A. F. M. Shahen Shah | Artificial Intelligence | Best Researcher Award

Assoc. Prof. Dr A. F. M. Shahen Shah | Artificial Intelligence | Best Researcher Award

Associate Professor at Yildiz Technical University, Turkey

Assoc. Prof. Dr. A. F. M. Shahen Shah is a distinguished academic and researcher in the Department of Electronics and Communication Engineering at Yildiz Technical University, Turkey. He is recognized as one of the World’s Top 2% Scientists by Stanford University and Elsevier (2023-2024), reflecting his exceptional contributions to research and academia. With extensive experience in teaching, project management, and interdisciplinary research, Dr. Shah’s work primarily focuses on next-generation communication systems, artificial intelligence, and disaster-resilient technologies. His leadership in multiple funded projects and innovative research underscores his commitment to advancing the field of electronics and communication engineering.

Professional Profile

Education

Dr. Shah completed his Ph.D. in Electronics and Communication Engineering at Yildiz Technical University in 2020, earning a CGPA of 3.75 and receiving a prestigious Gold Medal at ITEX. He holds a Master’s degree in Information Technology from the University of Dhaka, Bangladesh, where he ranked third in his batch with a CGPA of 3.85. His academic journey began with a Bachelor’s in Electronics and Telecommunication Engineering from Daffodil International University, Bangladesh, graduating at the top of his class with a CGPA of 3.96. His academic achievements highlight his unwavering commitment to excellence in learning and research.

Professional Experience

Dr. Shah’s professional career encompasses both academia and industry. He is currently an Associate Professor at Yildiz Technical University, where he has been teaching advanced undergraduate and graduate courses since 2021. He previously served as an Assistant Professor at Istanbul Gelisim University, specializing in wireless communication and artificial neural networks. Before transitioning to academia, Dr. Shah gained valuable industry experience as an IT professional in leading banks in Bangladesh, managing critical operations and support systems. His diverse career trajectory combines academic rigor with practical expertise, enabling him to bridge theory and real-world applications effectively.

Research Interests

Dr. Shah’s research interests lie in the realms of next-generation wireless communication systems, artificial intelligence, vehicular ad hoc networks (VANETs), and UAV-based disaster communication systems. He is particularly passionate about exploring the integration of intelligent reflecting surfaces and fluid antenna systems for 6G communication. His work also includes developing deep learning models for real-time sign language recognition and designing mobility-aware cooperative MAC protocols for VANETs. Dr. Shah’s innovative approach to addressing real-world challenges through advanced communication technologies reflects his dedication to impactful and forward-thinking research.

Research Skills

Dr. Shah possesses a diverse set of research skills, including expertise in designing and analyzing wireless communication systems, MIMO antenna systems, and deep learning-based applications. He is proficient in project management, having led multiple high-impact projects funded by TÜBİTAK and YTÜ-BAP. His technical expertise extends to developing and simulating advanced communication protocols, integrating artificial intelligence into communication systems, and optimizing network performance. With a strong foundation in programming, data analysis, and mathematical modeling, Dr. Shah excels in delivering innovative solutions to complex engineering problems.

Awards and Honors

Dr. Shah’s illustrious career has earned him several accolades, including recognition among the World’s Top 2% Scientists by Stanford University and Elsevier. He was awarded a Gold Medal in the 32nd ITEX for his outstanding Ph.D. research. Additionally, his academic excellence during his undergraduate and master’s studies earned him top rankings in his class. Dr. Shah’s consistent record of achievements in both research and academics highlights his profound impact on the field of electronics and communication engineering.

Conclusion 🤝

Assoc. Prof. Dr. A. F. M. Shahen Shah is a strong contender for the Best Researcher Award due to his remarkable academic credentials, global recognition, and leadership in innovative projects. With increased emphasis on publishing in high-impact journals, pursuing patents, and engaging broader audiences, he has the potential to further solidify his reputation as a leading researcher. His interdisciplinary expertise and proven project management skills make him an outstanding candidate for this prestigious recognition.

