Dr. Adib Mahmoodi Nasrabadi | Sustainability | Best Researcher Award
Dr. Adib Mahmoodi Nasrabadi, Florida Atlantic University, United States
Publication Profile
Education
Dr. Nasrabadi is currently pursuing a Ph.D. in Mechanical Engineering at Florida Atlantic University, where he has maintained an impressive GPA of 3.83/4.0. His previous academic achievements include a Masterβs degree from Iran University of Science and Technology with a GPA of 3.87/4.0, showcasing a solid foundation in engineering principles. His undergraduate studies at the University of Kurdistan further emphasize his long-standing commitment to the field.
Research Experience
His current research focuses on investigating the nucleate boiling process using advanced thermometry techniques, such as Laser-Induced Fluorescence (LIF) and infrared thermography. This work is crucial for enhancing thermal management solutions, aligning with his expertise in cooling systems. Additionally, his experience as a senior analyst at TurboTec, where he conducted data analysis and thermodynamic investigations of gas turbine performance, highlights his analytical skills and ability to apply theoretical knowledge to practical challenges.
Teaching Experience
Dr. Nasrabadi has also contributed to education as a teaching assistant and instructor in various capacities. His experience in teaching electronics, robotics, math, and physics to high school students indicates strong communication skills and a dedication to fostering knowledge in the next generation.
Conclusion
Dr. Adib Mahmoodi Nasrabadi’s combination of advanced education, significant research contributions in thermal management, and diverse skill set make him an exemplary candidate for the Research for Best Researcher Award. His ongoing commitment to advancing knowledge in mechanical engineering and renewable energy sectors is commendable and positions him as a leader in his field.
Publication Top Notes Β
- Design, modeling and optimization of a renewable-based system for power generation and hydrogen production – Cited by 57 (2022) π±β‘
- Energy analysis and optimization of a biosensor-based microfluidic microbial fuel cell using both genetic algorithm and neural network PSO – Cited by 39 (2022) π‘π¬
- Deep learning optimization of a combined CCHP and greenhouse for CO2 capturing; case study of Tehran – Cited by 32 (2022) ππ±
- Techno-economic analysis and optimization of a proposed solar-wind-driven multigeneration system; case study of Iran – Cited by 30 (2023) βοΈπ¨
- Experimental investigation of factors affecting the micro microbial fuel cells’ main outputs – Cited by 11 (2023) ππ
- 4E analysis of stacked microbial fuel cell as a component in power plants for power generation and water treatment; with a cost-benefit perspective – Cited by 10 (2022) β»οΈπ§
- Full analysis and deep learning optimization of a sustainable and eco-friendly power plant to generate green hydrogen and electricity; A zero-carbon approach (2024) π±π