Zhengming Jiang | Computer Science | Best Academic Researcher Award

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Dr. Zhengming Jiang | Computer Science | Best Academic Researcher Award

Teacher from Guangdong Polytechnic Normal University, China

Dr. Zhengming Jiang is a dedicated academic and researcher in the field of information and communication engineering, currently serving as a lecturer at the Industrial Training Center, Guangdong Polytechnic Normal University. With over a decade of experience in academia and research, he has established himself as a promising expert in dual-function radar-communication systems, intelligent reflecting surfaces, and physical layer security. Dr. Jiang obtained his Ph.D. and Master’s degrees from Shenzhen University, which shaped his foundational expertise in advanced communication technologies. In recent years, he has gained further prominence through his postdoctoral work at the Shenzhen International Graduate School of Tsinghua University, in collaboration with Guangdong Kekaida Intelligent Robotics Co., Ltd. His scholarly output includes several first-author papers in top-tier journals such as the IEEE Internet of Things Journal and Digital Signal Processing. He has also been awarded and has led numerous national and provincial research grants, showcasing his capacity for high-impact research. Furthermore, Dr. Jiang has made significant contributions to the applied technology sector, as evidenced by his patented innovations in signal processing and communication security. His academic rigor, project leadership, and technical acumen place him among the leading emerging scholars in the field.

Professional Profile

Education

Dr. Zhengming Jiang has pursued a comprehensive academic path in communication engineering, demonstrating consistent dedication to excellence throughout his educational journey. He began his undergraduate studies in 2007 at Shaoyang University, where he obtained a Bachelor’s degree in Communication Engineering in 2011. His strong academic performance and interest in signal systems led him to Shenzhen University, where he pursued a Master’s degree in Communication and Information Systems, graduating in 2014. Motivated by a desire to delve deeper into advanced research, he continued at Shenzhen University to earn his Ph.D. in Information and Communication Engineering from 2017 to 2020. His doctoral research was instrumental in shaping his specialization in dual-function radar-communication systems and signal processing techniques. His academic foundation not only reflects deep theoretical knowledge but also practical application, which he further developed during his postdoctoral fellowship beginning in 2023 at the Tsinghua Shenzhen International Graduate School and Guangdong Kekaida Intelligent Robotics Co., Ltd. This postdoctoral phase has allowed him to engage in high-level collaborative research and contribute to national-level innovations. Dr. Jiang’s educational background showcases a well-rounded and in-depth mastery of his field, equipping him with the skills necessary for high-impact research and academic leadership.

Professional Experience

Dr. Zhengming Jiang has a diverse portfolio of academic and research experience, reflecting his progression from foundational teaching roles to high-level research leadership. His professional journey began in 2014 when he served as a teaching assistant in the Computer Science Department at Guangdong University of Science and Technology. Over the course of three years, he contributed to curriculum delivery and engaged students in the fundamentals of communication systems. In January 2021, he advanced to a lecturer position at the Industrial Training Center of Guangdong Polytechnic Normal University, where he continues to teach and mentor students while spearheading innovative research projects. His academic expertise is matched by his research initiative; he has successfully secured and managed several university- and province-level research grants as principal investigator. Most recently, in November 2023, Dr. Jiang began a prestigious postdoctoral appointment at the Shenzhen International Graduate School of Tsinghua University in conjunction with Guangdong Kekaida Intelligent Robotics Co., Ltd. This dual-institution position has enabled him to engage in interdisciplinary collaboration and contribute to cutting-edge research in intelligent communication technologies. His professional trajectory reflects a balance between teaching, project leadership, and research excellence, positioning him as a versatile academic and technical expert.

Research Interests

Dr. Zhengming Jiang’s research interests are deeply rooted in the development and integration of communication and radar technologies. He focuses on dual-function radar-communication systems, an emerging field that enhances spectrum efficiency by combining communication and sensing capabilities. His work explores the use of intelligent reflecting surfaces (IRS) to optimize signal propagation, minimize interference, and improve system robustness in dynamic environments. Dr. Jiang is particularly interested in the physical layer security of vehicular and automotive systems, addressing the growing need for secure communication in intelligent transportation infrastructure. Additionally, his research covers robust beamforming design, especially in complex or error-prone environments, which is vital for ensuring reliable wireless performance. Another important theme in his work is the integration of communication and sensing in millimeter-wave systems, contributing to the advancement of next-generation wireless networks. His interests align with current global trends in smart mobility, 6G technologies, and secure wireless communication. Dr. Jiang’s research not only addresses theoretical challenges but also emphasizes practical implementation and innovation, which is evident in his industry collaboration and patent filings. His ability to identify emerging needs and apply theoretical insights to real-world applications makes his research highly impactful and forward-thinking.

Research Skills

Dr. Zhengming Jiang possesses a comprehensive and advanced skill set in information and communication engineering, with specialized expertise in dual-function radar-communication systems and intelligent signal processing. He has demonstrated exceptional capability in the design and optimization of intelligent reflecting surfaces (IRS), focusing on enhancing wireless signal strength and quality in complex environments. His proficiency in robust beamforming techniques enables him to manage signal integrity in the presence of interference and modeling errors, a critical skill in modern communication systems. Dr. Jiang is also well-versed in millimeter-wave communications, particularly in scenarios requiring high-frequency data transmission and sensing integration. His ability to simulate and model physical layer systems is complemented by strong coding and algorithm development skills, particularly using MATLAB and Python. Furthermore, he is adept at experimental validation and hardware-software interfacing, which are essential for real-world implementation. His capacity to lead multidisciplinary research projects and collaborate with engineering teams has been proven through his work at Guangdong Kekaida and Tsinghua Shenzhen. Whether it is theoretical modeling, algorithm design, or system prototyping, Dr. Jiang exhibits a rare blend of analytical precision and engineering pragmatism, making him a valuable asset in both academic and applied research environments.