Publication Top Notes

  1. Survey and performance evaluation of multiple access schemes for next-generation wireless communication systems
    Authors: AFMS Shah, AN Qasim, MA Karabulut, H Ilhan, MB Islam
    Year: 2021
    Citations: 91
    Published in: IEEE Access 9, 113428-113442
  2. A survey from 1G to 5G including the advent of 6G: Architectures, multiple access techniques, and emerging technologies
    Authors: AFMS Shah
    Year: 2022
    Citations: 65
    Published in: 2022 IEEE 12th Annual Computing and Communication Workshop and Conference
  3. Internet of things and wireless sensor networks for smart agriculture applications-a survey
    Authors: MN Mowla, N Mowla, AFMS Shah, K Rabie, T Shongwe
    Year: 2023
    Citations: 62
    Published in: IEEE Access
  4. A survey on cooperative communication in wireless networks
    Authors: AFMS Shah, MS Islam
    Year: 2014
    Citations: 60
    Published in: International Journal of Intelligent Systems and Applications 6 (7), 66-78
  5. A secured privacy-preserving multi-level blockchain framework for cluster-based VANET
    Authors: AFMS Akhter, M Ahmed, AFMS Shah, A Anwar, A Zengin
    Year: 2021
    Citations: 55
    Published in: Sustainability 13 (1), 400
  6. CB-MAC: A novel cluster-based MAC protocol for VANETs
    Authors: AFM Shahen Shah, H Ilhan, U Tureli
    Year: 2019
    Citations: 53
    Published in: IET Intelligent Transport Systems 13 (4), 587-595
  7. RECV-MAC: A novel reliable and efficient cooperative MAC protocol for VANETs
    Authors: AFM Shahen Shah, H Ilhan, U Tureli
    Year: 2019
    Citations: 43
    Published in: IET Communications 13 (16), 2541-2549
  8. Inspecting VANET with various critical aspects–a systematic review
    Authors: MA Karabulut, AFMS Shah, H Ilhan, ASK Pathan, M Atiquzzaman
    Year: 2023
    Citations: 41
    Published in: Ad Hoc Networks, 103281
  9. A blockchain-based emergency message transmission protocol for cooperative VANET
    Authors: M Ahmed, N Moustafa, AFMS Akhter, I Razzak, E Surid, A Anwar, …
    Year: 2021
    Citations: 38
    Published in: IEEE Transactions on Intelligent Transportation Systems 23 (10), 19624-19633
  10. A blockchain-based authentication protocol for cooperative vehicular ad hoc network
    Authors: AFMS Akhter, M Ahmed, AFMS Shah, A Anwar, ASM Kayes, A Zengin
    Year: 2021
    Citations: 37
    Published in: Sensors 21 (4), 1273

 

Liangyu Yin | Artificial Intelligence | Best Researcher Award

Dr. Liangyu Yin | Artificial Intelligence | Best Researcher Award

Research Professor at Xinqiao Hospital, Army Medical University, China

Dr. Liangyu Yin is an accomplished academic and researcher specializing in clinical nutrition, epidemiology, and artificial intelligence. He has made significant contributions to understanding cancer nutrition and malnutrition, particularly in oncology patients. His expertise spans the intersection of nutrition, cancer biology, and advanced machine learning methodologies. With numerous publications in prestigious journals such as Journal of Cachexia Sarcopenia Muscle, American Journal of Clinical Nutrition, and Clinical Nutrition, Dr. Yin is recognized as a thought leader in his field. He is currently a Research Professor at the Department of Nephrology, Xinqiao Hospital, Army Medical University, where he continues to advance research on cancer cachexia, nutritional interventions, and artificial intelligence applications. His work is aimed at improving patient outcomes, especially for cancer patients, by utilizing innovative research methods, including AI-driven diagnostics and predictive models for malnutrition and cancer prognosis.

