Iype Eldho - Work Experience

North Carolina Institute for Climate Studies, Asheville

Research and Development Associate (August 2024 – Present)

Currently working on Data Extraction, Time Series Analysis, and Dataset Comparison of the Standard Precipitation Index and Standardized Precipitation-Evapotranspiration Index for any location on Earth.
Data Science Student Intern (July 2023 – June 2024)
- Created a Python model to generate maps and graphs of the US, illustrating the impact of 8 teleconnection indices on the standardized precipitation index drought using netCDF and Zarr data.
- Developed an R-based Machine Learning (KNN, Linear Regression) model to predict drought intensity – improved model recall from 79% to 90% by analyzing teleconnection relevance.

Machine Learning Engineer Intern (January 2022 – June 2022)

Elevated the data compression capabilities of a Convolutional Autoencoder model, from 65% to 98% accuracy used in compressing and transmitting beam values within a 6G-System MATLAB simulator.

Software Developer Intern (May 2020 – August 2020)
- Designed a Python-driven simulator to mirror light ambient sensor data, seamlessly uploading sensor output via MQTT with 7 topics, to a cloud-based database for real-time analysis.
- Programmed 9 API functionalities to access the light sensor's control, status, and data registers.