Dr. Ardalan Awlla | Machine Learning for Big Data | Best Researcher Award

Dr. Ardalan Awlla| Machine Learning for Big Data | Best Researcher Award

Dr. Ardalan Awlla, Cihan University Sulaimaniya, Iraq

Dr. Ardalan Awlla is a dedicated computer science educator and researcher, currently pursuing his Ph.D. at Sulaimani Polytechnic University. With a Master’s in Computer Science from Nanjing University of Information Science and Technology (NUIST), where he earned the Outstanding International Graduate Student and Academic Excellence awards, Dr. Awlla has built a strong academic foundation. He has taught a wide range of subjects, including Software Engineering, System Integration, Game Programming, and Data Structures, as a faculty member at institutions such as the University of Human Development and Qaiwan International University. His research focuses on network and information security, machine learning, and big data, reflecting his commitment to advancing technology and education in the region.

Professional Profile:

Google Scholar
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Suitability for the Award:

Dr. Awlla’s focus on network security and machine learning applications demonstrates a commitment to solving critical technological issues that have both academic and practical significance. His achievements, particularly in botnet detection research, position him as an asset to the cybersecurity field. Additionally, his contributions to academic excellence in teaching core computer science subjects strengthen his candidacy, as he shapes the next generation of computer scientists with knowledge in current, high-demand areas.

Education & Expertise:

Dr. Taku Ito holds a Doctor of Medicine degree from Tokyo Medical and Dental University, where he has developed extensive expertise in Otorhinolaryngology (ENT) and Cognitive-Behavioral Medicine applications in ENT care.

Professional Roles:

Currently serving as an Associate Professor in the Department of Otorhinolaryngology at Tokyo Medical and Dental University, Dr. Ito has previously held positions as an Assistant Professor and Visiting Lecturer in the same department, demonstrating his commitment to advancing ENT medicine and education.

Research Interests & Innovations:

His research focuses on clinical and surgical innovations in otolaryngology, improved imaging and diagnostic techniques, and the integration of cognitive-behavioral medicine within ENT. His work has driven forward critical improvements in surgical outcomes and diagnostic accuracy.

Achievements & Recognition:

With over 20 publications in peer-reviewed journals, numerous presentations at global conferences, and several research grants, Dr. Ito is a recognized leader in his field. He has also developed clinical protocols that significantly enhance patient outcomes in ENT surgeries.

Publications Top Notes:

  • Performance Analysis and Prediction Student Performance to build effective student Using Data Mining Techniques
    • Citations: 10
    • Year: 2019
  • Botnet detection based on genetic neural network
    • Citations: 9
    • Year: 2015
  • Prediction of CoVid-19 mortality in Iraq-Kurdistan by using Machine learning
    • Citations: 5
    • Year: 2021
  • Secure device to device communication for 5G network based on improved AES
    • Citations: 3
    • Year: 2021
  • A Hybrid Simulated Annealing and Back-propagation Algorithm for Feed-forward Neural Network to Detect Credit Card Fraud
    • Citations: 2
    • Year: 2017

 

 

 

Mr. Tohid Sharifi | Machine Learning Award | Best Researcher Award

Mr. Tohid Sharifi | Machine Learning Award | Best Researcher Award

Mr. Tohid Sharifi, Niroo Research Institute, Iran

Mr. Tohid Sharifi is a proficient electrical engineer with an M.Sc. in Electrical Machines and Power Electronics from Amirkabir University of Technology and a B.Sc. in Electrical Power Engineering from Urmia University. His research encompasses notable projects such as a hybrid estimation model for real-time temperature monitoring in electric motors, published in Case Studies in Thermal Engineering, and he is actively working on heat transfer investigations for advanced motor designs. With industrial experience as a CFD Specialist and Cooling System Design Engineer, he has contributed to thermal analysis for a 100kW flywheel energy storage system and optimized heat transfer for a 200kW water-cooled motor using artificial neural networks. His research interests include power electronics, electrical machines, electric vehicles, and metaheuristics, and he holds a patent for a hybrid excited flux switching permanent magnet motor for electric vehicle applications.

Professional Profile:

Orcid
Google Scholar

Suitability for the Best Researcher Award:

Mr. Tohid Sharifi’s extensive research and industrial contributions make him an ideal candidate for the Best Researcher Award. His focus on heat transfer and cooling systems for electric motors, coupled with his work in metaheuristic optimization for motor efficiency, reflects his forward-thinking approach to solving key challenges in power electronics and energy systems. His innovative contributions to electric vehicle motor design and the optimization of thermal systems using advanced algorithms showcase his potential for significant future impact in the field.

🎓 Education:

Mr. Tohid Sharifi holds an M.Sc. in Electrical Machines and Power Electronics from Amirkabir University of Technology (Tehran Polytechnic) and a B.Sc. in Electrical Power Engineering from Urmia University.

🛠️ Academic Projects:

His research includes significant projects such as a hybrid estimation model for real-time temperature monitoring in electric motors, published in Case Studies in Thermal Engineering. He has also worked on heat transfer investigations for advanced motor designs, with papers under revision in prominent journals.

🏭 Industrial Experience:

In the industrial sector, Mr. Sharifi has contributed as a CFD Specialist and Cooling System Design Engineer for electric motors. He played a crucial role in thermal analysis for a 100kW flywheel energy storage system at Niroo Research Institute and optimized heat transfer for a 200kW water-cooled motor using artificial neural networks.

🔍 Research Focus:

His research interests lie in power electronics, electrical machines, electric vehicles, metaheuristics, and heat transfer. He is also an inventor, with a patented hybrid excited flux switching permanent magnet motor for electric vehicle applications.

Publication Top Notes:

  • “An asymmetrical cascaded single-phase quasi Z-source multilevel inverter with reduced number of switches and lower THD”
    • Citations: 9
    • Published: 2020
  • “Optimal design of a synchronous reluctance motor using biogeography-based optimization”
    • Citations: 5
    • Published: 2021
  • “Optimal Design of a Permanent Magnet Synchronous Motor Using the Cultural Algorithm”
    • Citations: 4
    • Published: 2021
  • “Analytical Modeling and Electrical Equivalent Circuit Extraction for a Flux Switching PM Motor for EVs”
    • Citations: 3
    • Published: 2022
  • “Torque Ripple Minimization for a Switch Reluctance Motor Using the Ant Lion Optimization Algorithm”
    • Citations: 2
    • Published: 2022