Dr. Mehrdad Kaveh, K. N. Toosi University of Technology, Iran
Mehrdad Kaveh is a highly qualified expert in Surveying Engineering (GIS), holding a Ph.D. and M.Sc. from K.N. Toosi University of Technology, along with a B.Sc. from Babol Noshirvani University of Technology. His academic achievements include outstanding GPAs throughout his educational journey. He has contributed significantly to the field through several conference papers focusing on topics like landslide risk zoning, healthcare GIS, and urban transportation networks. With extensive teaching experience, Mehrdad has instructed ArcGIS and Optimization Algorithms at various universities, demonstrating his proficiency in GIS software and algorithmic optimization. His research spans diverse areas such as crisis management, machine learning implementation, SAR image processing, and spatial database design in Java. Proficient in ArcGIS, QGIS, GAMS, and programming languages like Matlab, Java, Python, and SQL, Mehrdad Kaveh combines academic excellence with practical skills in spatial analysis, optimization, and deep learning applications in environmental modeling.
Professional Profile:
ORCID
Education:
- Ph.D. in Surveying Engineering (GIS), K.N. Toosi University of Technology, GPA: 19.21
- M.Sc. in Surveying Engineering (GIS), K.N. Toosi University of Technology, GPA: 18.14
- B.Sc. in Surveying Engineering, Babol Noshirvani University of Technology, GPA: 16.00
Teaching Experience:
- Instructor of ArcGIS software at various universities.
- Teaching Assistant and Lecturer in Surveying courses.
- Instructor of Optimization Algorithms.
- Instructor of Machine Learning Algorithms.
- Lecturer for undergraduate and graduate entrance exam courses.
Research and Practical Experience:
- Application of GIS and RS in crisis management and urban planning.
- Health GIS and healthcare network management.
- GIS and multi-criteria decision analysis.
- Simulation and implementation of machine learning and meta-heuristic algorithms.
- Feature selection and classification of SAR images (image processing).
- Multi-objective optimization problems simulation and implementation.
- Design of spatial databases in Java.
- Air pollution modeling using deep learning algorithms.
Skills:
- Software Proficiency: ArcGIS, QGIS, GAMS, AutoCAD, Land, Microsoft Office
- Programming Languages: Matlab, Java, Python, SQL Server
Publication top Notes:
A crossover-based multi-objective discrete particle swarm optimization model for solving multi-modal routing problems
TDMBBO: a novel three-dimensional migration model of biogeography-based optimization (case study: facility planning and benchmark problems)
Optimal Band Selection Using Evolutionary Machine Learning to Improve the Accuracy of Hyper-spectral Images Classification: a Novel Migration-Based Particle Swarm Optimization
Predicting PM10 Concentrations Using Evolutionary Deep Neural Network and Satellite-Derived Aerosol Optical Depth
Application of Meta-Heuristic Algorithms for Training Neural Networks and Deep Learning Architectures: A Comprehensive Review