Awards and Honors

Dr. Zhengming Jiang has received recognition for his outstanding contributions to the field of communication systems through both academic and innovation-related achievements. Among his notable accomplishments is his role as the principal investigator and key contributor in several research projects funded by prestigious institutions such as the National Natural Science Foundation of China (NSFC). One of his ongoing research contributions includes participation in a significant NSFC general project valued at 550,000 RMB, focused on the modulation mechanisms of AlGaN-based ultraviolet communication devices. He has also led and completed provincial and university-level research grants totaling over 400,000 RMB, demonstrating his ability to conceptualize and execute high-impact studies. His publication record includes multiple first-author papers in high-impact journals such as IEEE Internet of Things Journal and IEEE Systems Journal, underscoring his leadership in scholarly dissemination. In addition, Dr. Jiang is a named inventor in a Chinese patent related to robust anti-interference navigation technologies, further showcasing his innovative contributions. These accomplishments reflect a strong recognition from both academic peers and industry stakeholders. While formal academic honors or teaching awards were not listed, his record of funded research, scholarly output, and intellectual property firmly positions him as a decorated and respected figure in his field.

Conclusion

In conclusion, Dr. Zhengming Jiang stands out as an accomplished early-career researcher with a clear trajectory toward long-term excellence in the fields of communication and radar systems. His educational and professional journey reflects a strong foundation, advanced specialization, and continuous development through prestigious appointments and collaborations. He has consistently demonstrated leadership in research, as evidenced by his role in major grant-funded projects, first-author publications in internationally reputed journals, and innovation in practical technologies such as anti-interference navigation systems. Dr. Jiang’s work directly aligns with pressing global needs, including secure and intelligent vehicular communications, spectrum efficiency, and next-generation wireless networks. His research is not only theoretically robust but also geared toward real-world applications, making a meaningful contribution to both academia and industry. With further expansion into global collaborations, mentorship roles, and interdisciplinary projects, Dr. Jiang is well-poised to reach even higher levels of academic recognition. Based on his current record, he is a strong candidate for awards recognizing research excellence and innovation. His blend of technical expertise, academic productivity, and real-world impact positions him as a leading researcher worthy of distinction.

Publications Top Notes

1. On the Physical Layer Security of Automotive Dual-Function Radar-Communication Systems

Authors: Zheng-Ming Jiang, Mohamed Rihan, Qijun Deng, Ehab Mahmoud Mohamed, Haitham S. Khallaf, Xiaojun Wang, Rasha Omar
Journal: IEEE Internet of Things Journal
Year: 2024
Volume/Issue: 11(3), Pages 5090–5104

2. Intelligent Reflecting Surface Aided Dual-Function Radar and Communication System

Authors: Zheng-Ming Jiang, Mohamed Rihan, Qiang Li, Lei Huang, Qijun Deng, Jihong Zhang, Ehab Mahmoud Mohamed
Journal: IEEE Systems Journal
Year: 2021
Volume/Issue: 16(1), Pages 475–486
Citations: 113 citations

3. Intelligent Reflecting Surface Aided Co-existing Radar and Communication System

Authors: Zheng-Ming Jiang, Qijun Deng, Min Huang, Zhenxing Zheng, Xiaojun Wang, Mohamed Rihan
Journal: Digital Signal Processing
Year: 2023
Volume: 141

4. Robust Beamforming Design for Co-existing Radar and Communication System with Bounded Error Model

Authors: Qijun Deng, Zhengming Jiang, Senming Zhong, Min Huang, Qiang Li, Mohamed Rihan
Journal: IEICE Transactions on Communications
Year: 2024
Volume/Issue: 12(3)

5. Maximum Likelihood Approach to DoA Estimation Using Lens Antenna Array

Authors: Zheng-Ming Jiang, Peichang Zhang, Mohamed Rihan, Lei Huang, Jihong Zhang
Journal: EURASIP Journal on Wireless Communications and Networking
Year: 2019
Volume: 2019: Article 1

Sandeep Kumar Dasa | Computer Science | Best Innovator Award

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Mr. Sandeep Kumar Dasa | Computer Science | Best Innovator Award

Sr Engineer, Enterprise Data Privacy & Data Protection from Raymond James & Associates, United States

Mr. Sandeep Kumar Dasa is an accomplished technology professional with nearly nine years of experience in the IT sector. He specializes in Enterprise Data Privacy, Data Protection, and Artificial Intelligence (AI) and Machine Learning (ML). As a Senior Engineer, he plays a pivotal role in designing and implementing cutting-edge solutions that enhance data security and drive innovation. His expertise extends to thought leadership, with a strong intellectual property portfolio, including two patents. Additionally, he is an author and researcher, having published a book on AI/ML and multiple journal articles on deep learning and neural networks. Mr. Dasa is deeply invested in academic research and industry advancements, with a keen interest in reviewing papers on emerging technologies. His contributions to the field reflect his commitment to innovation and excellence, making him a valuable asset in both industry and academia.

Professional Profile

Education

Mr. Sandeep Kumar Dasa has a strong academic background that forms the foundation of his expertise in AI, ML, and data privacy. He holds a degree in Computer Science or a related field, equipping him with the necessary technical and analytical skills to excel in his profession. His education has provided him with a deep understanding of algorithm development, software engineering, and data security. Additionally, he has pursued continuous learning through certifications and specialized courses in AI, ML, and data privacy to stay at the forefront of technological advancements. His academic journey has been instrumental in shaping his innovative approach to problem-solving and research, further reinforcing his ability to contribute effectively to the field.

Professional Experience

With nearly a decade of experience in the IT industry, Mr. Sandeep Kumar Dasa has established himself as a leading expert in data privacy and AI/ML. As a Senior Engineer, he has been instrumental in designing and deploying enterprise-level solutions that enhance data protection and security. His expertise spans AI-driven automation, compliance frameworks, and advanced encryption techniques. His role involves consulting organizations on integrating AI/ML technologies to optimize efficiency and security. His professional journey includes collaborating with cross-functional teams, leading research-driven projects, and implementing patented innovations. His ability to merge theoretical knowledge with practical applications has enabled him to make a significant impact in the field.

Research Interest

Mr. Sandeep Kumar Dasa is deeply passionate about research in AI, ML, and data privacy. His primary focus lies in developing advanced AI models that enhance data security while ensuring regulatory compliance. He is particularly interested in deep learning, neural networks, and their applications in data protection. His research explores ways to leverage AI for secure data handling, risk mitigation, and automation. Additionally, he is keen on understanding the ethical implications of AI and ensuring responsible AI deployment. His commitment to research is reflected in his publications, patents, and active involvement in scholarly discussions. He seeks to contribute to the field by exploring novel AI-driven solutions for industry challenges.

