Reyhaneh Rahimi Email & Phone Number

Dedicated to advancing the field of Atmospheric and Environmental Data Science, I bring extensive expertise in machine learning, deep learning, and remote sensing. My work focuses on implementing advanced ML/DL models for improving wind forecasting, global precipitation estimation, and forecasting extreme atmospheric conditions, while also assessing and mitigating operational risks. I have led projects leveraging multidimensional satellite datasets to build scalable systems for training and deploying machine learning models in real-time operational environments, optimizing both performance and risk management. With a solid foundation in civil engineering and computer science and a PhD in Civil Engineering with a focus on atmosphere and climate science, I possess a unique interdisciplinary skill set that bridges machine learning, risk assessment, and Earth sciences. My current work at Zipline and a NASA-funded PhD project demonstrates my commitment to developing innovative, risk-aware solutions for critical environmental and climate challenges.Skill Highlights:Python (Tensorflow, Pandas, Seaborn, Xarray, GDAL, Geopandas, Rasterio), Machine Learning (SVM, random forest, gradient boosting, RNN, LSTM), Deep Learning (YOLO, R-CNN, FPN, U-net, ResNet), Computer Vision (Image Classification, Object Detection, VAE, GAN), Time-series analysis, Geospatial Modelling, Predictive Analytics, Bayesian Modeling, Cloud Platforms: AWS (EC2, S3, SageMaker), Databricks, Kubernetes, UNIX Shell Scripting, BASH, SQL, Git.