Prof. Mehdi Ghatee | PArtificial Intelligence | Best Researcher Award

Full Professor at Amirkabir University of Technology, Iraq

This individual is a highly skilled project manager with expertise in intelligent transportation systems and infrastructure. They have led several high-profile ITS projects across Iran, including the Action Plan for Intelligent Transportation Systems in Shiraz and national projects involving intracity and intercity ITS. Their work focuses on optimizing transportation systems using advanced technologies such as artificial intelligence, neural networks, and data science. With a career spanning over two decades, they have contributed significantly to improving Iran’s public transportation and highway systems, as well as advising on critical petroleum transport safety issues.

Profile

Google Scholar Profile

Education🎓

They hold advanced degrees in engineering and transportation systems, including specialized training in artificial intelligence and network optimization. Their academic journey began with a focus on optimizing transportation networks, and they later pursued studies that explored neural networks and intelligent transportation systems. Through continued education and professional development, they gained cutting-edge knowledge in data mining and its applications in transportation. Their interdisciplinary background merges technical expertise with the management of large-scale infrastructure projects.

Experience💼

The individual has a rich professional background in transportation management. They have served as a project manager for various organizations, including the Shiraz Municipality, Tehran Deputy of Traffic, MSRT, and Tehran Control Traffic Company. Their leadership has been instrumental in developing intelligent transportation solutions and investigating hazardous material transportation risks. They also advised on BRT systems and public transportation initiatives. With over 15 years of experience in both the public and private sectors, they’ve been at the forefront of implementing ITS and advising on petroleum-related transport and logistics.

Awards & Honors🏆

Over their career, the individual has been recognized for their contributions to transportation system innovation and project management excellence. Their leadership on intelligent transportation systems projects has earned them accolades from governmental bodies such as the MSRT and NIOPDC. Notable achievements include awards for the implementation of cutting-edge ITS technologies, as well as safety improvements in the transportation of hazardous materials. Their work has significantly enhanced public transit systems in major Iranian cities, particularly Tehran and Shiraz, positioning them as a key figure in national transportation projects.

Research Focus 🔬

Their research primarily revolves around the application of artificial intelligence and neural networks in optimizing transportation networks. Starting with a focus on network optimization in 2004, they expanded their interests to intelligent transportation systems (ITS) and later neural networks and data mining. They aim to create efficient and safer transportation systems through the use of AI, exploring ways to minimize congestion, enhance road safety, and improve the transportation of goods, especially hazardous materials. Their work intersects with both public transit and highway infrastructure improvements through innovative tech solutions.

Conclusion

The candidate possesses outstanding credentials in intelligent transportation systems and AI-driven technologies, making them a strong contender for the Best Researcher Award. Their vast project management experience, coupled with a diverse research portfolio in AI, neural networks, and data science, aligns well with the award criteria. To further solidify their candidacy, expanding their international collaborations and academic contributions would provide a broader platform for their innovative work, making them a more recognized figure in the global research community.