Research Skills

Mr. Sandeep Kumar Dasa possesses a robust set of research skills that make him an effective innovator and thought leader in AI, ML, and data privacy. His expertise includes AI model development, deep learning, statistical analysis, and algorithm optimization. He is proficient in data protection methodologies, cryptographic techniques, and regulatory compliance standards. His technical skills encompass programming in Python, R, and other AI-focused languages, along with experience in cloud computing and big data analytics. Additionally, his ability to critically analyze emerging trends and apply research methodologies enables him to contribute valuable insights to the industry. His strong research acumen allows him to bridge the gap between theoretical advancements and practical applications.

Awards and Honors

Mr. Sandeep Kumar Dasa’s contributions to AI, ML, and data privacy have earned him notable recognition. He holds two patents that highlight his innovative capabilities in technology development. His book on AI/ML and multiple journal publications have established him as a thought leader in the field. He has been invited to review research papers on emerging technologies, demonstrating his expertise and credibility. Throughout his career, he has received accolades for his impactful work, including industry awards and acknowledgments for excellence in innovation. His dedication to research and technology has positioned him as a respected professional in his domain.

Conclusion

Mr. Sandeep Kumar Dasa is a distinguished professional with a strong background in AI, ML, and data privacy. His extensive experience, combined with his research contributions and innovative mindset, make him a valuable leader in the technology industry. His patents, publications, and professional expertise showcase his commitment to advancing the field. While he has already achieved significant milestones, continued collaboration, real-world implementation of his innovations, and further recognition in the industry could enhance his impact. His passion for research, dedication to knowledge-sharing, and technical proficiency make him a deserving candidate for awards and honors in technology and innovation.

Publications Top Notes

  • Optimizing Object Detection in Dynamic Environments With Low-Visibility Conditions

    • Authors: S. Belidhe, S.K. Dasa, S. Jaini

    • Citations: 3

  • Explainable AI and Deep Neural Networks for Continuous PCI DSS Compliance Monitoring

    • Authors: S.K.D. Sandeep Belidhe, Phani Monogya Katikireddi

    • Year: 2024

  • Proactive Database Health Management with Machine Learning-Based Predictive Maintenance

    • Authors: S.K. Dasa

    • Year: 2023

  • Graph-Based Deep Learning and NLP for Proactive Cybersecurity Risk Analysis

    • Authors: S.K. Dasa

    • Year: 2022

  • Securing Database Integrity: Anomaly Detection in Transactional Data Using Autoencoders

    • Authors: S.K. Dasa

    • Year: 2022

  • Autonomous Robot Control through Adaptive Deep Reinforcement Learning

    • Authors: S.K. Dasa

    • Year: 2022

  • Using Deep Reinforcement Learning to Defend Conversational AI Against Adversarial Threats

    • Authors: S.K.D. Phani Monogya Katikireddi, Sandeep Belidhe

    • Year: 2021

  • Machine Learning Approaches for Optimal Resource Allocation in Kubernetes Environments

    • Authors: S.B. Sandeep Kumar Dasa, Phani Monogya Katikireddi

    • Year: 2021

  • Intelligent Cybersecurity: Enhancing Threat Detection through Hybrid Anomaly Detection Techniques

    • Authors: S.B. Phani Monogya Katikireddi, Sandeep Kumar Dasa

    • Year: 2021

 

 

 

 

 

 

Saurabh Kumar | Computer Science | Best Researcher Award

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Mr. Saurabh Kumar | Computer Science | Best Researcher Award

Shri Ramswaroop Memorial University, India

Saurabh Kumar is a passionate and driven Computer Science Engineering student with a strong focus on Artificial Intelligence, Machine Learning, and Natural Language Processing (NLP). With a deep interest in solving complex real-world challenges, Saurabh has worked extensively on AI-driven projects, including fine-tuning state-of-the-art models, developing computer vision applications, and enhancing NLP systems. His expertise spans multiple domains, including deep learning, speech synthesis, and autonomous systems. Saurabh actively contributes to the tech community through open-source projects and research-driven initiatives. His commitment to continuous learning, innovation, and collaboration sets him apart as a dedicated researcher in AI.

Professional Profile

Education

Saurabh Kumar is currently pursuing a degree in Computer Science Engineering, specializing in Artificial Intelligence and Machine Learning. Throughout his academic journey, he has developed a strong foundation in data science, deep learning, and cloud computing. His coursework includes advanced machine learning algorithms, computer vision, NLP, and big data analysis. In addition to academic learning, he has actively participated in AI-focused bootcamps, hackathons, and online certifications to enhance his technical knowledge. His commitment to education is evident through his consistent efforts to bridge theoretical knowledge with practical applications in AI-driven research.

Professional Experience

Saurabh has gained hands-on experience through various AI-based projects and internships. His work includes developing a Vehicle Classification Model using deep learning and computer vision, creating an advanced Text-to-Speech (TTS) model, and building multiple real-time computer vision applications. Additionally, he has experience working with cloud platforms like IBM Cloud and using tools such as SQL, Tableau, and Docker for AI deployment. His ability to work with cutting-edge AI models and optimize them for real-world use cases highlights his technical acumen. Saurabh’s professional experience reflects a strong ability to innovate, research, and implement AI solutions effectively.

Research Interests

Saurabh Kumar’s research interests lie at the intersection of Artificial Intelligence, Machine Learning, and Natural Language Processing. He is particularly passionate about Conversational AI, Reinforcement Learning, Explainable AI, and Generative AI. His work focuses on optimizing AI models for practical applications, enhancing NLP-based speech synthesis, and improving AI-driven automation. He is also interested in exploring AI ethics, fairness in machine learning, and the development of AI-driven assistive technologies. His continuous learning in AI research methodologies and practical deployment strategies showcases his commitment to pushing the boundaries of AI innovation.

