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.

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

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).

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).

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

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

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

4. Modeling Under Various Assumption Violations, 2018.

• Analyzing Kickstarter Videos with Machine Learning: West Big Data Innovation Hub.