Professional Profile

Education:

Dr. Liangyu Yin’s educational journey is marked by a strong foundation in medicine and nutrition. He earned his Ph.D. in Nutrition and Food Hygiene from Army Medical University in 2022, following a Master of Medicine in Nutrition and Food Hygiene from Chongqing Medical University in 2012. His academic journey began with a Bachelor of Arts degree in English, specializing in Biomedical English, from Chongqing Medical University. This diverse educational background has provided him with a robust understanding of both medical and nutritional sciences, which he applies in his research. His ongoing contributions reflect his dedication to bridging clinical nutrition with the latest advancements in artificial intelligence and cancer epidemiology.

Professional Experience:

Dr. Liangyu Yin’s professional experience spans several prestigious roles in academic research, clinical settings, and health science institutions. He currently serves as a Research Professor in the Department of Nephrology at Xinqiao Hospital, Army Medical University. Previously, he held positions as an Associate Research Professor at both Daping Hospital and Southwest Hospital within the Army Medical University, focusing on cancer epidemiology, nutrition, and artificial intelligence. Dr. Yin began his research career as a Research Assistant at the Institute of Hepatobiliary Surgery, Southwest Hospital, where he worked on cancer biology and non-coding RNA. His long-standing career at Army Medical University has contributed to the development of novel methodologies and interventions in clinical nutrition and cancer treatment. His expertise in epidemiology, nutrition, and AI has shaped the direction of his research in improving patient care outcomes.

Research Interests:

Dr. Liangyu Yin’s primary research interests lie at the intersection of clinical nutrition, cancer epidemiology, and artificial intelligence. His work focuses on understanding the role of malnutrition in cancer progression, with a particular emphasis on cancer cachexia, a complex metabolic syndrome associated with cancer. Dr. Yin is dedicated to developing predictive models and AI-driven solutions to identify and address malnutrition in cancer patients, improving patient outcomes and survival rates. His research also investigates non-coding RNA and its role in cancer biology, with a focus on its potential applications in cancer treatment. Through his interdisciplinary approach, combining machine learning with clinical nutrition, Dr. Yin aims to revolutionize cancer care by improving diagnosis, prognosis, and nutritional interventions in clinical practice.

Research Skills:

Dr. Liangyu Yin possesses a diverse set of research skills, enabling him to conduct cutting-edge investigations in the fields of clinical nutrition, cancer epidemiology, and artificial intelligence. His proficiency in utilizing machine learning models to predict and diagnose malnutrition in cancer patients demonstrates his technical expertise. Additionally, Dr. Yin’s deep understanding of cancer biology, especially cancer cachexia and non-coding RNA, is critical to his work. His research skills also extend to conducting large-scale cohort studies and multicenter analyses, as evidenced by his numerous publications. Moreover, his ability to integrate AI with clinical nutrition research allows him to pioneer innovative solutions in medical diagnostics and patient care, making him a leader in his field.

Awards and Honors:

Dr. Liangyu Yin has received numerous accolades and honors for his contributions to clinical nutrition and cancer research. His work has been consistently recognized in prestigious academic journals, and his research has influenced global medical practices regarding nutrition in cancer care. Dr. Yin’s expertise in combining artificial intelligence with nutrition science has earned him several recognitions for innovation in healthcare. He is a highly regarded researcher within the medical and scientific community, regularly invited to present his findings at international conferences and to collaborate on advanced research projects. His commitment to improving cancer patient outcomes through his interdisciplinary research has made him a prominent figure in his field.

Conclusion:

Liangyu Yin is an outstanding candidate for the Best Researcher Award. His research in clinical nutrition, cancer epidemiology, and the innovative use of artificial intelligence sets him apart as a leader in his field. His work has made significant strides in understanding malnutrition and cancer cachexia, with implications for improving patient care. By expanding the scope of his research and enhancing the real-world application of his findings, he has the potential to make an even greater impact on global health. Therefore, he is highly deserving of this award, and his future contributions will continue to shape the field of clinical nutrition and cancer care.