Research Skills

Saurabh possesses a strong set of research skills, including data analysis, deep learning model optimization, and AI-driven problem-solving. He is proficient in Python, PyTorch, TensorFlow, OpenCV, and NLP frameworks such as Hugging Face. His expertise in AI extends to cloud computing, SQL-based data management, and deployment of machine learning models. He has hands-on experience with real-world AI challenges, including speech synthesis, computer vision applications, and text-based AI solutions. His ability to develop, fine-tune, and deploy AI models efficiently highlights his strong research-oriented approach.

Awards and Honors

Saurabh Kumar has been recognized for his contributions to AI and research. He has successfully completed the OpenCV Bootcamp, demonstrating expertise in Computer Vision and Deep Learning. His AI-driven projects have received recognition within the tech community, and his work in fine-tuning AI models has been acknowledged on various platforms. His commitment to advancing AI research is evident through his achievements in open-source contributions and AI development. These accolades showcase his dedication to continuous learning and impactful research in Artificial Intelligence.

Conclusion

Saurabh Kumar is a dedicated AI researcher and technology enthusiast committed to innovation, research, and problem-solving. His expertise in Artificial Intelligence, Machine Learning, and NLP, combined with his passion for AI-driven solutions, makes him a strong candidate for the Best Researcher Award. His extensive work in AI model development, contributions to open-source projects, and commitment to continuous learning set him apart as a future leader in AI research. By further expanding his research publications and collaborative efforts, he is well-positioned to make significant contributions to the field of AI.

Publications Top Notes

  1. Title: Real Time Vehicle Classification Using Deep Learning—Smart Traffic Management
    Authors: T Maurya, S Kumar, M Rai, AK Saxena, N Goel, G Gupta
    Year: 2025

 

Liangyu Yin | Artificial Intelligence | Best Researcher Award

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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

 

 

Wisal Zafar | Computer Science | Best Researcher Award

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Mr. Wisal Zafar | Computer Science | Best Researcher Award

Lecturer at Cecos university of information technology and emerging sciences, Pakistan.

Mr. Wisal Zafar is a dedicated researcher and lecturer with a strong background in software engineering, focusing on artificial intelligence, machine learning, and deep learning applications in healthcare. Born on March 25, 1999, in Peshawar, Pakistan, he has consistently demonstrated a passion for advancing technology’s role in solving real-world problems. He has developed and published research that leverages machine learning for medical diagnoses, including brain tumor analysis and diabetes prediction. As a lecturer and Electronic Data Processing (EDP) Officer at Iqra National University, he is committed to mentoring students and contributing to the field through both teaching and research. His work is distinguished by his continuous learning, keeping pace with emerging trends in AI and big data. Mr. Zafar’s career is marked by his enthusiasm for interdisciplinary research, integrating software engineering with advancements in health and data science. He is eager to expand his research contributions further through collaborations and innovative projects that address global challenges using advanced technologies.

Professional Profile

Education

Wisal Zafar holds an MS in Software Engineering from Iqra National University, Hayatabad Peshawar, completed in July 2024 with a commendable CGPA of 3.62/4.00. His postgraduate studies provided him with in-depth knowledge of advanced topics like artificial intelligence, data analysis, and big data. Prior to this, he earned a BS in Software Engineering from the same institution in October 2020, with a CGPA of 3.47/4.00, building a strong foundation in software development and computer science principles. His academic journey started with an intermediate qualification from Capital Degree College, Peshawar, where he scored 700 out of 1100 marks, and continued with his matriculation from The Jamrud Model High School, achieving 824 out of 1100 marks. His educational background is characterized by consistent academic performance and a focus on both theoretical and practical aspects of software engineering, which has prepared him for his subsequent roles in academia and research.

Professional Experience

Wisal Zafar currently serves as a Lecturer at Iqra National University, Hayatabad, Peshawar, where he has been teaching various software engineering subjects since January 2023. His areas of instruction include Data Science, Artificial Intelligence, Machine Learning, Data Structures, and Algorithms, allowing him to impart advanced knowledge to students and prepare them for careers in technology. Alongside his role as a lecturer, he also holds the position of Electronic Data Processing (EDP) Officer at the same university, a role he has been fulfilling since October 2021. In this capacity, he manages data processing tasks, ensuring the effective handling of academic data and resources. Previously, he gained practical experience as a Junior Web Developer at Pakistan Online Services Software House, where he worked from November 2020 to April 2021, specializing in web development using PHP, Laravel, JavaScript, and other technologies. This diverse experience in academia and industry has equipped Mr. Zafar with the skills to blend theoretical concepts with real-world applications, making him an effective educator and a valuable contributor to research.

Research Interests

Wisal Zafar’s research interests are centered around artificial intelligence (AI), machine learning (ML), deep learning, and their applications in healthcare and data analysis. He is particularly fascinated by the potential of AI and ML in developing advanced diagnostic tools, aiming to improve medical outcomes through data-driven insights. His recent research projects have explored the use of deep learning techniques like YOLOv8s and U-Net for multi-class brain tumor analysis, integrating detection, localization, and segmentation of tumors using MRI data. Additionally, he has delved into predictive models for diabetes diagnosis using various ML algorithms, such as Decision Trees, K-Nearest Neighbors, Random Forest, Logistic Regression, and Support Vector Machines. His interests extend to big data analytics and the role of data science in enhancing information retrieval and management in medical libraries. Through his work, Wisal Zafar seeks to advance the intersection of technology and healthcare, utilizing cutting-edge algorithms and data processing techniques to solve critical challenges and improve human well-being.

Research Skills

Wisal Zafar possesses a diverse skill set in artificial intelligence, machine learning, data analysis, and big data management, making him adept at tackling complex research challenges. He has extensive experience in using programming languages like Python and C++, which he applies to develop machine learning models and algorithms. His technical expertise includes working with deep learning frameworks, as seen in his research on brain tumor analysis using advanced models such as YOLOv8s and U-Net. Additionally, Wisal has proficiency in cloud computing and handling large datasets, which supports his work in big data analytics and the implementation of data-driven decision-making tools. His hands-on experience as a Research Assistant has further refined his skills in conducting surveys, data preprocessing, and statistical analysis. Mr. Zafar is also skilled in web development using frameworks like Laravel and JavaScript, allowing him to create interactive platforms for research applications. His ability to integrate these skills into interdisciplinary projects makes him a capable researcher with a focus on innovation and problem-solving.

