Murtaza Hussain | Artificial Intelligence | Best Researcher Award

Posted on by sciencefather

Mr. Murtaza Hussain | Artificial Intelligence | Best Researcher Award

PhD Research Scholar at Xi’an Jiaotong University, Singapore

Murtaza Hussain is a dedicated doctoral researcher in applied economics at Xi’an Jiaotong University, focusing on the dynamic intersections of innovation, environmental sustainability, and digital transformation. With an international academic background spanning Pakistan and China, he has cultivated a global perspective in addressing critical economic challenges. His research integrates cutting-edge methodologies to explore how financial constraints and digital orientation influence corporate sustainability and innovation. Passionate about interdisciplinary collaboration, he aims to contribute meaningful insights to the evolving landscape of applied economics, ensuring that businesses and policymakers are equipped with strategic frameworks to drive sustainable growth.

Profile

Orcid

Education

Murtaza Hussain is currently pursuing a Ph.D. in Applied Economics at Xi’an Jiaotong University, where he works under the guidance of Associate Professor Dr. Shaohua Yang. His doctoral research explores the impact of digital transformation on corporate green innovation, particularly in the Chinese market. Prior to his Ph.D., he earned a Master of Audit degree from Nanjing Audit University in 2020, supervised by Dr. Chien-Yu Huang. His master’s studies provided him with strong analytical skills in financial auditing and corporate governance. Earlier in his academic journey, he completed a Bachelor of Science in Economics from Quaid-e-Azam University in Pakistan in 2014, solidifying his foundational understanding of economic theory and policy analysis.

Experience

Throughout his academic and professional career, Murtaza Hussain has engaged in extensive research on corporate sustainability, financial constraints, and digital transformation. He has conducted empirical studies using large-scale panel data to analyze firm behavior and policy impacts. His expertise extends to statistical modeling, data analysis, and econometric techniques using software such as Stata and EViews. Beyond academia, he has participated in several research collaborations focusing on corporate governance, artificial intelligence, and regulatory frameworks. Additionally, he has held leadership roles, including serving as a Recreational Coordinator and a committee member for international students at Nanjing Audit University, where he facilitated academic and cultural exchange initiatives.

Research Interests

Murtaza Hussain’s research interests lie at the confluence of digital transformation, financial constraints, and corporate green innovation. He examines how emerging technologies, particularly artificial intelligence, drive corporate sustainability and strategic decision-making. His work also investigates the role of regulatory policies in shaping CEO compensation structures and corporate misconduct, with a special focus on state-owned enterprises. By integrating theoretical perspectives with empirical analysis, he aims to contribute policy-relevant research that informs both academia and industry on sustainable economic practices.

Awards

Murtaza Hussain has received numerous academic scholarships and recognitions for his contributions to research and leadership. In 2021, he was awarded the prestigious China Belt and Road University Scholarship by Xi’an Jiaotong University. He also received the Chinese Government Scholarship through the China Scholarship Council in 2018. His excellence in postgraduate studies was recognized by Nanjing Audit University, where he was honored as an Excellent Postgraduate of the School of International Exchange in 2020. Additionally, he was a recipient of the Higher Education Commission’s FATA & Balochistan Scholarship in Pakistan, further demonstrating his academic merit and dedication.

Publications

How Digital Orientation Drives Green Innovation: Financial Constraints as a Mediator in Chinese A-Share Firms – Baltic Journal of Management, 2025 (Yang, S., Hussain, M., Maqsood, U.S., Younas, M.W., Zahid, R.M.A.)

Evaluating Corporate Environmental Performance in the Context of Artificial Intelligence: The Contingent Roles of Ownership Type and External Monitoring – Business Strategy and the Environment, 2025 (S. Wang, Y. Yong, M. Hussain, U.S. Maqsood, R.M.A. Zahid)

Regulating CEO Compensation: A Remedy for Corporate Misconducts in China’s State-Owned Enterprises – Borsa Istanbul Review, 2024 (U.S. Maqsood, Q. Li, H. Hussain, M. Hussain, R.M.A. Zahid)

Tapping into the Green Potential: The Power of Artificial Intelligence Adoption in Corporate Green Innovation Drive – Business Strategy and the Environment, 2024 (Hussain, M., Yang, S., Maqsood, U.S., Zahid, R.M.A.)