Publication Top Notes:

  1. Early prediction of severe acute pancreatitis based on improved machine learning models
    • Authors: Li, L., Yin, L., Chong, F., Wang, Y., Xu, H.
    • Journal: Journal of Army Medical University
    • Year: 2024
    • Volume: 46(7)
    • Pages: 753–759
  2. Association of possible sarcopenia with all-cause mortality in patients with solid cancer: A nationwide multicenter cohort study
    • Authors: Yin, L., Song, C., Cui, J., Shi, H., Xu, H.
    • Journal: Journal of Nutrition, Health and Aging
    • Year: 2024
    • Volume: 28(1)
    • Article ID: 100023
    • Citations: 3
  3. Comment on: “Triceps skinfold-albumin index significantly predicts the prognosis of cancer cachexia: A multicentre cohort study” by Yin et al. – the authors reply
    • Authors: Yin, L., Cui, J., Lin, X., Shi, H., Xu, H.
    • Journal: Journal of Cachexia, Sarcopenia and Muscle
    • Year: 2023
    • Volume: 14(6)
    • Pages: 2993–2994
  4. Comparison of the performance of the GLIM criteria, PG-SGA and mPG-SGA in diagnosing malnutrition and predicting survival among lung cancer patients: A multicenter study
    • Authors: Huo, Z., Chong, F., Yin, L., Shi, H., Xu, H.
    • Journal: Clinical Nutrition
    • Year: 2023
    • Volume: 42(6)
    • Pages: 1048–1058
    • Citations: 6
  5. Ensemble learning system to identify nutritional risk and malnutrition in cancer patients without weight loss information
    • Authors: Yin, L., Liu, J., Liu, M., Shi, H., Xu, H.
    • Journal: Science China Life Sciences
    • Year: 2023
    • Volume: 66(5)
    • Pages: 1200–1203
  6. Kruppel-like Factors 3 Regulates Migration and Invasion of Gastric Cancer Cells Through NF-κB Pathway
    • Authors: Liang, X., Feng, Z., Yan, R., Lu, H., Zhang, L.
    • Journal: Alternative Therapies in Health and Medicine
    • Year: 2023
    • Volume: 29(2)
    • Pages: 64–69
    • Citations: 1
  7. Triceps skinfold–albumin index significantly predicts the prognosis of cancer cachexia: A multicentre cohort study
    • Authors: Yin, L., Cui, J., Lin, X., Shi, H., Xu, H.
    • Journal: Journal of Cachexia, Sarcopenia and Muscle
    • Year: 2023
    • Volume: 14(1)
    • Pages: 517–533
    • Citations: 5

 

 

Marcelo Vasconcelos | Artificial Intelligence | Best Researcher Award

Mr. Marcelo Vasconcelos | Artificial Intelligence | Best Researcher Award

IT Auditor at Court of Auditors of the Federal District, Brazil

Marcelo Oliveira Vasconcelos is a seasoned professional and researcher from Brasília, Brazil, with over two decades of experience across public administration, financial auditing, and technology-based risk management. Currently pursuing a Ph.D. in Web Science and Technology, Marcelo’s expertise spans various roles, including Financial and External Control Analyst at the Tribunal de Contas do Distrito Federal (TCDF). He holds multiple certifications, such as Certified Information Systems Auditor (CISA) and Risk Management Professional (ISO 31000:2018). His research focuses on enhancing corruption risk assessments in public administration using advanced data science methods, making him a prominent figure in the application of technology for public sector improvements. Proficient in Portuguese, English, and Spanish, Marcelo brings a global perspective to his work, bolstered by leadership training from École Nationale d’Administration (ENA) in France. His contributions, such as his recent publications on artificial intelligence applications in public administration, underscore his commitment to advancing effective governance practices through data-driven insights and innovative methodologies.

Professional Profile

Education

Marcelo Vasconcelos has a comprehensive academic background that blends technology, law, and public administration. He is currently a Ph.D. candidate in Web Science and Technology at the University of Trás-os-Montes e Alto Douro (UTAD), Portugal, which builds on his Master’s degree in Computer Science from the University of Brasília, completed in 2020. His formal education is supplemented by a range of specialized qualifications: an MBA in Public Law from Instituto Processus and another in Constitutional Law from Instituto de Direito Público, Brasília. Marcelo also holds a Bachelor’s degree in Public Administration from the State University of Goiás and an undergraduate degree in Science from UniCEUB Brasília. His academic trajectory is further complemented by international training in leadership and public management from École Nationale d’Administration (ENA) in France, which has enriched his expertise in governmental processes and administration. Marcelo’s educational journey reflects a balanced combination of technical expertise, public policy, and governance, aligning with his goal to leverage data science for practical solutions in public administration.

