fall Meeting Abstracts (Vol. 2022, pp. C52C-0364).

  5. Arendt, A. A., Marshall, H. P., Henderson, S. T., Vuyovich, C., Haley, C., Reckase, G., ..., Alabi, I. O. & Meyer, J. (2022, December). Lessons Learned from SnowEx 2022 Hackweek for Fostering Open Science Communities. In AGU Fall Meeting Abstracts (Vol. 2022, pp. ED16B-04).

Workshops

  1. NASA Earth Sciences & UW Hackweek 2024, Neural Networks with PyTorch (link).

  2. GeoSmart Hackweek 2023, Introduction to Machine Learning (link).

  3. SnowEx Hackweek 2022, Introducton to Machine Learning (link).

  4. SnowEx Hackweek 2021, Introducton to Machine Learning (link).

  5. Modeling Under Various Assumption Violations, 2018.

Recognition

📈 GitHub Stats

Ibrahim's GitHub Stats

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  1. tree-models-in-ml tree-models-in-ml Public

    An introduction to tree models (decision trees and random forest) for regression. This tutorial starts from the very basics.

    Jupyter Notebook 1

  2. RAG RAG Public

    An introduction to Retrieval Augmented Generation (RAG) using LangChain

    Jupyter Notebook 3

  3. time-series-python time-series-python Public

    A project on time series in python

    Jupyter Notebook 1

  4. ml_for_sentence_classification ml_for_sentence_classification Public

    This project compares various models and embeddings for sentence classification

    Jupyter Notebook

  5. snow_density_ai snow_density_ai Public

    SnowDensityAI: statistical and machine learning models for snow density and snow water equivalent prediction.

    Python 2

  6. uavsar-lidar-project uavsar-lidar-project Public

    A project on predicting snow depth using L-Band InSAR parameters.

    Jupyter Notebook 1