Award Recognition

Wisal Zafar’s dedication to research and academic excellence has earned him recognition in the academic community, though he is still working towards broader award recognitions. His recent research publications, including studies on brain tumor analysis and diabetes prediction using machine learning, have been well-received and published in respected journals. These works have contributed significantly to the fields of AI in healthcare and big data analytics, positioning him as a promising researcher. His role as a Lecturer at Iqra National University also reflects the acknowledgment of his expertise, as he is entrusted with educating the next generation of software engineers. Additionally, Wisal has completed several certified courses from platforms like Coursera, receiving certificates in advanced learning algorithms, deep learning, and image processing with Python, which underscore his commitment to continuous learning. While he may not yet have specific awards, his publications, teaching contributions, and commitment to research excellence serve as strong indicators of his potential for future recognition in the field.

Awards and Honors

Wisal Zafar has demonstrated a commitment to continuous professional development through various certifications and achievements, contributing to his expertise in software engineering and AI. He has completed notable courses such as AI for Everyone and Advanced Learning Algorithms through Coursera, which are associated with respected institutions like DeepLearning.AI and Stanford University. These certifications have enhanced his knowledge of machine learning, deep learning, and image processing, enabling him to apply advanced concepts in his research. While he has not yet received specific formal awards, his role as a Lecturer at Iqra National University and his position as an Electronic Data Processing (EDP) Officer are testaments to his skills and recognition within the academic community. His contributions to research, especially in the areas of AI applications in healthcare, have been acknowledged through the publication of his work in peer-reviewed journals. Wisal Zafar’s ongoing pursuit of excellence, both in research and teaching, positions him as a candidate worthy of future awards and honors in the field of software engineering and AI.

Conclusion:

Wisal Zafar has demonstrated considerable research skills and expertise in the field of software engineering, particularly in applying machine learning and AI to medical problems. His academic background, technical skills, and research publications make him a strong contender for the Best Researcher Award. While he could benefit from diversifying his research and increasing his international presence, his current achievements in AI-driven healthcare solutions and data analytics set a solid foundation for this recognition.

Publications Top Notes

  1. Enhanced TumorNet: Leveraging YOLOv8s and U-net for superior brain tumor detection and segmentation utilizing MRI scans
    • Authors: Zafar, W., Husnain, G., Iqbal, A., AL-Zahrani, M.S., Naidu, R.S.
    • Journal: Results in Engineering
    • Year: 2024
    • Volume: 24
    • Article ID: 102994
    • Type: Open access
  2. Revolutionizing Diabetes Diagnosis: Machine Learning Techniques Unleashed
    • Authors: Shaukat, Z., Zafar, W., Ahmad, W., Ghadi, Y.Y., Algarni, A.
    • Journal: Healthcare (Switzerland)
    • Year: 2023
    • Volume: 11
    • Issue: 21
    • Article ID: 2864
    • Citations: 1
    • Type: Open access

 

 

 

 

Umaa Mahesswari G | Artificial Intellugence Engineering | Best Researcher Award

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Ms. Umaa Mahesswari G | Artificial Intellugence Engineering | Best Researcher Award

Research Scholar at College of Engineering Guindy, Anna University, India

G. Umaa Mahesswari is a highly motivated research scholar from Chennai, India, with a passion for innovation and technology. With a solid foundation in Computer Science, her academic journey spans from her B.E. at R.M.K College to a Ph.D. at Anna University, specializing in Big Data Analytics. Umaa has worked on significant projects like IoT-based air pollution detection and digital inscription readers for ancient Tamil stone inscriptions. A recipient of the prestigious Anna Research Fellowship, she is dedicated to leveraging technology for social good. Her technical expertise and passion for research make her a valuable asset in the R&D domain.

Profile

Education 📘🎓

Bachelor of Engineering (B.E.) in Computer Science from R.M.K College of Engineering and Technology, Chennai (2015-2019), with a CGPA of 8.65.Master of Engineering (M.E.) in Computer Science with a Specialization in Big Data Analytics from College of Engineering, Guindy, Anna University, Chennai (2019-2021), with a CGPA of 9.07.Ph.D. in Computer Science from College of Engineering, Guindy, Anna University (2023-present).Completed the Google Data Analytics Professional Specialization Course via Coursera (2021), enhancing her skills in data-driven problem-solving.

Experience 💼📊

Research Project Assistant at Tamil Virtual Academy (2022), working on the development of an inscription reader for ancient Tamil temple inscriptions, supervised by Dr. P. Uma Maheswari.Undergraduate project on IoT-based air pollution detection and analysis, focusing on real-time data collection and environmental monitoring.Postgraduate project on predictive analytics for plastic disposal by Walmart India, contributing to sustainable business solutions.Proficient in machine learning, data visualization, and SQL, with significant contributions to the field of Big Data Analytics.

Awards and Honors 🏆🎖

Academic Topper in the third year of her B.E. program, demonstrating her dedication to academic excellence.Nominee for Best Outgoing Student Award at the end of her undergraduate studies.Prize winner in several intra-college cultural competitions, showcasing her versatility beyond academics.Anna Research Fellowship Holder from 2023 to 2025, awarded in recognition of her research potential in Big Data Analytics.Published academic papers in esteemed venues like Springer ICTIS and Computer Society of India, highlighting her contributions to the academic community.

Research Focus 🔍💡

Umaa Mahesswari’s research focuses on leveraging Big Data Analytics, Machine Learning, and Deep Learning to solve pressing societal challenges. Her projects span diverse areas such as IoT-based environmental monitoring, predictive analytics for waste management, and digital solutions for heritage preservation (Tamil inscriptions). She aims to develop data-driven solutions that improve sustainability and drive innovation. Her ongoing Ph.D. research explores pattern recognition and data visualization techniques to extract meaningful insights from large datasets, with the goal of enhancing decision-making processes in both academic and practical settings.

Conclusion

G. Umaa Mahesswari is an exceptional candidate for the Best Scholar Award due to her innovative research, academic achievements, and technical expertise. By further broadening her research scope and international collaborations, she could elevate her already impressive profile and contribute even more profoundly to the global research community.

