Ahmed Ghazi BLAIECH | Artificial intelligence | Best Researcher Award

Mr. Ahmed Ghazi BLAIECH | Artificial intelligence | Best Researcher Award

Mr. Ahmed Ghazi BLAIECH | Artificial intelligence-Associate professor at Higher Institute of Applied Sciences and Technology of Sousse, Tunisia

Ahmed Ghazi Blaiech is a distinguished academic and researcher in the field of computer science, currently serving as an Assistant Professor at the High Institute of Applied Sciences and Technology of Sousse (ISSATSo), University of Sousse. With extensive experience in artificial intelligence, machine learning, and real-time computing, he has made significant contributions to the development of innovative deep learning models and neural networks. His research focuses on medical imaging, embedded systems, and FPGA-based accelerators. Over the years, he has been instrumental in fostering cutting-edge technological advancements through both research and academic mentoring.

Profile:

Orcid | Scopus | Google Scholar

Education:

Ahmed Ghazi Blaiech has an extensive academic background in computer science and informatics systems. He obtained his Habilitation thesis in Engineering of Informatics Systems from the National Engineering School of Sfax (ENIS) in 2022. Prior to that, he earned his PhD in Engineering of Informatics Systems in 2015 from the same institution, graduating with first-class honors. He also holds a Master’s degree in Safety and Security of Industrial Systems with a specialization in Real-Time Computer Science from the High Institute of Applied Sciences and Technology of Sousse. His foundational academic journey began with a Licence degree in Computer Science from the same institute in 2006.

Experience:

Dr. Blaiech has accumulated over a decade of teaching and research experience in academia. Since 2017, he has been an Assistant Professor at ISSATSo, contributing to various undergraduate and postgraduate courses. Before this, he served as an Assistant in Computer Science at ISSATSo (2016-2017) and at the High Institute of Computer Science and Multimedia of Gabes, University of Gabes (2011-2015). He also worked as a contractual assistant at the Faculty of Sciences of Monastir, University of Monastir (2008-2011). In addition to his teaching roles, he has actively led numerous research initiatives and coordinated academic programs.

Research Interests:

Dr. Blaiech’s research interests span multiple domains within artificial intelligence, machine learning, and real-time computing. His work is particularly focused on deep learning applications in medical imaging, embedded systems, and hardware-accelerated computing using FPGA-based architectures. He has also contributed to the advancement of intelligent pervasive systems and neural networks for real-time applications. His research outputs have been widely recognized in high-impact journals, showcasing innovative methodologies in biomedical signal processing, image synthesis, and classification techniques.

Awards and Recognitions:

Throughout his career, Dr. Blaiech has received several accolades for his contributions to the field of computer science. He holds multiple prestigious certifications, including the Huawei Certified ICT Associate (HCIA) in Artificial Intelligence and the Microsoft Technology Associate (MTA) for Python programming. He has also been recognized for his mentorship and coaching in AI-related competitions, playing a crucial role in fostering innovation among students and researchers.

Publications:

Dr. Blaiech has authored numerous research papers in high-impact journals, contributing to advancements in artificial intelligence and medical imaging. Some of his notable publications include:

📌 “CNN-based classification of epileptic states for seizure prediction using combined temporal and spectral features” – Biomedical Signal Processing and Control, 2022. DOI 📖
📌 “An innovative medical image synthesis based on dual GAN deep neural networks for improved segmentation quality” – Applied Intelligence, 2022. DOI 📖
📌 “Comparison by multivariate auto-regressive method of epileptic seizures prediction for real patients and virtual patients” – Biomedical Signal Processing and Control, 2021. DOI 📖
📌 “Innovative deep learning models for EEG-based vigilance detection” – Neural Computing and Applications, 2020. DOI 📖
📌 “A Novel Hardware Systolic Architecture of a Self-Organizing Map Neural Network” – Computational Intelligence and Neuroscience, 2019. DOI 📖
📌 “A New Hardware Architecture for Self-Organizing Map Used for Colour Vector Quantization” – Journal of Circuits, Systems, and Computers, 2019. DOI 📖
📌 “A Survey and Taxonomy of FPGA-based Deep Learning Accelerators” – Journal of Systems Architecture, 2019. DOI 📖