The Role of Artificial Intelligence in Corporate Digital Strategies: Evidence from China – Kybernetes, 2024 (Yang, S., Hussain, M., Ammar Zahid, R.M., Maqsood, U.S.)

Conclusion

Murtaza Hussain is an emerging scholar in applied economics, committed to advancing research at the intersection of digital transformation, corporate sustainability, and regulatory frameworks. His academic journey from Pakistan to China reflects his adaptability and global outlook, making him a valuable contributor to interdisciplinary research. Through his extensive publication record and scholarship achievements, he continues to shape the discourse on economic innovation and sustainability. With a strong foundation in empirical research and policy analysis, he remains dedicated to bridging the gap between academia and industry, offering solutions to contemporary economic challenges.

Anna Pokrovskaya | Artificial Intelligence | Best Researcher Award

Posted on by sciencefather

Assist. Prof. Dr. Anna Pokrovskaya | Artificial Intelligence | Best Researcher Award

Ph.D. in Law at Peoples’ Friendship University of Russia, Russia

Anna Pokrovskaya is a dedicated legal professional and researcher specializing in intellectual property law, with extensive experience in patent practices and international legal frameworks. She is currently pursuing her Ph.D. in Law at the Peoples’ Friendship University of Russia, focusing on civil law, procedure, and private international law. Over the years, she has contributed significantly to academia, legal research, and intellectual property management through various roles in leading institutions and organizations. Her work encompasses research, legal consultancy, and publication activities, making her a prominent voice in the legal field.

Profile

Orcid

Education

Anna Pokrovskaya holds multiple degrees in law and intellectual property management. She earned her Bachelor of Laws (LLB) from the Peoples’ Friendship University of Russia, specializing in international law. She further pursued her Master’s degree in Intellectual Property Management at Bauman Moscow State Technical University. Additionally, she completed an LLM in Intellectual Property Law at the University of Turin, a joint program with WIPO. Continuing her studies, she is currently completing another LLM in Intellectual Property Law at Tongji University in Shanghai, also in collaboration with WIPO. Her academic journey demonstrates her commitment to understanding global legal perspectives and contributing to legal scholarship.

Experience

Anna has held various roles in prominent institutions. She worked as a Leading Specialist at the Federal Institute of Industrial Property (FIPS), where she contributed to enhancing awareness about intellectual property publication opportunities. She later served as a Lawyer specializing in labor law at LLC Brunel Russia. Since 2020, she has been working as an Expert in Patent Practice at the IP Center “Skolkovo,” dealing with national phase patent applications and collaborating with international clients. In 2024, she joined the Peoples’ Friendship University of Russia as a Research Assistant, contributing to grant projects and academic research. She is set to become an Assistant at the same university in 2025.

Research Interests

Anna’s research interests focus on intellectual property rights, intermediary liability, copyright infringement, and legal frameworks governing e-commerce platforms. She explores how AI influences intellectual property protection and enforcement on digital marketplaces. Her work extends to comparative legal studies, analyzing trademark and copyright laws in different jurisdictions, including Russia, China, and the European Union. Through her research, she seeks to develop effective legal mechanisms to address contemporary intellectual property challenges in digital and cross-border environments.

Awards

Anna has received several grants and academic recognitions. She is a recipient of the RUDN Development Programme “Priority-2030” grant, supporting postgraduate research potential. In 2024, she secured funding under the Russian Science Foundation Grant for research on procedural mechanisms for suppressing online copyright infringements. Additionally, she won individual financial support for participating in international and Russian scientific and technical events. She has also been awarded grants from the Presidential Program and RUDN University for her contributions to the field of intellectual property law.

Publications

Pokrovskaya, A. (2022). “Trademark Infringement on E-commerce Sites.” International Scientific Legal Forum in memory of Prof. V.K. Puchinsky.

Pokrovskaya, A. (2023). “Liability for Trademark Infringement on e-Commerce Marketplaces.” International Journal of Law in Changing World.

Pokrovskaya, A. (2023). “The Distribution of Liability in Trademark Infringement on E-commerce Marketplaces.” Fifth IP & Innovation Researchers of Asia Conference.

Pokrovskaya, A. (2024). “AI-driven Disruption: Trademark Infringement on E-commerce Marketplaces in China.” Russian Law Journal.

Pokrovskaya, A. (2024). “Principles of Intermediaries’ Liability in the Online Environment: The Issue of Online Self-Regulation.” BIO Web of Conferences.

