Assoc. Prof. Dr. Mahmoud Bayat | Artificial intelligence Award | Best Researcher Award
Assoc. Prof. Dr. Mahmoud Bayat, Research Institute of Forests and Rangelands, Iran
Mahmoud Bayat is an Assistant Professor at the Research Institute of Forests and Rangelands, part of the Agricultural Research, Education, and Extension Organization (AREEO) in Tehran, Iran. He earned his B.A., M.Sc., and Ph.D. degrees from the University of Tehran, specializing in forestry science. Mahmoud has collaborated with renowned researchers, including Dr. Charles P.-A. Bourque, Dr. Pete Bettinger, Dr. Eric Zenner, Dr. Aaron Weiskittel, Dr. Harold Burkhart, and Dr. Timo Pukkala. His research focuses on forest modeling and inventory, with particular interest in applying artificial intelligence and machine learning techniques in forestry. Currently, he is working on projects related to growth and yield models for uneven-aged and mixed broadleaf forests using neural networks and the monitoring and mapping of tree species richness in northern Iran’s forests through symbolic regression and artificial neural networks. Mahmoud is proficient in statistical tools such as SPSS and MATLAB, and he is eager to share his expertise and discuss potential collaborations. For more information, his profiles can be found on ResearchGate, Google Scholar, and Scopus.
Professional Profile:
Mahmoud Bayat’s Suitability for the Research for Best Researcher Award
Based on the provided details, Mahmoud Bayat demonstrates a strong candidacy for the Research for Best Researcher Award due to his extensive academic and professional contributions. Below is a summary supporting his suitability
Education 🎓
- Ph.D. in Forestry Science
University of Tehran, Iran - M.Sc. in Forestry Science
University of Tehran, Iran - B.A. in Forestry Science
University of Tehran, Iran
Work Experience 🏢
- Assistant Professor
Research Institute of Forests and Rangelands, Agricultural Research, Education and Extension Organization (AREEO)
Tehran, Iran
Year: [Specify Year] – Present - Research Collaborator
Worked with:- Dr. Charles P.-A. Bourque
- Dr. Pete Bettinger
- Dr. Eric Zenner
- Dr. Aaron Weiskittel
- Dr. Harold Burkhart
- Dr. Timo Pukkala
Research Interests 🔍
- Forest modeling and inventory
- Application of artificial intelligence and machine learning in forestry
Current Projects 📊
- Growth and Yield Models for Uneven-Aged and Mixed Broadleaf Forest
- Method: Neural Network
- Monitoring, Mapping, and Modeling Variation in Tree Species Richness
- Method: Symbolic Regression and Artificial Neural Networks
- Location: Northern Iran Forests
Publication Top Notes:
Comparison of Random Forest Models, Support Vector Machine and Multivariate Linear Regression for Biodiversity Assessment in the Hyrcanian Forests
Projected biodiversity in the Hyrcanian Mountain Forest of Iran: an investigation based on two climate scenarios
Recreation Potential Assessment at Tamarix Forest Reserves: A Method Based on Multicriteria Evaluation Approach and Landscape Metrics
Comparison between graph theory connectivity indices and landscape connectivity metrics for modeling river water quality in the southern Caspian sea basin
Development of multiclass alternating decision trees based models for landslide susceptibility mapping
Modeling Tree Growth Responses to Climate Change: A Case Study in Natural Deciduous Mountain Forests