IDRISS DAGAL | Electrical Engineering | Best Researcher Award

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Dr. IDRISS DAGAL | Electrical Engineering | Best Researcher Award

Assistant Professor, Istanbul Beykent University, Turkey

Dr. Idriss Dagal, an Assistant Professor at Istanbul Beykent University, is a researcher and engineer from Chad specializing in Electrical Engineering, Renewable Energy, and Artificial Intelligence. With a career spanning over a decade, he has worked in various roles, including Aircraft Engineer and Lecturer, and has contributed extensively to the field of electrical systems, power electronics, and optimization algorithms. His academic journey includes a Ph.D. from Yıldız Technical University, Istanbul, Turkey, where he also completed his MSc in Avionics Engineering. Dr. Dagal has authored over 30 publications and is an active reviewer for renowned journals. 🌍💡

Publication Profile

ORCID

Education:

Dr. Dagal holds a Bachelor of Science (B.S.) degree in Industrial and Maintenance Engineering from Mongo Polytechnic University (Chad, 2006), a Master of Science (M.Sc.) in Aviation Engineering from Ethiopian Airlines Aviation School (Ethiopia, 2010), and a Ph.D. in Electrical Engineering from Yıldız Technical University (Turkey, 2022). He is currently pursuing a second M.Sc. in Avionics Engineering at Yıldız Technical University. 🎓📚

Experience:

Dr. Dagal’s professional experience spans multiple countries and roles, including serving as an Aircraft Maintenance Engineer in Chad, a Lecturer at various institutions in Chad, and a Sales Engineer in Turkey. Since 2024, he has been serving as an Assistant Professor at Istanbul Beykent University, Turkey, specializing in electrical engineering, renewable energy, and avionics. 🛠️✈️

Awards and Honors:

Dr. Dagal has received several prestigious awards, including the Chad’s Government National Scholarship (2003), Ethiopian Airlines Aviation School International Scholarship (2008), Turkish Government International Scholarship (2015), Young Research Scholarship Award for Eurasia Research (2019), and the Leadership Skills African Civic Engagement Academy (2022). 🏆🌟

Research Focus:

Dr. Dagal’s research interests are centered on optimization algorithms, artificial intelligence, renewable energy systems, power electronics, and aircraft control systems. His doctoral research focused on optimizing photovoltaic battery charging systems using hybrid particle swarm-based algorithms. He has a strong background in developing control mechanisms for sustainable energy systems and dynamic systems in aviation. 🔋🔧🚀

Conclusion:

Dr. Idriss Dagal is an accomplished academic and researcher who combines his expertise in electrical and aerospace engineering with a deep commitment to renewable energy and technology optimization. His interdisciplinary work continues to contribute to advancements in energy systems, aircraft control, and smart technologies. 🌱💻

Publications 

Energy transfer from PV panel to Battery via Buck-Boost Converter, International Journal of Technology and Science, Vol. 5, Issue 3, pp. 46-60, 26 November 2019. DOI

Improved salp swarm algorithm based on particle swarm optimization for maximum power point tracking of optimal photovoltaic systems, International Journal of Energy Research, 2022; 1-18. DOI: 10.1002/er.7753. Impact Factor: 4.3, Q1.

MPPT mechanism based on novel hybrid particle swarm optimization and salp swarm optimization (PSOSSO) algorithm for battery charging through Simulink, Scientific Reports Journal, 2022; 12:2664. DOI. Impact Factor: 3.8, Q1.

A Novel Hybrid Series Salp Particle Swarm Optimization (SSPSO) for Standalone Battery Charging Applications, Ain Shams Engineering Journal, 2022; 13:10174. DOI. Impact Factor: 6, Q1.

Improved Particle Swarm Optimization based Buck-Boost converter (IPSOBBC) for Photovoltaic System Application, Recent Advances in Science & Engineering (RASE), 2022.

Transformer rail-tapped buck-boost converter design-based feedback controller for battery charging systems, Energy Storage Journal, 2022; e414, DOI. ESCI.

Secure and Optimized Satellite Image Sharing based on Chaotic eπ Map and Racah Moments” Expert Systems with Applications, Volume 236, February 2024, 121247, DOI: 10.1016/j.eswa.2023.121247. Impact Factor: 7.5, Q1.

Hybrid SSA-PSO-based intelligent direct sliding-mode control for extracting maximum photovoltaic output power and regulating the DC-bus voltage, International Journal of Hydrogen Energy, Volume 51, Part C, 2 January 2024, Pages 348-370, DOI. Impact Factor: 8.1, Q1.

An Improved Constant Current Step-based Grey Wolf Optimization Algorithm for Photovoltaic Systems, Journal of Intelligent & Fuzzy Systems, 2024, DOI. Impact Factor: 1.7, Q3.

A Modified Multi-Stepped Constant Current Based on Grey Wolf Algorithm for Photovoltaics Applications, Springer, Electrical Engineering, 2024, DOI. Impact Factor: 1.6, Q3.

Najmeh Zamani | Engineering | Best Researcher Award

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Dr. Najmeh Zamani | Engineering | Best Researcher Award 

Postdoc researcher, Concordia university, Canada

🌟 Najmeh Zamani (b. 29th July 1989) is a dedicated researcher in the field of electrical and computer engineering. She is currently a Postdoctoral Researcher at Concordia University, Canada, with a strong academic background from Isfahan University of Technology, Iran. Najmeh’s expertise spans control systems, nonlinear multi-agent systems, and deep learning applications. Married and proficient in both Persian and English, she is recognized for her significant contributions to her field.

