Shihab Shahriar is fervently dedicated to the study of atmospheric pollution, climate change, and their profound impacts on the environment. He employed statistical downscaling of global climate models to produce insightful climate change projections in his early research career. With a keen interest in strengthening his analytical acumen, he pursued data science, leading him to craft machine learning models for urban air pollution analysis. In his PhD journey, Shahriar is focusing on harnessing deep learning methodologies to predict patterns in particulate matter and wildfire occurrences. Concurrently, he’s delving deep into the nexus between extreme weather events and air pollutants. For more information visit his website (www.shihabshahriar.com) and google scholar profile.