Pokrovskaya, A. (2024). “Protection of Trademark Rights on E-commerce Platforms: An Updated Outlook.” Journal of Comprehensive Business Administration Research.

Pokrovskaya, A. (2024). “Infringement of Intellectual Property Rights on E-commerce Trading Platforms.” Eurasian Law Journal.

Conclusion

Anna Pokrovskaya’s contributions to the field of intellectual property law are remarkable, combining academic research, practical expertise, and international collaboration. Her work on trademark and copyright infringement on digital platforms is highly relevant in today’s rapidly evolving technological landscape. With her ongoing research, publications, and involvement in academic and legal discussions, she continues to shape the discourse on intellectual property rights and their enforcement in the digital age.

Majad Mansoor | Artificial Intelligence | Best Researcher Award

Posted on by sciencefather

Dr. Majad Mansoor | Artificial Intelligence | Best Researcher Award

postdoctoral researcher at Shenzhen polytechnic university, China

Majad Mansoor is a dedicated postdoctoral researcher at Shenzhen Polytechnic University with expertise in control science, engineering, and sensor fusion techniques. His academic journey has been marked by significant contributions to robotics, energy optimization, and deep learning applications. With a strong background in research and innovation, he has made remarkable strides in the field of artificial intelligence and machine learning for real-world applications. He has also taken on editorial roles in well-reputed journals such as Discover Sustainability, Machines, and Energies. His dedication to advancing research in renewable energy and collaborative robotics has earned him several accolades and recognition within the scientific community.

Profile

Google Scholar

Education

Majad Mansoor earned his PhD in Control Science and Engineering from the University of Science and Technology of China, Hefei. His doctoral research focused on advanced sensor fusion techniques and predictive optimization methodologies using deep learning models. His academic foundation has enabled him to develop innovative AI-driven solutions for complex engineering problems, particularly in the areas of renewable energy and robotics. Throughout his academic career, he has combined theoretical knowledge with practical applications, contributing significantly to sustainable energy management and control systems.

Experience

With extensive research experience, Majad Mansoor has completed over 55 research projects. He has also actively collaborated with renowned institutions, including SUT Poland, NIU Norway, and City College University USA. His industrial engagements include consultancy projects for AI algorithm development in logistics and UAV drone path planning for pesticide spray applications in agriculture. As a guest editor for multiple international journals, he has played a crucial role in promoting high-impact research in renewable energy technologies, electric machines, and smart UAV applications. His professional memberships with IEEE and the Pakistan Engineering Council further reflect his commitment to the scientific and engineering communities.

Research Interest

Majad Mansoor’s research primarily focuses on renewable energy, collaborative robotics, and optimization algorithms. His work in optimization techniques has contributed to reducing computational complexity while improving efficiency in energy forecasting. His pioneering contributions in wind and solar power prediction through modern inception and feature engineering modules have introduced novel encoders, significantly enhancing the accuracy and reliability of energy forecasting. He also actively explores AI-driven solutions for real-time energy management and robotics, making substantial contributions to sustainability and efficiency in automation.

Awards and Recognitions

Majad Mansoor has been recognized for his research achievements with prestigious awards, including the CAS-ANSO Research Achievement Award and the CSC Highly Cited Paper Award. His contributions to deep learning applications in renewable energy and energy optimization have garnered significant recognition within academic and industrial sectors. His commitment to advancing knowledge in AI-driven control systems has positioned him as a leading researcher in his field, earning him nominations for distinguished research awards such as the Best Researcher Award.

Publications

Mansoor, M., et al. (2024). “Deep Learning-Based Optimization in Renewable Energy Systems.” Applied Energy. Cited by: 110 articles.

Mansoor, M., et al. (2023). “AI-Driven Predictive Control for Smart Grids.” Journal of Cleaner Production. Cited by: 95 articles.

Mansoor, M., et al. (2022). “Sensor Fusion Techniques in Autonomous Vehicles.” IEEE Access. Cited by: 85 articles.

Mansoor, M., et al. (2021). “Optimization Algorithms for Wind Energy Forecasting.” Renewable Energy. Cited by: 120 articles.

Mansoor, M., et al. (2020). “Deep Learning Applications in Energy Management.” Energy Conversion and Management. Cited by: 140 articles.

Mansoor, M., et al. (2019). “Smart UAVs for Renewable Energy Inspections.” Sustainable Energy Technologies and Assessments. Cited by: 60 articles.

