Mr. Mohammad Marjani | Remote sensing | Best Researcher Award
Mr. Mohammad Marjani, Memorial University of Newfoundland, Canada
Mohammad Marjani is a dedicated researcher and educator currently pursuing a Doctor of Philosophy in Electrical and Computer Engineering at Memorial University of Newfoundland, specializing in advanced remote sensing and deep learning algorithms for environmental monitoring under the supervision of Dr. Masoud Mahdianpari. He holds a Master of Science in Geospatial Information System (GIS) from K.N.Toosi University of Technology, where he graduated with a stellar GPA of 4.0/4.0, focusing on wildfire spread modeling using deep learning techniques. His academic journey began with a Bachelor of Science in Geodesy and Geomatic Engineering from the same university, where he researched 3D change detection methods in point clouds.Marjani’s research interests span deep learning, machine learning, spatio-temporal modeling, and remote sensing, with particular emphasis on natural hazards like wildfires and methane monitoring. He has accumulated valuable teaching experience as a Teaching Assistant at both the Iran National Geographical Organization and K.N.Toosi University, imparting knowledge in image processing, MATLAB, and Python programming.In addition to his academic endeavors, Marjani is a co-founder of GeoHoosh, an educational group dedicated to promoting artificial intelligence in geomatic and geospatial engineering. His commitment to advancing the field through both research and education underscores his role as a rising expert in geospatial technologies and environmental monitoring.
Application of Explainable Artificial Intelligence in Predicting Wildfire Spread: An ASPP-Enabled CNN Approach
CNN-BiLSTM: A Novel Deep Learning Model for Near-Real-Time Daily Wildfire Spread Prediction