Dr. Seyed Mohamad Javidan, Tarbiat Modares University, Iran
Dr. Seyed Mohamad Javidan is a dedicated researcher and educator in Biosystems Engineering at Tarbiat Modares University, Tehran, Iran. He earned his PhD in 2023 with a focus on diagnosing tomato fungal diseases through image processing. His research interests include plant disease detection, precision agriculture, and biosensor technologies. Dr. Javidan holds several patents, including innovations in agricultural machinery. He has published numerous articles in reputable journals and actively participates in conferences. Fluent in English and Farsi, he also teaches automotive engineering courses, fostering the next generation of engineers. ππΎ
Publication profile
Google Scholar
Education
Dr. Seyed Mohamad Javidan earned his PhD in Biosystems Engineering from Tarbiat Modares University, Tehran, in 2023, with a GPA of 17.33/20. His dissertation focused on “Intelligent Diagnosis of Tomato Common Fungal Diseases Using RGB and Hyperspectral Image Processing.” Prior to that, he completed his Master of Science in Biosystems Engineering at Islamic Azad University of Takestan in 2013, achieving a GPA of 17.78/20 with a thesis on a semi-automatic tomato transplanter. He also holds a Bachelor of Science in Agricultural Machinery from Islamic Azad University of Azadshahr, graduated in 2009 with a GPA of 16.17/20. ππ±π
Research Interests
Dr. Seyed Mohamad Javidan’s research interests are centered on innovative solutions in agriculture. He focuses on plant disease detection through image processing and artificial intelligence, utilizing hyperspectral image analysis for enhanced accuracy. His work also explores biosensor technologies for the early detection of plant pathogens, contributing to precision agriculture and smart farming practices. Additionally, he is passionate about robotics in agriculture, aiming to improve efficiency and productivity. His expertise includes the design, construction, testing, and evaluation of agricultural machinery, bridging technology and sustainable farming. πΏπ€π¬β¨
Awards and Recognitions
Dr. Seyed Mohamad Javidan received the prestigious First Place award in the Scientific Competition of EEDE BARTAR for his innovative “Seed Sowing Robot” project at Islamic Azad University of Gorgan in 2021. This recognition highlights his commitment to advancing agricultural technology and showcases his ability to turn visionary ideas into practical solutions. The competition celebrated the best ideas in the field, and Dr. Javidan’s work stood out for its potential impact on enhancing efficiency in agricultural practices. His achievement not only reflects his expertise but also contributes to the future of smart farming. ππ±π€β¨
Teaching Activities
Dr. Seyed Mohamad Javidan is dedicated to educating future engineers through a diverse curriculum focused on automotive engineering. His teaching activities include courses on the fundamentals of Internal Combustion Engines, Power Generating Technology, and Power Transmission Technology. He also covers specialized topics such as Chassis Technology, Steering and Suspension, as well as Diesel and Gasoline Fuel Systems. Dr. Javidan emphasizes practical skills in General and Technical Drawing, Hydraulic and Pneumatic systems, and Machine Components. His comprehensive approach ensures that students gain both theoretical knowledge and hands-on experience, preparing them for successful careers in engineering. ππ§πβ¨
Conclusion
Dr. Seyed Mohamad Javidan’s extensive educational background, impactful research contributions, innovative patents, and commitment to teaching and mentoring position him as an exceptional candidate for the Best Researcher Award. His work not only advances academic knowledge but also addresses practical challenges in agriculture, making a significant impact on the field.
Publication Top Notes
- Diagnosis of grape leaf diseases using automatic K-means clustering and machine learning π± β Cited by: 120, Year: 2023
- Tomato leaf diseases classification using image processing and weighted ensemble learning π
β Cited by: 16, Year: 2024
- Design, construction and evaluation of semi-automatic vegetable transplanter with conical distributor cup π οΈ β Cited by: 13, Year: 2019
- A feature selection method using slime mould optimization algorithm in order to diagnose plant leaf diseases π β Cited by: 12, Year: 2022
- Detection of Cucumber Fruit on Plant Images Using Artificial Neural Network π₯ β Cited by: 12, Year: 2022
- Detection of Callosobruchus maculatus F. with image processing and artificial neural network π β Cited by: 10*, Year: 2020
- Diagnosing the spores of tomato fungal diseases using microscopic image processing and machine learning πΏ β Cited by: 9, Year: 2024
- Design, Construction, and Evaluation of Automated Seeder with Ultrasonic Sensors for Row Detection π β Cited by: 8, Year: 2021
- A novel approach for automated strawberry fruit varieties classification using image processing and machine learning π β Cited by: 4, Year: 2024
- Design and construction of solar seeding robot equipped with row detection technology βοΈ β Cited by: 3, Year: 2018