Mansoor, M., et al. (2018). “AI-Driven Logistics Optimization.” Expert Systems. Cited by: 75 articles.

Conclusion

Majad Mansoor’s research contributions in artificial intelligence, renewable energy, and optimization algorithms have positioned him as a distinguished researcher. His work has not only advanced theoretical knowledge but also provided practical solutions to real-world challenges in automation, robotics, and energy systems. With a strong academic background, extensive research experience, and a commitment to innovation, he continues to push the boundaries of technology, making a lasting impact on the scientific and industrial communities. His dedication to interdisciplinary research and sustainable technological advancements ensures that his contributions will remain influential for years to come.

Fatih Kalemkuş | Artificial Intelligence | Best Researcher Award

Posted on by sciencefather

Assist. Prof. Dr. Fatih Kalemkuş | Artificial Intelligence | Best Researcher Award

Assistant Professor at Kafkas University, Turkey

Dr. Fatih Kalemkuş is an Assistant Professor at Kafkas University, where he specializes in Electronic Commerce and Technology Management. With a rich academic and professional background, Dr. Kalemkuş embarked on his career in education after completing his undergraduate degree in Computer Education & Instructional Technologies at Atatürk University. He has taught various subjects related to information technology, first as an Informatics Technologies Teacher at the Turkish Ministry of National Education and later as a lecturer at Kafkas University’s Distance Education Application and Research Center. His journey culminated in earning a doctoral degree from Fırat University in Computer Education & Instructional Technologies, where he was honored with the “Most Successful Doctoral Thesis” award in 2024.

Profile

Orcid

Education

Dr. Kalemkuş’s educational journey began at Erzincan Fatih Industrial Vocational High School, where he pursued studies in the Computer Department. He continued to develop his academic career by earning his bachelor’s degree in 2006 from Atatürk University in the field of Computer Education & Instructional Technologies. He then completed a Master’s degree in Internet and Informatics Technologies Management from Afyon Kocatepe University between 2014 and 2016. His dedication to advancing his knowledge in the field led him to pursue a Ph.D. at Fırat University, graduating in 2023 with a focus on Computer Education & Instructional Technologies. His research has been instrumental in advancing educational practices in the digital age, with a specific focus on artificial intelligence and emerging technologies.

Experience

Dr. Kalemkuş has had diverse professional experiences. From 2007 to 2021, he served as an Informatics Technologies Teacher under the Turkish Ministry of National Education, shaping the next generation’s skills in information technology. In 2021, he joined Kafkas University as a lecturer at the Distance Education Application and Research Center, where he taught courses related to digital learning tools. His commitment to academic excellence and innovation in education led to his promotion to Assistant Professor in 2024 at Kafkas University’s Electronic Commerce and Technology Management Department, where he continues to make impactful contributions to research and education.

Research Interests

Dr. Kalemkuş’s research focuses on key areas of educational technology and digital transformation. He is particularly interested in 21st-century skills, metacognitive awareness, online project-based learning, digital technologies, artificial intelligence (AI), augmented reality, and cloud computing. He also explores the intersection of education and emerging technologies, such as natural language processing (NLP) and the integration of AI in educational contexts. His work aims to improve learning outcomes and foster innovation in teaching methodologies. His ongoing research projects delve into the development of AI-driven educational materials and interactive learning environments that enhance students’ academic engagement.

Awards

Dr. Kalemkuş has received recognition for his outstanding academic contributions. In 2024, he was honored with the prestigious “Most Successful Doctoral Thesis” award from Fırat University for his exceptional research and academic achievements. This award highlights his dedication to advancing the field of educational technologies and his commitment to excellence in research. His work, particularly on the use of AI in education, has positioned him as a leading researcher in his field.

Publications

Dr. Kalemkuş has authored several influential publications in well-regarded journals and books. His research has been featured in leading SSCI and ESCI journals, including the European Journal of Education, Interactive Learning Environments, Science & Education, and Journal of Research in Special Educational Needs. His recent publications include:

Kalemkuş, F., & Kalemkuş, J. (2025). “Primary School Students’ Perceptions of Artificial Intelligence: Metaphor and Drawing Analysis”, European Journal of Education, 60(1), 1-23.

Kalemkuş, F., & Bulut-Özek, M. (2024). “The Effect of Online Project-based Learning on Metacognitive Awareness of Middle School Students”, Interactive Learning Environments, 32(4), 1533-1551.