Conclusion:

Dr. Ahmed Ghazi Blaiech’s contributions to the field of artificial intelligence and medical computing have been impactful in both research and academia. His dedication to technological innovation, particularly in neural networks and real-time computing, has positioned him as a leader in the domain. His extensive research output, coupled with his teaching and mentoring experience, underscores his significant role in advancing knowledge and fostering the next generation of AI researchers. Through his work, he continues to drive progress in medical imaging, deep learning applications, and FPGA-based architectures, making a lasting impact in his field.

Oswald Chong | Artificial Intelligence | Best Researcher Award

Dr. Oswald Chong | Artificial Intelligence | Best Researcher Award

Dr. Oswald Chong | Artificial Intelligence-Associate Professor at Arizona State University, United States

Dr. Wai Oswald Chong is an esteemed Associate Professor at Arizona State University, specializing in sustainable engineering and the built environment. His pioneering work integrates artificial intelligence, data science, and engineering principles to optimize infrastructure design, construction, and sustainability. With a focus on carbon-neutral solutions and resource optimization, his research has significantly influenced the fields of green building, lifecycle assessment, and energy efficiency. Over the years, Dr. Chong has led numerous groundbreaking projects, contributing to the advancement of engineering practices and sustainability in the built environment.

Profile:

Scopus | Orcid

Education:

Dr. Chong pursued his higher education in engineering, earning advanced degrees that laid the foundation for his expertise in sustainable engineering. His academic journey was marked by a strong commitment to integrating data science and engineering, equipping him with the skills to develop innovative solutions for complex infrastructure challenges. Throughout his academic training, he focused on optimizing construction processes, reducing environmental impact, and enhancing resource efficiency.

Experience:

With an extensive background in academia and industry, Dr. Chong has held key roles in research, teaching, and consultancy. As an Associate Professor at Arizona State University, he has mentored students, conducted cutting-edge research, and collaborated with global institutions. His work spans multiple disciplines, including civil, fire, electrical, mechanical, and green engineering. His involvement in international projects and consultancy roles has strengthened his reputation as a leading expert in sustainable engineering, contributing valuable insights to the industry’s evolution.

Research Interests:

Dr. Chong’s research focuses on the intersection of engineering, artificial intelligence, and sustainability. His key areas of interest include:

  • Knowledge Systems and Models: Integrating codes, standards, regulations, and best practices across multiple engineering domains.
  • Data-Driven Engineering Optimization: Utilizing AI and big data to enhance project design, safety, cost efficiency, and lifecycle management.
  • Resource Optimization: Enhancing the sustainable use of energy, water, raw materials, and carbon in construction projects.
  • Carbon-Neutral Solutions: Developing predictive analytics and lifecycle assessments to minimize environmental footprints.
  • Circular Economy in Semiconductor Industry: Establishing frameworks to improve sustainability in high-tech industries.

Awards & Recognitions:

Dr. Chong’s contributions have been widely recognized through prestigious awards and accolades. His innovative research in sustainable engineering has earned him funding from leading institutions, including the National Science Foundation and various governmental agencies. His projects on carbon emissions modeling and lifecycle performance have been instrumental in shaping policies and best practices in energy-efficient engineering.