Professional Experience

Marcelo Vasconcelos has accumulated diverse professional experience, with a primary focus on public sector auditing and analysis. Since August 2004, he has served as a Financial and External Control Analyst at the Tribunal de Contas do Distrito Federal (TCDF), where he applies his expertise in data auditing, fraud detection, and risk management to enhance public accountability. Previously, he held various roles, including Social Security Tax Auditor at the National Social Security Institute (INSS) from 2003 to 2004, and Foreign Trade Analyst at the Secretariat of Foreign Trade, where he honed his skills in regulatory compliance and policy analysis. His early career also includes work as a Federal Revenue Analyst for the Secretariat of Federal Revenue and as a Teacher of Science and Mathematics in the Federal District’s Secretariat of Education. Marcelo’s professional journey reflects a commitment to strengthening governance and public sector efficiency, leveraging both his analytical and technological skills to contribute to Brazil’s federal and financial control sectors.

Research Interest

Marcelo’s primary research interest lies in the intersection of data science, public administration, and ethics, particularly in using technology to tackle corruption and enhance governance transparency. His research explores the application of artificial intelligence and machine learning to identify and mitigate risks associated with public administration processes. Notably, Marcelo has focused on creating models that assess corruption risk in public administration, emphasizing the development of imbalanced learning techniques to improve accuracy in risk detection. His work, such as his study on mitigating false negatives in imbalanced datasets, aligns with his commitment to data-driven governance reforms. In addition, Marcelo’s interest extends to Web Science and the application of large datasets for public decision-making. By advancing methodologies that blend computer science with public policy, he seeks to bridge gaps in data application and ethical governance, positioning his research within the broader movement of responsible AI in public services.

Research Skills

Marcelo Vasconcelos brings a robust skill set to his research, particularly in data analytics, risk assessment, and machine learning applications in public administration. He is proficient in using artificial intelligence techniques, specifically imbalanced learning methods, to enhance the reliability of corruption risk models. His technical skills extend to using Control Objectives for Information and Related Technologies (COBIT 5) and ISO 31000:2018 standards for risk management. Marcelo is certified as a Certified Information Systems Auditor (CISA), which bolsters his skills in cybersecurity and information systems auditing. His analytical expertise is complemented by his experience in developing ensemble approaches to minimize errors in data models. Marcelo also brings practical knowledge in data governance and policy application, supported by his academic research, which is published in journals like Expert Systems with Applications and Data in Brief. These skills position him as a research-driven professional with advanced capabilities in designing, implementing, and evaluating technology-based solutions for complex public sector challenges.

Awards and Honors

While Marcelo’s curriculum does not explicitly mention awards, his achievements reflect recognition through certifications and high-impact publications. His certifications, including CISA and ISO 31000:2018 for risk management, demonstrate his commitment to maintaining industry standards and developing expertise in information systems and public sector accountability. Marcelo’s acceptance of his work in respected journals, such as Data in Brief and Expert Systems with Applications, further highlights his research contributions. His participation in leadership training at the prestigious École Nationale d’Administration (ENA) also underscores his standing as a thought leader in the public sector. By achieving a high level of proficiency in his certifications and continuing professional development, Marcelo has positioned himself as a well-regarded expert in his field, aligning with the standards expected for research awards in public administration and technology applications.

Conclusion

Marcelo Vasconcelos demonstrates a robust profile for the Best Researcher Award, combining practical public sector expertise with advanced research in technology and data analytics. His work in assessing corruption risk through imbalanced learning models addresses critical issues, showcasing his contribution to public administration and AI fields. Strengthening his academic engagement and expanding his research scope could enhance his candidacy further, positioning him as a well-rounded researcher with substantial contributions to his field.

