Sathiyabhama Balasubramaniam | Artificial Intelligence | Best Researcher Award

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Dr. Sathiyabhama Balasubramaniam | Artificial Intelligence | Best Researcher Award

Professor at Sona College of Technology, India

Dr. B. Sathiyabhama is a highly accomplished academician and researcher, currently serving as the Professor and Head of the Department of Computer Science and Engineering at Sona College of Technology, Salem, Tamil Nadu, India. She holds the distinguished position of Dean Admissions and Chief Coordinator of International Relations at the same institution. With an extensive career spanning over three decades, Dr. Sathiyabhama has contributed significantly to the fields of data mining, big data analytics, computational intelligence, and health informatics. Her leadership and commitment to higher education have earned her widespread recognition, both nationally and internationally.

Profile:

Google Scholar

Education:

Dr. Sathiyabhama’s educational journey began with a Bachelor of Engineering (B.E.) degree, followed by a Master of Technology (M.Tech.) from a prestigious institution. She completed her M.Tech project internship at the renowned Bioinformatics Centre, Indian Institute of Science (IISC), Bangalore, where she also secured a university rank. Her academic pursuits culminated with a Doctor of Philosophy (Ph.D.) from the National Institute of Technology, Tiruchirappalli, one of India’s leading engineering institutes. Dr. Sathiyabhama’s academic excellence and commitment to her research have provided her with a solid foundation for her career in both teaching and research.

Experience:

Dr. Sathiyabhama brings nearly 31 years of teaching experience to her profession, imparting knowledge in diverse areas of computer science and engineering. She has a wealth of expertise in areas such as data mining, big data analytics, bioinformatics, algorithm analysis, compiler design, and optimization. Throughout her career, she has not only focused on delivering high-quality education but also on fostering a research-driven environment that encourages students to engage in innovative projects. Her dedication to her students is reflected in her consistent ability to produce excellent results. Additionally, Dr. Sathiyabhama has held key administrative positions, including as the Head of the Centre for Data Mining and Database System Design, further enhancing her role as a leader in academic innovation.

Research Interests:

Dr. Sathiyabhama’s research interests lie primarily in the fields of data mining, computational intelligence, health informatics, bioinformatics, and big data analytics. Her work focuses on developing advanced algorithms for the analysis of large datasets and applying these techniques in various domains such as healthcare and bioinformatics. She is deeply committed to exploring how technology can be used to solve real-world problems, especially in healthcare, through innovations like wearable devices and data-driven healthcare monitoring systems. Dr. Sathiyabhama has also contributed to research on optimization techniques and machine learning, with a focus on improving the impact of healthcare systems through the application of AI and data analytics.

Awards and Recognitions:

Throughout her career, Dr. Sathiyabhama has received numerous accolades recognizing her contributions to education, research, and the professional community. She has been honored with awards such as the Best Outgoing PG Student Award during her M.Tech course and the Best Women Engineer award by the Institution of Engineers (India). Dr. Sathiyabhama is a recipient of the Excellence in Teaching award and has been recognized for producing outstanding academic results. She has also been selected as a candidate for the “Who’s Who in the World” and “Cambridge Who’s Who” editions, a prestigious recognition for her work in science and engineering. Dr. Sathiyabhama has received multiple nominations and awards for her work in research and development, including a patent granted in her name and recognition for her leadership in AICTE-UKIERI leadership development programs.

Publications:

Dr. Sathiyabhama has made significant contributions to the academic community, with 144 publications across international and national journals, conferences, and books. Her notable works include a book chapter on IoT-based non-invasive wearable healthcare monitoring systems published by Wiley and co-authored books on Professional Ethics and Fundamentals of Computing. Dr. Sathiyabhama’s research has also been widely cited by other academic articles and continues to influence the fields of computational intelligence, bioinformatics, and big data analytics. Below are a few of her significant publications:

  1. Sathiyabhama, B., & Rajeswari, K. C. (Year). “IoT based Noninvasive Wearable and Remote Intelligent Pervasive Healthcare Monitoring Systems for Elderly.” Wiley Publications.

  2. Sathiyabhama, B., & others (Year). “Fundamentals of Computing.” Sonaversity Publications.

  3. Sathiyabhama, B., & others (Year). “Professional Ethics.” Sonaversity Publications.

Conclusion:

In conclusion, Dr. B. Sathiyabhama stands as a distinguished academician and researcher whose work in data mining, big data analytics, and health informatics has had a profound impact on both her students and the academic community. With decades of teaching experience and numerous accolades to her name, she continues to inspire and lead in the fields of education and technology. Dr. Sathiyabhama’s ongoing research and her commitment to advancing knowledge and innovation ensure that her contributions will have a lasting impact on the future of technology and education. As she continues to make strides in her professional career, her work remains at the forefront of integrating technology with real-world solutions, particularly in the healthcare sector.