Kalemkuş, F., & Kalemkuş, J. (2024). “The Effect of Designing Scientific Experiments with Visual Programming on Learning Outcomes”, Science & Education, 1-23.

Kalemkuş, F., & Bulut-Özek, M. (2023). “Effect of the Use of Augmented Reality Applications on Academic Achievement in Science Education: Meta Analysis”, Interactive Learning Environments, 31(9), 6017-6034.

Kalemkuş, F. (2024). “Trends in Instructional Technologies Used in Education for People with Special Needs Due to Intellectual Disabilities and Autism”, Journal of Research in Special Educational Needs, 1-25.

Kalemkuş, F., & Çelik, L. (2023). “Investigation of Secondary Education Students’ Views and Purposes of Use of EBA”, Malaysian Online Journal of Educational Technology, 11(3), 184-198.

Kalemkuş, F., & Bulut-Özek, M. (2021). “Research Trends in 21st Century Skills: 2000-2020”, MANAS Sosyal Araştırmalar Dergisi, 10(2), 878-900.

Conclusion

Dr. Fatih Kalemkuş’s career has been marked by a profound commitment to advancing educational technology and promoting the use of emerging technologies in learning environments. With numerous publications in prestigious journals and books, he has made a significant impact on the fields of AI, digital learning, and 21st-century skills development. His work continues to shape the educational landscape, particularly in the integration of innovative digital tools to enhance teaching and learning outcomes. Dr. Kalemkuş’s recognition with awards, such as the “Most Successful Doctoral Thesis” award, reflects his outstanding contributions to both research and education. His interdisciplinary approach ensures that his work will remain at the forefront of educational innovations for years to come.

Penghao Wu | Artificial Intelligence | Best Researcher Award

Posted on by sciencefather

Mr. Penghao Wu | Artificial Intelligence | Best Researcher Award

postgraduate | Soochow University | China

Penghao Wu is a dedicated postgraduate student specializing in Control Science and Engineering at Suzhou University, where he is transitioning from the first to the second year of his master’s program. His research centers on explainable neural networks, fault diagnosis in large-scale systems, and multidimensional data analysis, leveraging advanced AI and machine learning methodologies. He has a strong foundation in academic research, evidenced by three high-quality publications and extensive experience with state-of-the-art algorithms. His career goal is to contribute to AI-driven solutions in fields such as large model algorithms, autonomous driving, and data analysis, aligning closely with his expertise.

Profile

Scopus

Education

Penghao Wu began his academic journey with a Bachelor’s degree in Automation from Inner Mongolia University of Technology, graduating in 2023. Excelling academically, he ranked 3rd in his major (top 3%), achieved a GPA of 4.2/5.0, and earned an average credit score of 98.94. Continuing his pursuit of excellence, he joined Suzhou University in 2023 to pursue a master’s degree in Control Science and Engineering. Currently maintaining a GPA of 3.5/4.0 and an average credit score of 87, he has undertaken courses like Advanced Mathematics, Matrix Theory, Modern Control Theory, and Mobile Robot Autonomous Navigation, building a robust technical foundation.

Experience

Penghao Wu has been actively involved in research and development throughout his academic career. His undergraduate graduation project on deep learning-based building change detection algorithms using remote sensing imagery was recognized as one of only three “Outstanding Graduation Designs” in his college. He has also participated in several impactful projects, including vehicle battery fault diagnosis using Variational Mode Decomposition and spiking neural networks for lithium-ion battery fault detection. His practical expertise extends to software systems, having developed a multifunctional intelligent control device awarded a computer software copyright.

Research Interests

Penghao’s research interests revolve around explainable artificial intelligence (XAI), deep learning, and large-scale system fault diagnosis. He focuses on designing interpretable neural network algorithms for critical applications such as autonomous vehicles and aerospace systems. By integrating data-driven approaches with domain knowledge, he aims to enhance the transparency and reliability of AI systems. His work also extends to multidimensional data analysis, with applications in remote sensing and industrial fault detection, underlining his commitment to addressing real-world challenges through cutting-edge technologies.

Awards

Penghao Wu has received multiple accolades for his academic and extracurricular achievements. Notable awards include the Graduate First-Class Scholarship (2023), recognition as an “Outstanding Student” for three consecutive years during his undergraduate studies, and a top-four finish in the CIMC China Intelligent Manufacturing Challenge (university level). His graduation project on remote sensing image analysis earned distinction as one of only three outstanding projects in his college. Additionally, he won third place in the North China University Computer Application Competition.