Publication Top Notes

SmartScanPCOS: A Feature-Driven Approach to Cutting-Edge Prediction of Polycystic Ovary Syndrome using Machine Learning and Explainable Artificial Intelligence

Journal: Heliyon
Published: October 2024
DOI: 10.1016/j.heliyon.2024.e39205
Contributors: G. Umaa Mahesswari; P Uma Maheswari

Abid Iqbal | Artificial Intelligence | Best Researcher Award

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Assist Prof Dr. Abid Iqbal | Artificial Intelligence | Best Researcher Award

Assistant Professor at King Faisal University, Saudi Arabia

Dr. Abid Iqbal is an accomplished Assistant Professor at the University of Engineering and Technology Peshawar, specializing in Electrical Engineering and artificial intelligence. He earned his Ph.D. from Griffith University, Australia, where he researched piezoelectric energy harvesters. With a strong academic background, he ranked first in his Master’s program at Ghulam Ishaq Khan Institute, Pakistan. Dr. Iqbal has a diverse professional experience, including roles as an Electrical Design Engineer and Research Assistant. His expertise encompasses developing embedded devices and innovative teaching methodologies, mentoring students, and conducting impactful research. He has successfully secured funding for multiple projects in AI applications for health and agriculture. Dr. Iqbal’s publication record includes numerous papers in reputable journals, reflecting his commitment to advancing knowledge in his field. His technical skills in programming and software further enhance his research capabilities, making him a valuable asset to academia and industry.

Profile

Education

Dr. Abid Iqbal is a highly accomplished academic with a solid educational foundation in electrical and electronics engineering. He earned his Ph.D. from the Queensland Micro- and Nanotechnology Centre at Griffith University, Australia, from April 2013 to February 2017. His doctoral research focused on the design, fabrication, and analysis of aluminum nitride (AlN)/silicon carbide (SiC)-based piezoelectric energy harvesters, contributing significantly to renewable energy technologies. Prior to his Ph.D., Dr. Iqbal completed his Master’s degree in Electronics Engineering at the Ghulam Ishaq Khan Institute in Topi, Swabi, Pakistan, graduating with a remarkable GPA of 3.88/4 and securing the top position in his class. His academic journey began with a Bachelor’s degree in Electrical Engineering from the University of Engineering & Technology in Peshawar, Pakistan, where he was recognized as an outstanding student. Dr. Iqbal’s educational background reflects his dedication and expertise in his field, laying a strong foundation for his professional career.

Professional Experience

Dr. Abid Iqbal is an accomplished electrical engineer currently serving as an Assistant Professor at the University of Engineering and Technology Peshawar since August 2019. In this role, he has been instrumental in teaching undergraduate courses in Electrical Engineering, developing innovative teaching methods, and mentoring students on research projects. Prior to this position, he worked as an Electrical Design Engineer at Alliance Power and Data in Australia, focusing on ERGON and NBN projects. He also contributed to the development of embedded systems for individuals with disabilities while employed as an Electronic Engineer at Community Lifestyle Support. His research experience includes a significant role as a Research Assistant at Griffith University, where he worked on piezoelectric devices for harsh environments and gained expertise in various semiconductor fabrication processes. Additionally, he has served as a lecturer at Comsat Institute of Information Technology and worked as a research associate at the City University of Hong Kong, demonstrating a robust and diverse professional background in academia and industry.

Research Interest

Dr. Abid Iqbal’s research interests lie at the intersection of electrical engineering and artificial intelligence, focusing on the development of innovative technologies that enhance energy efficiency and improve healthcare outcomes. His work includes designing and fabricating advanced piezoelectric energy harvesters using AlN/SiC materials, aimed at harnessing renewable energy sources. Additionally, Dr. Iqbal is deeply involved in projects utilizing artificial intelligence for agricultural applications, such as real-time disease detection in crops, and developing telehealth systems that leverage IoT technology to monitor patient health remotely. He has a keen interest in embedded systems and the design of hardware for assistive technologies, including portable ventilators and muscle sensors for individuals with disabilities. Through his research, Dr. Iqbal aims to contribute to sustainable energy solutions and advancements in healthcare technology, fostering a multidisciplinary approach that integrates engineering principles with artificial intelligence for practical applications.

Research Skills

Dr. Abid Iqbal possesses a robust set of research skills that underscore his expertise in Electrical Engineering and artificial intelligence. His extensive experience in designing and fabricating piezoelectric energy harvesters highlights his proficiency in materials science and device characterization. Dr. Iqbal is adept at using advanced simulation tools such as COMSOL, Ansys, and Coventorware, which facilitate in-depth analysis and optimization of microelectromechanical systems (MEMS). His work on artificial intelligence applications in telehealth and agricultural systems showcases his ability to integrate machine learning techniques with practical engineering solutions. Additionally, Dr. Iqbal has a strong background in programming languages such as Python and MATLAB, enhancing his capability to develop innovative software solutions for complex engineering problems. His involvement in funded projects and numerous publications further illustrates his commitment to advancing research and contributing to knowledge in his field. Overall, Dr. Iqbal’s diverse skills position him as a valuable asset to any research team.

Award and Recognition

Dr. Abid Iqbal is a distinguished electrical engineer and academic known for his significant contributions to the field of electrical and electronics engineering. He has received multiple accolades for his research and academic excellence, including the IGNITE funding for four innovative projects focused on machine learning applications in health and agriculture. Dr. Iqbal was awarded publication scholarships and prestigious Griffith University PhD scholarships, recognizing his outstanding academic performance during his doctoral studies. Additionally, he ranked first among his peers in the Master’s program at Ghulam Ishaq Khan Institute, further demonstrating his commitment to excellence in engineering. His dedication to teaching and mentoring future engineers is evident in his role as an Assistant Professor at the University of Engineering and Technology Peshawar, where he has developed innovative curricula and guided numerous student research projects. Dr. Iqbal’s work has been widely published, contributing significantly to advancements in artificial intelligence, embedded systems, and renewable energy technologies.

Conclusion

Dr. Abid Iqbal is a highly qualified candidate for the Best Researcher Award, demonstrating exceptional expertise in Electrical Engineering and a strong commitment to research and education. His accomplishments in renewable energy research, successful project management, and dedication to mentoring future engineers make him a standout choice. While he has areas for growth, particularly in expanding collaborative networks and enhancing commercialization efforts, his current achievements and potential for future contributions position him as an inspiring figure in his field. This award would not only recognize his past efforts but also encourage his continued pursuit of excellence in research and education.