Publication Top Notes

  • Title: Mitigating False Negatives in Imbalanced Datasets: An Ensemble Approach
    • Publication: Expert Systems with Applications
    • Year: 2025
    • DOI: 10.1016/j.eswa.2024.125674
    • Authors: Marcelo Vasconcelos, Luís Cavique
  • Title: Dataset for Corruption Risk Assessment in a Public Administration
  • Title: Imbalanced Learning in Assessing the Risk of Corruption in Public Administration
    • Publication: Book Chapter in Imbalanced Learning in Assessing the Risk of Corruption in Public Administration
    • Year: 2021
    • DOI: 10.1007/978-3-030-86230-5_40
    • Authors: Marcelo Oliveira Vasconcelos, Ricardo Matos Chaim, Luís Cavique

 

Karimeh Ata | Artificial Intelligence | Best Researcher Award

Dr. Karimeh Ata | Artificial Intelligence | Best Researcher Award

Researcher at UPM, Jordan

Dr. Karimeh Ata is a Computer and Artificial Intelligence Engineering Ph.D. candidate at Universiti Putra Malaysia (UPM), specializing in deep learning and big data analytics for urban mobility and vehicle flow optimization. With a strong academic foundation, she holds a Master’s degree in Computer Engineering and Embedded Systems from UPM and a Bachelor’s degree in Computer Engineering from Fahad Bin Sultan University, Saudi Arabia, where she graduated with first-class honors. Dr. Ata’s research focuses on solving complex problems using advanced algorithms like Dijkstra’s and Ant Colony Optimization, contributing to various high-impact projects. In addition to her academic achievements, she has experience as an AI trainer and lecturer, and her work is highlighted by numerous publications in top-tier journals and conferences. Proficient in technologies like Microsoft Azure, GIS, Python, and Raspberry Pi, Dr. Ata is committed to driving innovation in the fields of artificial intelligence and computer engineering.

Profile

Education

Dr. Karimeh Ata is currently pursuing her Ph.D. in Computer Engineering and Artificial Intelligence at Universiti Putra Malaysia (UPM), with an expected completion in June 2024. Her doctoral research focuses on traffic flow prediction using deep learning and big data analysis, and she has maintained an outstanding GPA of 4.00 throughout her studies. Prior to this, she earned a Master of Computer Engineering and Embedded Systems from UPM in 2019, where she addressed challenges in vehicle navigation and parking optimization using algorithms like Dijkstra’s and Ant Colony Optimization, achieving a GPA of 3.57. Dr. Ata holds a Bachelor of Computer Engineering from Fahad Bin Sultan University (FBSU) in Saudi Arabia, where she graduated with first-class honors and a GPA of 4.91, also receiving the Prince Fahad Bin Sultan Scholarship for academic excellence.

Professional Experience

Dr. Karimeh Ata has a diverse range of professional experience in the fields of artificial intelligence and computer engineering. From December 2018 to January 2020, she served as an Artificial Intelligence Trainer at Hass Resources Corporation in Malaysia, where she supervised and trained teams on AI applications in education. In early 2019, she was a member of the Technical Committee for the Symposium on Control Systems and Signal Processing in Malaysia, bringing together experts to discuss advancements in AI, signal processing, and control systems. Dr. Ata has also contributed to academia as a Computer Engineering Lecturer at Universiti Putra Malaysia (UPM) from November 2022 to September 2023, where she designed and delivered courses on subjects such as Programming Fundamentals, Digital Logic Design, and Machine Learning, while also supervising laboratory sessions. Additionally, she worked as a Research Assistant at UPM from July 2021 to October 2022, where she ensured the quality, integrity, and security of research data and guided teams in preparing findings for top-tier journals and conferences. Dr. Ata’s professional experience highlights her leadership in project management, research ethics, and AI integration.