Selected Publications 📚:

  1. Event-Induced Anomalies in Energy Consumption – ASCE Journal of Architectural Engineering (2025) 📅 🔗 https://ascelibrary.org/article/10.1061/(ASCE)AE.1943-5568.0000231
    🔍 Cited by 15 articles
  2. Optimizing HVAC Systems for Semiconductor Fabrication – Journal of Building Engineering (2024) 📅 🔗 https://doi.org/10.1016/j.jobe.2024.109397
    🔍 Cited by 30 articles
  3. Semiconductor Fab Energy Optimization – Engineering Technology (2024) 📅 🔗 https://juniperpublishers.com/etoaj/pdf/ETOAJ.MS.ID.555674.pdf
    🔍 Cited by 22 articles
  4. Determining Critical Success Factors for Urban Residential Reconstruction – Sustainable Cities and Society (2023) 📅 🔗 https://doi.org/10.1016/j.scs.2023.104977
    🔍 Cited by 18 articles
  5. Empowering Owners of Small and Medium Commercial Buildings – Energies (2023) 📅 🔗 https://doi.org/10.3390/en16176191
    🔍 Cited by 12 articles
  6. Quality Management Platform During COVID-19 – Journal of Civil Engineering and Management (2023) 📅 🔗 https://doi.org/10.3846/jcem.2023.18687
    🔍 Cited by 10 articles
  7. Big Data and Cloud Computing for Sustainable Building Energy Efficiency – Elsevier Science and Technology (2016) 📅 🔗 https://doi.org/10.1016/j.jobe.2024.109397
    🔍 Cited by 50 articles

Conclusion:

Dr. Wai Oswald Chong is a distinguished researcher whose work has significantly advanced the field of sustainable engineering. His dedication to integrating AI and data science into engineering has led to the development of more efficient, environmentally friendly, and cost-effective construction practices. With a strong record of publications, ongoing research, and impactful industry collaborations, he stands as a deserving candidate for the Best Researcher Award. His expertise and contributions continue to shape the future of engineering, promoting sustainable development and innovation in the built environment.

 

Mohammad Javad Mahmoodabadi | AI Engineering | Best Paper Award

Assoc. Prof. Dr. Mohammad Javad Mahmoodabadi | AI Engineering | Best Paper Award

Assoc. Prof. Dr. Mohammad Javad Mahmoodabadi | AI Engineering – Associate Professor at Sirjan University of Technology, Iran

Dr. Mohammad Javad Mahmoodabadi is an accomplished academic and researcher, currently serving as an Associate Professor in the Department of Mechanical Engineering at Sirjan University of Technology, Iran. With an impressive track record in mechanical engineering and control theory, Dr. Mahmoodabadi has made significant contributions to the fields of optimization algorithms, machine learning, and mechanical design. He is highly regarded for his innovative approaches in robotics, control engineering, and computational methods. His research has been widely published and cited, establishing him as a leader in his area. Dr. Mahmoodabadi has also played an instrumental role in mentoring graduate students, guiding them through cutting-edge research in nonlinear systems and robotics.

Professional Profile

ORCID | Scopus

Education

Dr. Mahmoodabadi’s educational background reflects a solid foundation in mechanical engineering. He earned his Ph.D. in Mechanical Engineering from the University of Guilan, Iran, in 2012. His dissertation focused on the multi-objective optimization of linear and nonlinear controllers, combining powerful optimization techniques such as Particle Swarm Optimization (PSO) and Genetic Algorithms (GA). During his Ph.D., Dr. Mahmoodabadi achieved excellent academic performance, earning a GPA of 18.80 out of 20 and a dissertation grade of 19 out of 20. Prior to this, he completed his Master’s degree in Mechanical Engineering at Shahid Bahonar University of Kerman, Iran, where his thesis dealt with elasto-static problems using meshless methods. His academic achievements have provided him with a deep understanding of both theoretical and applied mechanics, which have been pivotal in his research career.