 

Profile

Google Scholar

 

Education

🎓 Najmeh Zamani has an impressive academic record, starting with a Bachelor’s degree in Electrical Engineering from Isfahan University (2007-2011), where she ranked 1st. She continued at the same university for her Master’s degree (2011-2014), ranking 3rd, and then pursued a Ph.D. in Electrical Engineering at Isfahan University of Technology (2015-2021), achieving a GPA of 19/20. Her Ph.D. dissertation focused on the “Consensus of Nonlinear Multi-Agent Systems with Time-Delays and Actuator Faults.” Najmeh also completed postdoctoral research at Concordia University, Canada, in 2023.

Experience

💼 Najmeh Zamani has a robust professional background, including roles as a researcher at Isfahan University of Technology, an R&D researcher at Control Farayand Pasargad Company, and an electronic designer at Sirco Company. Her experience spans industrial projects like COVID-19 pandemic prediction models and power electronic boost converter design. Najmeh has also served as a visiting professor and teaching assistant in various institutions, sharing her expertise in control systems and electronics.

Research Interests

🔬 Najmeh Zamani‘s research interests are diverse and cutting-edge. They include distributed control systems and multi-agent systems, adaptive control of nonlinear systems with time-delays and faults, fault estimation and control theory, and control of distributed applications like mobile sensors. She is also passionate about deep learning, probabilistic graphical models (PGM), data-driven control, reinforcement learning, and data analysis.

Awards

🏆 Najmeh Zamani has received several accolades throughout her academic journey. She was ranked 1st among all graduated students in Electrical and Computer Engineering at Isfahan University in 2011. She was also recognized as an outstanding B.Sc. and M.Sc. student from 2007 to 2014. Notably, she received admission offers for both her graduate and doctoral studies at Isfahan University of Technology without needing to take the National Entrance Exam for Graduate Schools.

Publications

N. Zamani, M. Ataei, M. Niroomand, “Analysis and Control of Chaotic Behavior in Boost Converter by Ramp Compensation Based on Lyapunov Exponents Assignment: Theoretical and Experimental Investigation”, Chaos, Solitons and Fractals, 2015, cited by 20 articles. Link.

N. Zamani, J. Askari, M. Kamali, A. Aghdam, “Distributed adaptive consensus tracking control for non-linear multi-agent systems with time-varying delays”, IET Control Theory & Applications, 2020, cited by 15 articles. Link.

H. Kalantari, M. Mojiri, S. Dubljevic, N. Zamani, “Fast l1-MPC Based on Sensitivity Analysis Strategy”, IET Control Theory & Applications, 2020, cited by 10 articles. Link.

N. Zamani, J. Askari, M. Kamali, H. Kalantari, A. Aghdam, “Adaptive Tracking Control for Nonlinear Multi-Agent Systems with Stuck Failures and Unknown Control Directions”, Journal of the Franklin Institute, 2024. Link.

H. Kalantari, M. Mojiri, Najmeh Zamani, “Urban Traffic Control By Fast l1 Model Predictive Control Based on Sensitivity Analysis”, IET Control Theory & Applications, 2024. Link.

Quan Yuan | Engineering | Best Researcher Award

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Prof. Quan Yuan | Engineering | Best Researcher Award

Professor, School of Vehicle and Mobility, Tsinghua University, China

Dr. Quan Yuan is a distinguished professor at the School of Vehicle and Mobility, Tsinghua University. With a Ph.D. in vehicle engineering earned in 1997, Dr. Yuan has made significant contributions to the fields of intelligent vehicles, human factors engineering, traffic safety, and accident analysis. Over his illustrious career, he has led more than 40 research projects, published over 100 papers, and analyzed over 8,000 traffic crashes in Beijing. His research has provided valuable insights and innovations to improve the safety and functionality of intelligent transportation systems.

Profile

ORCID

🎓 Education:

Dr. Quan Yuan received his Ph.D. in Vehicle Engineering in 1997. He further honed his expertise as a postdoctoral research fellow at Tsinghua University from 2000 to 2003. Additionally, he broadened his academic horizon as a visiting scholar at the University of Washington from 2013 to 2014.

💼 Experience:

Dr. Yuan’s professional journey is marked by his role as a professor at Tsinghua University, where he has been instrumental in advancing research in intelligent vehicles and traffic safety. He has completed over 40 research projects and published more than 100 papers. His editorial appointments include roles such as the editorial director for the Journal of Intelligent & Connected Vehicles and associate editor for Digital Transportation and Information.

🔬 Research Interests:

Dr. Yuan’s research interests are centered on intelligent vehicles, traffic safety, and human factors engineering. His work focuses on combining intelligent vehicle technology with traffic safety to develop testing scenarios that enhance vehicle safety. He has also proposed innovative solutions such as a visual and infrared fusion perception recognition method to improve safety in adverse weather conditions and address traffic safety issues in pastoral areas.

🏆 Awards:

Dr. Quan Yuan has received numerous accolades for his contributions to the field of vehicle engineering and traffic safety. He is a recognized senior member of SAE-China and an esteemed member of IEEE. His work has significantly influenced the development and safety of intelligent transportation systems.

Publications 

Paper on Intelligent Vehicle Technology
Study on Traffic Safety and Accident Analysis
Research on Human Factors Engineering in Vehicle Design
Innovations in Traffic Crash Analysis
Book on Vehicle Engineering and Safety