A systematic review on overfitting control in shallow and deep neural networks
- Authors: MM Bejani, M Ghatee
- Journal: Artificial Intelligence Review
- Citations: 304
- Year: 2021
- Details: This review addresses various methods for controlling overfitting in neural networks, both shallow and deep, presenting strategies and techniques for improving generalization in machine learning models.
Computational methods for solving fully fuzzy linear systems
- Authors: M Dehghan, B Hashemi, M Ghatee
- Journal: Applied Mathematics and Computation
- Citations: 298
- Year: 2006
- Details: This paper introduces novel computational techniques to solve fully fuzzy linear systems, which have applications in systems where uncertainty is modeled using fuzzy logic.
Solution of the fully fuzzy linear systems using iterative techniques
- Authors: M Dehghan, B Hashemi, M Ghatee
- Journal: Chaos, Solitons & Fractals
- Citations: 171
- Year: 2007
- Details: Focuses on iterative techniques to solve fuzzy linear systems, providing an alternative to traditional crisp systems solutions.
A context-aware system for driving style evaluation by an ensemble learning on smartphone sensors data
- Authors: MM Bejani, M Ghatee
- Journal: Transportation Research Part C: Emerging Technologies
- Citations: 153
- Year: 2018
- Details: Proposes an ensemble learning model for driving style evaluation using smartphone sensor data, improving transportation safety and behavior analysis.
Convolutional neural network with adaptive regularization to classify driving styles on smartphones
- Authors: MM Bejani, M Ghatee
- Journal: IEEE Transactions on Intelligent Transportation Systems
- Citations: 84
- Year: 2019
- Details: Introduces CNNs with adaptive regularization techniques for classifying driving styles using mobile sensor data.
Hybrid of discrete wavelet transform and adaptive neuro-fuzzy inference system for overall driving behavior recognition
- Authors: HR Eftekhari, M Ghatee
- Journal: Transportation Research Part F: Traffic Psychology and Behavior
- Citations: 83
- Year: 2018
- Details: Combines wavelet transforms and neuro-fuzzy systems to recognize driving behaviors, helping in real-time traffic safety assessments.
A similarity-based neuro-fuzzy modeling for driving behavior recognition applying fusion of smartphone sensors
- Authors: HR Eftekhari, M Ghatee
- Journal: Journal of Intelligent Transportation Systems
- Citations: 68
- Year: 2019
- Details: Describes a neuro-fuzzy modeling approach for driving behavior detection using fused smartphone sensor data.
Three-phases smartphone-based warning system to protect vulnerable road users under fuzzy conditions
- Authors: RB Zadeh, M Ghatee, HR Eftekhari
- Journal: IEEE Transactions on Intelligent Transportation Systems
- Citations: 65
- Year: 2017
- Details: Develops a warning system using fuzzy logic for protecting road users, especially pedestrians and cyclists.
An inference engine for smartphones to preprocess data and detect stationary and transportation modes
- Authors: HR Eftekhari, M Ghatee
- Journal: Transportation Research Part C: Emerging Technologies
- Citations: 65
- Year: 2016
- Details: Introduces an inference engine to classify transportation modes from smartphone data, improving mobility tracking.
Optimal network design and storage management in petroleum distribution network under uncertainty
- Authors: M Ghatee, SM Hashemi
- Journal: Engineering Applications of Artificial Intelligence
- Citations: 60
- Year: 2009
- Details: Proposes a model for optimizing petroleum distribution networks, considering uncertainty factors in supply chains.

🎉🏆 Congratulations, Dr. Meiguang Cao , on Your Outstanding Achievement as the Best Researcher! 🏆🎉

Dr. Meiguang Cao : Leading Researcher in Wire-arc additive manufacturing

Doctoral student at Wire-arc additive manufacturing, Naval University of Engineering, Egypt

Your remarkable academic journey, extensive research contributions, and dedication to the field of psychology are truly commendable. Your wealth of knowledge and diverse skill set reflect a deep commitment to understanding and addressing critical issues such as bullying, inclusion, and socialization.

🔬 Your successful completion of a PhD in Psychology, along with the numerous advanced courses and workshops, showcases your continuous pursuit of excellence and expertise in your field.

🏆 The awards and recognitions, including the First Place in the Poster Award at the University of Stavanger, underscore the impact of your research and the high regard it holds in the academic community.

Professional Profiles:

Learning Experience

B.S. in Industrial Design
- Duration: September 1, 2016, to June 23, 2020
- Institution: Department of Electromechanical Engineering, Zaozhuang University
Postgraduate Degree in Agricultural Engineering and Information Technology
- Duration: September 1, 2020, to June 14, 2023
- Institution: School of Marine Engineering Equipments, Zhejiang Ocean University
Doctoral Student in Ship and Ocean Engineering
- Duration: September 1, 2023, to Present
- Institution: College of Naval Architecture and Ocean Engineering, Naval University of Engineering

This educational progression reflects your commitment to acquiring diverse knowledge across industrial design, agricultural engineering, and ship and ocean engineering. Each phase of your academic journey contributes to your expertise in different fields, showcasing a well-rounded learning experience.

About your contribution towards the Research & Development, Innovations, and Extension Activities:

Recently, we have investigated the effect of droplet oscillation momentum (DOM) on the surface roughness of wire-arc additive manufacturing fabricated parts, which was published in the internationally renowned journal “Virtual and Physical Prototyping” under the title “Modelling and application of droplet oscillation momentum for elucidating the development of surface roughness in wire-arc additive manufacturing”. The relevant study was published in the internationally renowned journal “Virtual and Physical Prototyping” under the title of “Modelling and application of droplet oscillation momentum for elucidating the development of surface roughness in wire-arc additive manufacturing”.

Mehdi Ghatee | Artificial Intelligence | Best Researcher Award