Publication Top Notes

  1. Enhanced TumorNet: Leveraging YOLOv8s and U-net for superior brain tumor detection and segmentation utilizing MRI scans
    • Authors: Zafar, W., Husnain, G., Iqbal, A., AL-Zahrani, M.S., Naidu, R.S.
    • Year: 2024
    • Journal: Results in Engineering
    • Volume/Page: 24, 102994
  2. Novel dual absorber configuration for eco-friendly perovskite solar cells: design, numerical investigations and performance of ITO-C60-MASnI3-RbGeI3-Cu2O-Au
    • Authors: Hasnain, S.M., Qasim, I., Iqbal, A., Amin Mir, M., Abu-Libdeh, N.
    • Year: 2024
    • Journal: Solar Energy
    • Volume/Page: 278, 112788

 

 

 

Navid Ghaffarzadeh | Engineering | Best Researcher Award

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Assoc Prof Dr. Navid Ghaffarzadeh | Engineering | Best Researcher Award

Assoc Prof Dr. Navid Ghaffarzadeh, Imam Khomeini International University, Iran

Assoc Prof Dr. Navid Ghaffarzadeh is an accomplished engineer recognized for his innovative contributions to the field of engineering. With a focus on [specific area of expertise], he has been instrumental in advancing research and development initiatives. His dedication and impactful work earned him the prestigious Best Researcher Award, highlighting his commitment to excellence and collaboration. Navid continues to inspire through his research, aiming to drive advancements that benefit both industry and society.

 

Profile:

Education

Navid Ghaffarzadeh earned his PhD in Electrical Engineering from Iran University of Science and Technology in Tehran, completing his studies from September 2007 to April 2011. Prior to that, he obtained his Master of Science in Electrical Engineering from Amirkabir University of Technology (Tehran Polytechnic) between September 2005 and August 2007. He also holds a Bachelor of Science in Electrical Engineering from Zanjan University, where he studied from September 2001 to June 2005.

Professional Activities

Navid Ghaffarzadeh is actively engaged in the academic community as a reviewer for numerous prestigious journals in the field of electrical engineering. His reviewing contributions span a wide array of publications, including Renewable and Sustainable Energy Reviews, Applied Energy, Journal of Energy Storage, and IEEE Transactions on Power Systems, among others, with impact factors ranging from 1.276 to 16.799. With over 100 reviewed journal papers, Navid plays a vital role in advancing research quality and integrity in the field. His extensive experience demonstrates his commitment to fostering innovation and excellence in engineering research.

Research Interests

Navid Ghaffarzadeh’s research interests encompass a wide range of cutting-edge topics in electrical engineering. He focuses on renewable energy, exploring innovative solutions in battery energy storage systems and electric vehicles. His work in microgrid and smart grid design aims to enhance the efficiency and reliability of power systems. Navid is particularly interested in the application of artificial intelligence in renewable energy systems, as well as power systems protection and transients. Additionally, he investigates intelligent systems and optimization techniques to improve power systems, with a strong emphasis on ensuring power quality.

Honors and Awards: ‌

Navid Ghaffarzadeh has received numerous honors and awards throughout his academic and professional career. In 2012, he was honored with the IET Science, Measurement and Technology Premium Award for his outstanding paper on power quality disturbances, recognized as one of the best published in the journal. He has been named Outstanding Researcher at I.K International University multiple times, in 2013, 2014, 2016, and 2020, and has also received the Outstanding Professor award in 2017, 2019, 2020, 2021, and 2023. Additionally, he was awarded the Best Iranian PhD Dissertation in power system protection, highlighting his significant contributions to the field. Navid achieved top rankings in his studies, finishing first among PhD electrical power engineering students at Iran University of Science and Technology with a GPA of 18.72 out of 20, first among M.Sc. students at Amirkabir University of Technology with a GPA of 19.18 out of 20, and first among B.Sc. students at Zanjan University with a GPA of 18.36 out of 20.

 

Publication Top Note

A. Bamshad, N. Ghaffarzadeh, “A novel smart overcurrent protection scheme for renewables-dominated distribution feeders based on quadratic-level multi-agent system (Q-MAS),” Electrical Engineering, vol. 105, pp. 1497–1539, February 2023.

S. Ansari, N. Ghaffarzadeh, “A Novel Superimposed Component-Based Protection Method for Multi Terminal Transmission Lines Using Phaselet Transform,” IET Generation, Transmission & Distribution, vol. 17, no. 1, pp. 469–485, January 2023.

A. HN. Tajani, A. Bamshad, N. Ghaffarzadeh, “A novel differential protection scheme for AC microgrids based on discrete wavelet transform,” Electric Power Systems Research, vol. 220, pp. 1-12, July 2023.

A. Zarei, N. Ghaffarzadeh, “Optimal Demand Response-based AC OPF Over Smart Grid Platform Considering Solar and Wind Power Plants and ESSs with Short-term Load Forecasts using LSTM,” Journal of Solar Energy Research, vol. 8, no. 2, pp. 1367-1379, April 2023.

M. Dodangeh, N. Ghaffarzadeh, “A New Protection Method for MTDC Solar Microgrids using on-line Phaselet, Mathematical Morphology, and Signal Energy Analysis,” Energy Engineering & Management, vol. 13, no. 1, pp. 40-53, March 2023 (in Persian).

M. Dodangeh, N. Ghaffarzadeh, “An Intelligent Protection Method for Multi-terminal DC Microgrids Using On-line Phaselet, Mathematical Morphology, and Fuzzy Inference Systems,” Energy Engineering & Management, vol. 12, no. 2, pp. 12-25, August 2022 (in Persian).

M. Dodangeh, N. Ghaffarzadeh, “Optimal Location of HTS-FCLs Considering Security, Stability, and Coordination of Overcurrent Relays and Intelligent Selection of Overcurrent Relay Characteristics in DFIG Connected Networks Using Differential Evolution Algorithm,” Energy Engineering & Management, vol. 10, no. 2, pp. 14-25, May 2020 (in Persian).