Experience

Dr. Mahmoodabadi’s academic career spans over a decade, during which he has held several important positions. After earning his Ph.D., he served as an Assistant Professor at Sirjan University of Technology from 2012 to 2019, before advancing to the role of Associate Professor. Throughout his career, he has taught various undergraduate and graduate courses, including robotics, control of robots, linear control, fuzzy logic, and optimization. His extensive teaching experience in mechanical engineering and related disciplines has earned him recognition for his ability to convey complex concepts with clarity. In addition to his teaching roles, Dr. Mahmoodabadi has served as the head of the Department of Mechanical Engineering and the Graduate Student Office at his university. His leadership has contributed to the development of academic programs and research initiatives within the department.

Research Interests

Dr. Mahmoodabadi’s research interests are diverse, with a primary focus on control theory, machine learning, computational methods, and optimization algorithms. He has worked on various topics such as adaptive robust control, fuzzy logic systems, and multi-objective optimization in the context of nonlinear dynamic systems. His research also extends to robotics, where he has developed novel control strategies for autonomous systems. Additionally, Dr. Mahmoodabadi’s work on mechanical design and analysis of complex systems has led to innovative solutions in both theoretical and applied engineering. His approach integrates computational techniques with practical applications, particularly in optimization and control engineering.

Awards

Throughout his career, Dr. Mahmoodabadi has received numerous accolades for his contributions to research and teaching. His excellence in academic leadership and groundbreaking research has earned him recognition within his institution and the broader academic community. Notably, his work in the development of control algorithms and optimization methods has received significant attention from his peers, reflected in his high citation count and his role as a mentor to graduate students. Although Dr. Mahmoodabadi has not explicitly listed awards in the traditional sense, his impact on the academic and research community through his publications, patents, and leadership roles can be considered as a testament to his achievements.

Publications

M.J. Mahmoodabadi, N.R. Babak, Pareto optimum design of an adaptive robust backstepping controller for an unmanned aerial vehicle, Asian Journal of Control (2022). 📚
R. Abedzadeh Maafi, S. Etemadi Haghighi, M.J. Mahmoodabadi, A novel multi-objective optimization algorithm for Pareto design of a fuzzy full state feedback linearization controller applied on a ball and wheel system, Transactions of the Institute of Measurement and Control 44 (7) (2022), 1388–1409. 🛠
M.J. Mahmoodabadi, S. Hadipour Lakmesari, Optimal design of an adaptive robust controller using a multi-objective artificial bee colony algorithm for an inverted pendulum system, Transactions of the Canadian Society for Mechanical Engineering 46 (1) (2022), 89–102. 📈
S.H. Lakmesari, M.J. Mahmoodabadi, Adaptive sliding mode control of HIV-1 infection model, Informatics in Medicine Unlocked 25 (2021), 100703. 💡
M.J. Mahmoodabadi, Moving least squares approximation-based online control optimized by the team game algorithm for Duffing-Holmes chaotic problems, Cyber-Physical Systems 7 (2) (2021), 1-21. ⚙️
M.J. Mahmoodabadi, A.R. Nemati, A new optimum numerical method for analysis of nonlinear conductive heat transfer problems, Journal of the Brazilian Society of Mechanical Sciences and Engineering 43 (5) (2021), 1-8. 🔥
R. Abedzadeh Maafi, S. Etemadi Haghighi, M.J. Mahmoodabadi, Pareto optimal design of a fuzzy adaptive hierarchical sliding-mode controller for an XZ inverted pendulum system, IETE Journal of Research (2021). 🔄

Conclusion

Dr. Mohammad Javad Mahmoodabadi’s academic and research career exemplifies excellence in mechanical engineering and control systems. His innovative work in optimization algorithms, machine learning, and mechanical design has earned him recognition as a leader in his field. With a strong publication record and significant contributions to the academic community, he is a well-deserving candidate for the “Best Researcher Award.” His ability to blend theoretical advancements with practical applications, along with his mentorship of future researchers, positions him as a key figure in the development of engineering solutions for complex systems. Dr. Mahmoodabadi’s dedication to advancing knowledge, combined with his academic leadership and impactful research, makes him an outstanding nominee for this prestigious award.