Research Interest

Dr. Karimeh Ata’s research interests focus on leveraging advanced technologies to address complex challenges in urban mobility, traffic flow optimization, and artificial intelligence. Her work primarily centers around deep learning and big data analytics, with a particular emphasis on traffic flow prediction and vehicle optimization. She has explored algorithms such as Dijkstra’s and Ant Colony Optimization to calculate the shortest paths and improve transportation efficiency in urban environments. Additionally, Dr. Ata is interested in applying AI-driven solutions to enhance brain stroke detection, lithium iron phosphate battery electrode performance, and spatial-temporal traffic flow prediction through multi-layer models. Her research aims to innovate in fields like smart transportation systems, deep learning, and AI for real-world problem-solving.

Research Skills

Dr. Karimeh Ata possesses extensive research skills in deep learning, big data analytics, and artificial intelligence, with a focus on solving complex problems in urban mobility and traffic flow optimization. She is proficient in designing and implementing deep learning models for traffic prediction and vehicle flow using large datasets to ensure accuracy. Dr. Ata has expertise in optimizing algorithms such as Dijkstra’s and Ant Colony Optimization to calculate efficient paths in transportation networks. Her research capabilities extend to developing innovative AI models for brain stroke detection and lithium battery performance evaluation, along with spatial-temporal data analysis using advanced machine learning techniques like CNN-GRU and dynamic KNN-Bi-LSTM. Dr. Ata’s skills reflect a deep understanding of integrating AI into real-world applications.

Award and Recognition

Dr. Karimeh Ata has been recognized for her academic excellence and contributions to research in the fields of computer engineering and artificial intelligence. She was awarded the prestigious Prince Fahad Bin Sultan Scholarship during her undergraduate studies for her outstanding academic performance, graduating with a first honor distinction. Additionally, her research work has been acknowledged through notable publications in top-tier journals, reflecting her deep expertise in areas such as traffic flow prediction and smart indoor parking systems. Dr. Ata’s achievements underscore her commitment to advancing the field of AI and computer engineering through innovative research and impactful projects.

Conclusion

Given Dr. Karimeh Ata’s strong academic background, innovative research contributions, and extensive skills in AI and big data, she is a suitable candidate for the Best Researcher Award. Her work not only demonstrates technical proficiency but also showcases her ability to solve complex, real-world problems, making a significant impact in the field of AI and computer engineering.

Publications Top Notes

  • Title: Smart Indoor Parking System Based on Dijkstra’s Algorithm
    Authors: K.M. Ata, A.C. Soh, A. Ishak, H. Jaafar, N. Khairuddin
    Cited By: 19
    Year: 2019
  • Title: Performance Evaluation of Two Mobile Ad-hoc Network Routing Protocols: Ad-hoc On-Demand Distance Vector Dynamic Source Routing
    Authors: J. Alamri, A.S. Al-Johani, K.I. Ata
    Cited By: 13
    Year: 2020
  • Title: Radio Frequency Identification (RFID) Indoor Parking Control System
    Authors: H.M.M. El-Hageen, K. Ibrahim, M. Ata, A. Chesoh, H. Jaafar
    Cited By: 3
    Year: 2017
  • Title: A Smart Guidance Indoor Parking System Based on Dijkstra’s Algorithm and Ant Colony Algorithm
    Authors: K.I. Ata, A.C. Soh, A.J. Ishak, H. Jaafar
    Cited By: 1
    Year: 2020
  • Title: Investigation of Loading Variation Effect on Lithium Iron Phosphate Battery Electrodes Using Long Short Term Memory
    Authors: K.A.A. Md Azizul Hoque, Mohd Khair Hassan, Muhesh Dhaarwind, Abdulrahman Hajjo
    Year: 2024
  • Title: Enhancing Brain Stroke Detection: A Novel Deep Neural Network with Weighted Binary Cross Entropy Training
    Authors: A.N. Qasim, S. Alani, S.N. Mahmood, S.S. Mohammed, D.A. Aziz, K.I.M. Ata
    Year: 2024
  • Title: Guidance System Based on Dijkstra-Ant Colony Algorithm with Binary Search Tree for Indoor Parking System
    Authors: H.J. K. Ibrahim Ata, A. Che Soh, A.J. Ishak
    Year: 2021