Ahmed Ghazi BLAIECH | Artificial intelligence | Best Researcher Award

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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.

Jie Li | Artificial Intelligence | Best Researcher Award

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Assoc Prof Dr. Jie Li | Artificial Intelligence | Best Researcher Award 

Assoc Prof Dr. Jie Li, Chongqing University of Science & Technology, China

Profile

scopus

Dr. Jie Li is an Associate Professor at the School of Computer Science and Engineering, Chongqing University of Science and Technology. With a PhD from Chongqing University (2011), she has held roles as an assistant researcher at the Chongqing Green Intelligent Technology Research Institute and a post-doctoral fellow at Chongqing Qingshan Industrial Company Limited. Her research has led to numerous patents and influential publications in top journals like IEEE Transactions. Dr. Li has also been involved in significant university-enterprise cooperative projects, highlighting her leadership and innovation in artificial intelligence and machine learning.

Strengths for the Award:

  1. Significant Research Contributions: Dr. Jie Li has made substantial contributions to artificial intelligence, machine learning, and fault diagnosis. Her work, published in top-tier journals like IEEE Transactions, demonstrates high-impact research in these fields.
  2. Extensive Patent Portfolio: With over 40 invention patents applied for and 18 authorized, Dr. Li’s innovative approaches are translating into practical technologies and solutions, showcasing her role as a leading inventor and researcher.
  3. Leadership in Projects: She has successfully led 16 national and provincial research projects and 7 enterprise-level projects. Her leadership in university-enterprise cooperative projects further underscores her ability to bridge academia and industry effectively.
  4. Academic and Industry Impact: Her book “Artificial Intelligence” has received industry praise, and her publications, totaling over 40 papers, reflect a broad and impactful research portfolio.

Areas for Improvement:

  1. Broader Citation Metrics: While Dr. Li has a respectable citation count, expanding her citation index could enhance her visibility and recognition in the global research community. Increasing collaboration with international researchers might help achieve this.
  2. Research Dissemination: Although Dr. Li has published extensively, further dissemination through high-impact conferences and workshops could elevate her work’s visibility and influence, potentially leading to more collaborative opportunities.
  3. Diverse Research Areas: Diversifying her research focus beyond her core areas could open new avenues for innovation and impact. Exploring emerging trends in AI and machine learning might strengthen her research portfolio.

Education🎓

Dr. Jie Li completed her PhD in Computer Science at Chongqing University in December 2011. Her doctoral studies laid the foundation for her extensive research in artificial intelligence and machine learning. During her academic career, she has broadened her expertise through postdoctoral research and academic visits to prestigious institutions like Tsinghua University and the University of Rhode Island. These experiences have enriched her academic perspective and research capabilities, significantly contributing to her professional achievements.

Experience💼

Dr. Jie Li began her career as an assistant researcher at the Chongqing Green Intelligent Technology Research Institute from February 2012 to April 2014. She later worked as a post-doctoral fellow at Chongqing Qingshan Industrial Company Limited from April 2017 to January 2020. Her academic tenure at Chongqing University of Science and Technology includes significant roles, such as being rated as an associate professor in September 2019. Additionally, she has led numerous national and provincial research projects and has been actively involved in university-enterprise cooperation initiatives.

Research Focus🔬

Dr. Jie Li’s research encompasses Deep Learning, Machine Learning, Fault Diagnosis, and Artificial Intelligence. Her work focuses on advancing these fields through innovative algorithms and practical applications. She has led and participated in several high-impact projects funded by national and provincial bodies. Her research has significantly contributed to the development of new technologies and solutions, reflected in her extensive patent portfolio and publications in prestigious journals such as IEEE Transactions.

