Dr. Abdullah Al Mehedi

My work focuses on the integration of ML/DL, and statistical modeling in the domains of hydrology and climate science. Throughout my doctoral research and professional career, I have developed and implemented advanced data-driven and physics-based models across on-premises and cloud-computing platforms, including HPC environments.

My expertise lies in building predictive models for hydrologic systems under climate change scenarios, leveraging remote sensing data, geospatial analytics, and ML algorithms to enhance predictive accuracy and operational efficiency. I have extensive experience working with large-scale datasets, integrating satellite imagery (e.g., SAR) and GIS-based tools for hydrologic modeling. I am proficient in Python, MATLAB, R, C++, JavaScript, Java, and SQL, with expertise in major ML/DL frameworks such as TensorFlow, PyTorch, and scikit-learn. I am experienced with cloud computing platforms like AWS/GCP enabling scalable AI-driven solutions.