A. Inanloo Salehi, N. Ghaffarzadeh, “Fault detection and classification of VSC-HVDC transmission lines using a deep intelligent algorithm,” International Journal of Research and Technology in Electricity Industry, vol. 1, no. 2, pp. 161-170, September 2022.

N. Ghaffarzadeh, H. Faramarzi, “Optimal Solar plant placement using holomorphic embedded power flow considering the clustering technique in uncertainty analysis,” Journal of Solar Energy Research, vol. 7, no. 1, pp. 997-1007, Winter 2022.

N. Ghaffarzadeh, A. Bamshad, “A new approach to AC microgrids protection using a bi-level multi-agent system,” International Journal of Research and Technology in Electricity Industry, vol. 1, no. 1, pp. 66-74, March 2022.

Amel SAHLI | Computer Science | Best Researcher Award

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MS. Amel SAHLI | Computer Science | Best Researcher Award

École Nationale des Sciences de l’Informatique , Tunisia

Amel Sahli is a dedicated researcher pursuing her PhD in computer science at the École Nationale des Sciences de l’Informatique in Tunisia, focusing on optimizing e-learning processes through AI and key performance indicators. She holds a Master’s degree in information systems and has published significant work on performance measurement in education. Sahli’s diverse professional background includes roles as a contract lecturer and various internships, providing her with practical insights and teaching experience. Her technical skills in programming and web development, coupled with her proficiency in Arabic, French, and English, enhance her ability to engage with the international research community. Amel Sahli’s commitment to advancing educational methodologies through her research makes her a strong candidate for the Best Researcher Award, highlighting her potential to contribute meaningfully to the field of education technology.

 

Profile:

Education

Amel Sahli is currently pursuing her PhD in computer science at the École Nationale des Sciences de l’Informatique (ENSI) in Tunisia. Her doctoral research focuses on developing an integrated approach that leverages artificial intelligence (AI) and key performance indicators (KPIs) to optimize e-learning processes. Prior to her PhD, she earned a Master’s degree in information systems and web technologies, where she studied performance measurement in educational settings. This followed her Bachelor’s degree in computer science, during which she designed and implemented web applications for educational management. Sahli’s academic journey has been marked by consistent excellence, earning distinctions in her studies and developing a strong foundation in both theoretical and practical aspects of computer science. Her educational background not only highlights her technical competencies but also underscores her commitment to advancing the field of education through innovative research.

Professional Experiences

Amel Sahli has gained diverse professional experience that enriches her academic pursuits. She began her career as a bank intern and a counter agent, where she honed her customer service and operational skills. Following these roles, she interned at the Institut Supérieur d’Informatique du Kef, further deepening her understanding of information technology in educational contexts. In 2023, she transitioned into academia as a part-time lecturer, sharing her expertise in computer science with students. Currently, Sahli is engaged in research at the RIADI laboratory at the Université de la Manouba, where she applies her knowledge of artificial intelligence and KPIs to enhance e-learning processes. This combination of practical experience and academic engagement positions her as a well-rounded professional, capable of bridging theory and practice effectively. Sahli’s journey reflects her commitment to continuous learning and development in both research and teaching.

Research Skills

Amel Sahli possesses a robust set of research skills that are essential for her academic pursuits. Her expertise in quantitative and qualitative research methodologies allows her to design comprehensive studies that yield meaningful insights. Proficient in data analysis, Sahli employs statistical tools to interpret complex datasets, ensuring her findings are both reliable and impactful. Additionally, her experience in academic writing and publication equips her to effectively communicate her research outcomes to diverse audiences. Sahli’s ability to critically evaluate existing literature enables her to identify gaps in knowledge, guiding her own research questions. Her strong organizational skills facilitate the management of research projects, from initial conception to final execution. Moreover, her proficiency in various programming languages and web development enhances her capability to create innovative solutions within her research, particularly in optimizing e-learning processes. Overall, Sahli’s comprehensive research skill set positions her as a valuable contributor to the field of computer science and education technology.

Award and Recognition

Amel Sahli has been recognized for her outstanding contributions to the field of computer science and education. Notably, she participated in the “Inspiring Research & Innovation Using IEEE Publications” event, demonstrating her commitment to advancing research practices. Additionally, she attended the “23rd International Conference on Intelligent Systems Design and Applications,” where she engaged with leading experts and shared her insights. Her certifications from prestigious organizations, including Google and Microsoft, further attest to her dedication to continuous learning and professional development. Moreover, Sahli’s article on performance measurement in educational processes has been published in Procedia Computer Science, enhancing her visibility in academic circles. These recognitions not only reflect her hard work and innovation but also position her as a rising star in her field, earning her respect among peers and contributing to her eligibility for the Best Researcher Award.

Conclusion

In conclusion, Amel Sahli exemplifies the qualities sought in a candidate for the Best Researcher Award. Her academic journey, characterized by a robust educational background in computer science and information systems, has equipped her with the necessary tools to conduct meaningful research. Her focus on optimizing e-learning processes through the integration of AI and KPIs showcases her innovative approach to addressing contemporary educational challenges. Furthermore, her contributions to peer-reviewed journals and participation in international conferences illustrate her commitment to advancing knowledge in her field. Sahli’s diverse professional experiences, ranging from teaching to research, highlight her multifaceted skill set and adaptability. With her proficiency in multiple languages and technical expertise, she stands out as a collaborative researcher poised to make a lasting impact in education technology. Thus, Amel Sahli is not only a deserving nominee but also a potential leader in shaping the future of educational practices.

Publication Top Note

  • Conference Paper in Procedia Computer Science
    • Title: Performance Measurement of Reading Teaching-Learning Business Processes: Case of Whole-Word and Syllabic Reading Methods in Primary Schools
    • Authors: Amel Sahli, A. Mejri, A. Louati
    • Year: 2024
    • Citations: 0
  • Conference Paper in Lecture Notes in Networks and Systems
    • Title: Performance Measurement of Reading Teaching-Learning Business Processes: Case of Whole-Word and Syllabic Reading Methods in Primary Schools
    • Authors: Amel Sahli, A. Mejri, A. Louati
    • Year: 2024
    • Citations: 0

 

Karimeh Ata | Artificial Intelligence | Best Researcher Award

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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