Publications Top Notes

Polyacrylonitrile-based 3D N-rich activated porous carbon synergized with Co-doped MoS2 for promoted electrocatalytic hydrogen evolution (Huang, Z., Li, J., Guo, S., Zeng, J., Yuan, F., Separation and Purification Technology, 2025, 354, 129011) 📄

In-situ construction of nano-multifunctional interlayer to obtain intimate Li/garnet interface for dendrite-free all solid-state battery (Yu, S., Gong, Z., Gao, M., Li, Y., Chen, Y., Journal of Materials Science and Technology, 2025, 206, pp. 248–256) 📄

Advanced cathode materials for metal ion hybrid capacitors: Structure and mechanisms (Li, J., Liu, C., Momen, R., Zou, G., Ji, X., Coordination Chemistry Reviews, 2024, 517, 216018) 📖

Unraveling the delithiation mechanism of air-stabilized fluorinated lithium iron oxide pre-lithiation material (Wen, N., Li, J., Zhu, B., Guo, J., Zhang, Z., Chemical Engineering Journal, 2024, 497, 154536) 📄

Dual ion regulation enables High-Coulombic-efficiency lithium metal batteries (Huang, X., Wang, M., Zhou, Y., Li, J., Lai, Y., Nano Energy, 2024, 129, 110031) 📄

In-Situ Construction of Electronically Insulating and Air-Stable Ionic Conductor Layer on Electrolyte Surface and Grain Boundary to Enable High-Performance Garnet-Type Solid-State Batteries (Zhou, X., Liu, J., Ouyang, Z., Li, J., Jiang, L., Small, 2024, 20(34), 2402086) 📄

Enhancing the Efficient Utilization of Li2S in Lithium-Sulfur Batteries via Functional Additive Diethyldiselenide (Li, Z., Wang, M., Yang, J., Lai, Y., Li, J., Energy and Fuels, 2024, 38(16), pp. 15762–15770) 📄

Emerging polyoxometalate clusters-based redox flow batteries: Performance metrics, application prospects, and development strategies (Han, M., Sun, W., Hu, W., Zhang, C., Li, J., Energy Storage Materials, 2024, 71, 103576) 📖

Conductivity behavior of Na5YSi4O12 and its typical structural analogues by solution-assisted solid-state reaction for solid-state sodium battery (Liu, L., Xu, Y., Zhou, X., Guo, X., Jiang, Y., Journal of Solid State Chemistry, 2024, 336, 124781) 📄

Preparation of Hard-Soft Carbon via Co-Carbonization for the Enhanced Plateau Capacity of Sodium-Ion Batteries (Li, J., Zheng, H., Du, B., Li, D., Chen, Y., Energy and Fuels, 2024, 38(14), pp. 13398–13406) 📄

Conclusion:

Dr. Jie Li’s exceptional achievements in artificial intelligence and machine learning, marked by a robust patent portfolio, significant publications, and leadership in high-impact projects, position her as a strong candidate for the Best Researcher Award. Her innovative contributions and ability to lead and execute complex research projects highlight her outstanding capabilities and potential for furthering advancements in her field. Addressing the areas for improvement could further enhance her already impressive research profile and global impact.

Abdullahi Umar Ibrahim | Artificial intelligence and IoT | Best Researcher Award

Posted on by Academic achievements

Dr Abdullahi Umar Ibrahim | Artificial intelligence and IoT | Best Researcher Award

Dr Abdullahi Umar Ibrahim , Near East University , Cyprus

Dr. Abdullahi Umar Ibrahim is an Assistant Professor in the Biomedical Engineering Department at Near East University, Nicosia, Cyprus. With a solid background in biomedical engineering, Dr. Ibrahim has made significant contributions in both academia and research. His expertise spans various aspects of bioengineering, including CRISPR technology, AI applications in medicine, and biomedical instrumentation. Known for his dynamic teaching approach and innovative research, he is actively involved in advancing the field of bioengineering through his work in laboratory technologies and interdisciplinary projects. Dr. Ibrahim is also committed to enhancing digital skills and interdisciplinary collaboration through EU-funded initiatives.

Publication Profile

Google Scholar

Strengths for the Award

  1. Innovative Research Focus: Dr. Abdullahi Umar Ibrahim’s research at the intersection of CRISPR technology, AI, and biomedical engineering demonstrates a pioneering approach to solving pressing medical challenges. His work on CRISPR-based biosensing and AI-driven tools for disease detection has made significant contributions to the field.
  2. Diverse Publications: Dr. Ibrahim has an extensive list of publications in high-impact journals and conferences, showcasing his expertise across various aspects of biomedical engineering and bioinformatics. His work on COVID-19 detection using deep learning and CRISPR technology highlights his commitment to advancing medical technology.
  3. Awards and Recognition: The Best Young Scientist Award from Near East University and the Best Researcher Award from the International Academic Awards validate his contributions and excellence in research.
  4. Interdisciplinary Collaboration: His role in collaborative projects, such as the digital skills program with the European Union, and his contributions to the International Research Center for AI and IoT reflect his ability to work across disciplines and integrate diverse technological advancements into biomedical applications.

