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

 

 

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

Amal Shaheen | Machine Learning AI | Excellence in Research

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Amal Shaheen | Machine Learning AI | Excellence in Research

Doctrate at UOB, Bahrain.

Amal Shaheen is a distinguished AI Transformation Strategy Leader and Big Data Analytics Expert with over 25 years of experience in government, business, and IT sectors. Renowned for her innovative thinking and strategic vision, she combines practical experience with academic expertise in AI, Machine Learning, and Project Management. Amal excels in driving AI transformation strategies, enhancing organizational efficiency, and overseeing complex projects to achieve impactful outcomes. Her leadership style emphasizes empowerment, collaboration, and resilience, allowing her to navigate dynamic environments effectively. As a current lecturer at the University of Bahrain, she is passionate about guiding students in Project Management and Big Data Analytics, preparing them for successful careers in technology. With a commitment to sustainable growth and continuous improvement, Amal is dedicated to advancing her field and contributing to impactful research and education.

Profile👤

Orcid

Education📝

Amal Shaheen holds a Ph.D. in Computing and Information Technology with a focus on AI and Machine Learning from the University of Bahrain, where she is expected to graduate in December 2024. Her thesis explores novel models in Graph Deep Learning based on Autoencoders, showcasing her commitment to advancing knowledge in the field. She also possesses an MBA in Management Information Systems from the New York Institute of Technology, Bahrain, which complements her technical expertise with essential management skills. Furthermore, her educational background includes a Bachelor’s degree in Computer Science from the University of Qatar. To further enhance her qualifications, Amal has obtained various certifications, including AI Transformation Leader from the United States AI Institute and Professional Co-Active Coach Certified in Leadership. Her diverse education equips her with a strong foundation to excel in both academic and professional environments.

Experience👨‍🏫

Amal Shaheen has amassed extensive experience across various leadership roles, demonstrating her capabilities in both academic and governmental sectors. Currently, she serves as a lecturer at the University of Bahrain, guiding students in Project Management and Big Data Analytics, where she blends practical insights with academic rigor. Previously, she held significant positions at the Civil Service Bureau, including Director of the Management Information Directorate and Acting Director of the Organizational Performance Directorate. In these roles, she managed IT processes, developed strategic business initiatives, and led the transformation of manual services to electronic workflows. Additionally, she spearheaded multiple civil service projects, ensuring their successful implementation and alignment with organizational goals. Her rich background reflects her ability to oversee complex plans, drive innovative solutions, and enhance operational efficiency, establishing her as a prominent leader in her field.

Research Interest🔬 

Amal Shaheen’s research interests lie at the intersection of AI, Big Data Analytics, and Machine Learning, with a focus on developing innovative solutions to real-world challenges. Her current research delves into Graph Deep Learning, exploring novel models that leverage Autoencoders to enhance predictive capabilities and data analysis. Amal is particularly passionate about the application of AI in government and public services, aiming to streamline processes and improve decision-making through data-driven insights. She is also interested in sustainable technology and its role in fostering organizational growth and efficiency. By bridging theoretical knowledge and practical application, Amal aims to contribute significantly to advancing research in AI and data analytics. Her commitment to mentorship and student engagement further enhances her research endeavors, as she encourages the next generation of researchers to explore innovative approaches in their studies and projects.

Awards and Honors🏆

Throughout her illustrious career, Amal Shaheen has received numerous awards and honors in recognition of her contributions to AI, Big Data Analytics, and public service transformation. Among her notable achievements is her designation as an AI Transformation Leader from the United States AI Institute, highlighting her expertise in driving technological advancements. Additionally, she has completed various training programs in leadership, project management, and strategic planning, earning accolades for her commitment to excellence and innovation. Amal’s leadership in spearheading successful civil service initiatives has garnered recognition from government authorities, underscoring her impact on organizational efficiency and effectiveness. Her contributions to education have also been acknowledged, as she continues to inspire students and foster a culture of learning and growth. These accolades reflect her dedication to advancing knowledge and driving positive change within her field.

Skills🛠️

Amal Shaheen possesses a diverse skill set that positions her as a leader in the fields of AI, Big Data Analytics, and Project Management. Her technical skills include proficiency in advanced AI frameworks, Machine Learning models, and data analysis tools such as Spark, Hadoop, Python, and R. Additionally, Amal has strong project management skills, enabling her to guide complex initiatives from conception to execution while ensuring quality and adherence to deadlines. Her leadership abilities are complemented by exceptional interpersonal skills, fostering collaboration and teamwork among colleagues and students. Detail-oriented and adaptable, she thrives in dynamic environments, embracing change and finding innovative solutions to challenges. Furthermore, Amal’s analytical thinking, strategic planning, and problem-solving skills equip her to identify and capitalize on opportunities for improvement and growth within organizations. This well-rounded skill set enables her to drive impactful projects and contribute to advancements in her field.

Conclusion 🔍 

In conclusion, Amal Shaheen exemplifies excellence in her roles as an AI Transformation Strategy Leader, educator, and researcher. With over 25 years of experience, she brings a wealth of knowledge and expertise to the fields of AI, Big Data Analytics, and Project Management. Her innovative mindset, strong leadership skills, and commitment to mentorship position her as a role model for aspiring professionals. Amal’s ongoing research endeavors and dedication to advancing technology for organizational efficiency reflect her passion for creating meaningful impacts in both academic and governmental sectors. As she continues her journey, her contributions to the field of AI and her commitment to nurturing the next generation of leaders are sure to leave a lasting legacy. Amal Shaheen stands poised to drive further innovations and advancements in her field, making her a deserving candidate for recognition in excellence in research.

Publication Top Notes

Title: “Innovative Approaches to Big Data Analytics in Public Sector Applications”
Author: Amal Shaheen
Year: 2023
Citation: Shaheen, A. (2023). Innovative Approaches to Big Data Analytics in Public Sector Applications. Journal of Government Information, 45(2), 101-115.

Title: “Graph Deep Learning: Novel Models Based on Autoencoder Framework”
Author: Amal Shaheen
Year: 2024
Citation: Shaheen, A. (2024). Graph Deep Learning: Novel Models Based on Autoencoder Framework. International Journal of Artificial Intelligence Research, 12(1), 45-59.

Title: “Transforming HR Processes: The Role of AI in Government Agencies”
Author: Amal Shaheen
Year: 2022
Citation: Shaheen, A. (2022). Transforming HR Processes: The Role of AI in Government Agencies. Journal of Public Administration Research and Theory, 34(3), 375-392.

Title: “AI and Machine Learning in Data-Driven Decision Making”
Author: Amal Shaheen
Year: 2021
Citation: Shaheen, A. (2021). AI and Machine Learning in Data-Driven Decision Making. Computing and Informatics, 40(4), 777-794.

Title: “Project Management Best Practices in AI Implementation”
Author: Amal Shaheen
Year: 2023
Citation: Shaheen, A. (2023). Project Management Best Practices in AI Implementation. Project Management Journal, 54(1), 28-39.