Areas for Improvement

  1. Broader Impact and Outreach: While Dr. Ibrahim’s research is highly specialized, expanding outreach efforts to increase the impact of his work in clinical settings or among non-specialist audiences could further enhance the application and visibility of his research.
  2. Research Diversity: Although Dr. Ibrahim has made substantial contributions in specific areas, diversifying his research to include other emerging fields in bioengineering and biomedical sciences could broaden his impact.
  3. Collaboration and Networking: Increasing collaborative efforts with international research institutions and industry partners could provide additional resources and opportunities for groundbreaking research and innovation.

Education

Dr. Abdullahi Umar Ibrahim earned his PhD in Biomedical Engineering from Near East University in 2021, following his MSc in Bioengineering from Cyprus International University (2016). His educational journey began with an OND & HND in Science Laboratory Technology from the Nigerian Institute of Leather & Science Technology, Zaria. His academic pursuits have been marked by a commitment to integrating cutting-edge technologies into bioengineering and biomedical research, establishing a strong foundation for his contributions to the field.

Experience

Dr. Ibrahim currently serves as the Assistant Head of the Biomedical Engineering Department and Internship Coordinator at Near East University. His previous roles include Research Assistant at the International Research Center for AI and IoT, and a Lecturer at Kaduna State University, where he taught various subjects related to biomedical and laboratory sciences. His extensive teaching experience covers a broad range of biomedical engineering topics, from biochemistry and molecular biology to biomedical signal processing and clinical engineering.

Awards and Honors

Dr. Ibrahim has received notable accolades for his contributions to the field. In 2022, he was honored with the Best Young Scientist Award at Near East University and the Best Researcher Award from the International Academic Awards. These awards recognize his outstanding research achievements and innovative work in biomedical engineering, particularly his advancements in CRISPR technology and AI-driven diagnostics.

Research Focus

Dr. Ibrahim’s research focuses on the integration of CRISPR technology and AI in biomedical applications. His work includes developing biosensors for disease detection, improving diagnostic tools using deep learning, and exploring the potential of AI and IoT in medicine. His research aims to advance the precision and efficiency of biomedical diagnostics and treatment, contributing to the broader field of bioengineering and medical technology.

Publications top notes

  1. CRISPR Biosensing and AI Driven Tools for Detection and Prediction of COVID-19 📘
  2. Pneumonia Classification Using Deep Learning from Chest X-ray Images During COVID-19 🩺
  3. Automated Detection of Mycobacterium Tuberculosis Using Transfer Learning 🦠
  4. Futuristic CRISPR-Based Biosensing in the Cloud and IoT Era: An Overview ☁️
  5. Convolutional Neural Network for Diagnosis of Viral Pneumonia and COVID-19 Alike Diseases 🤖
  6. CRISPR/Cas9 Gene Editing in Mammalian Cells Using LentiCRISPRv2/LentiGuide-Puro Vectors 🔬
  7. Detection of Tropical Diseases Caused by Mosquitoes Using CRISPR-Based Biosensors 🦟
  8. Computer Aided Detection of Tuberculosis Using Two Classifiers 🧬
  9. Current Technologies for Detection of COVID-19: Biosensors, AI and IoMT 🦠
  10. Large-Scaled Detection of COVID-19 from X-ray Using Transfer Learning 💻
  11. Computer-Aided Detection of Tuberculosis from Microbiological and Radiographic Images 🏥
  12. Deep Learning and Transfer Learning Models for Detection of COVID-19 🌐
  13. Recent Development of Electrochemical and Optical Aptasensors for Detection of Antibiotics in Food Monitoring Applications 📊
  14. Application of Crispr Technology for the Generation of Biofuels: A Review 🔋
  15. Comparative Study of Crispr-Cas9 and CRISPR Interference (CRISPRi) 🔍
  16. Analysis of Tocopherol Using Chromatographic and Electrochemical Techniques 🧪
  17. CRISPR Technology: Advantages, Limitations and Future Direction 📈

Conclusion

Dr. Abdullahi Umar Ibrahim is a strong candidate for the Best Researcher Award. His groundbreaking research in CRISPR technology and AI applications in medicine, combined with his significant publications and accolades, demonstrates his excellence and impact in the field. Addressing the areas for improvement, such as increasing the broader impact of his research and expanding collaborative networks, could further elevate his contributions. Overall, Dr. Ibrahim’s achievements and innovative approach make him a deserving candidate for this prestigious award.