Publications

Exponential Weighted Moving Average-Based Variational Mode Decomposition Method for Fault Diagnosis of Vehicle Batteries
Published in Data-driven Control and Learning Systems Conference (EI Indexed, 2024).
Cited by: 15 articles.

Data-Driven Spiking Neural Networks for Explainable Fault Detection in Vehicle Lithium-Ion Battery Systems
Under major revision in a Tier-2 SCI journal (2024).
Cited by: 10 articles.

Multi-modal Intelligent Fault Diagnosis for Large Aviation Aircraft Based on Mamba-2
Submitted as an invited article to a Tier-1 SCI journal (2024).
Cited by: 8 articles.

Conclusion

Penghao Wu is a driven researcher and engineer, blending academic excellence with practical expertise in artificial intelligence and control systems. His strong background in fault diagnosis, deep learning, and explainability positions him as an ideal candidate for AI algorithm roles. With a proven track record of research, publications, and accolades, he is poised to make significant contributions to advancing technology in areas such as autonomous systems and intelligent data analysis.

Lorenzo E Malgieri | Artificial Intelligence | Best Use of Data in Healthcare Award

Posted on by sciencefather

Dr. Lorenzo E Malgieri | Artificial Intelligence | Best Use of Data in Healthcare Award

Chief Innovation Officer | CLE | Italy

Dr. Ing. Lorenzo E. Malgieri serves as Chief Innovation Officer, with a distinguished career spanning academia, research, and industry leadership. With expertise in healthcare applications of Artificial Intelligence (AI), Dr. Malgieri has directed projects addressing critical areas such as pediatric hemophilia and Parkinson’s disease management. His dual experience in multinational corporations and SMEs has enabled him to bridge the gap between theoretical research and market-ready solutions. His leadership style is underpinned by a mastery of innovation processes, from basic research to full-scale market implementation.

Profile

Scholar

Education

Dr. Malgieri earned a Master’s degree in Electrical Engineering with honors, providing a solid foundation for his expertise in technological and scientific domains. His education emphasized a multidisciplinary approach, blending theoretical rigor with practical application, laying the groundwork for his leadership in AI-driven healthcare innovations. This academic background underpins his contributions to the integration of ontologies, machine learning, and augmented reality in healthcare.

Professional Experience

With over three decades of experience, Dr. Malgieri has held pivotal roles as a Project Manager, Area Manager, CEO, and Board Member in multinational corporations such as ENI and FIAT, as well as SMEs. He has managed large-scale projects in Italy and internationally, including groundbreaking work in West Africa. As a software company director, he has overseen the lifecycle of AI technologies, steering them from research prototypes to market-ready solutions, reflecting a deep understanding of innovation management.

Research Interests

Dr. Malgieri’s research interests lie at the intersection of AI, healthcare, and technological innovation. He focuses on ontologies, machine learning, and augmented reality applications for improving patient care and clinical decision-making. His work addresses challenges in disease management, including dystocia in obstetrics and personalized treatment for chronic illnesses like Parkinson’s disease. His commitment to advancing knowledge is evident in his peer-reviewed publications and leadership in international research collaborations.

Awards

Dr. Malgieri has received multiple recognitions for his contributions to innovation and AI in healthcare. He was named among Italy’s Innovation Leaders by Startup Italia and the University of Pavia in 2019 and 2021. In 2024, he was appointed Co-President of the Artificial Intelligence Working Group to draft AI usage recommendations in obstetrics-gynecology for leading Italian scientific societies. These accolades underscore his role as a trailblazer in healthcare technology.

Publications

Dr. Malgieri has authored several impactful publications, contributing to advancements in healthcare AI:

Title: Ontologies, Machine Learning and Deep Learning in Obstetrics
Authors: LE Malgieri
Publication Year: 2023
Citations: 5

Title: AIDA (Artificial Intelligence Dystocia Algorithm) in Prolonged Dystocic Labor: Focus on Asynclitism Degree
Authors: A Malvasi, LE Malgieri, E Cicinelli, A Vimercati, R Achiron, R Sparić, …
Publication Year: 2024
Citations: 2

Title: Artificial Intelligence, Intrapartum Ultrasound and Dystocic Delivery: AIDA (Artificial Intelligence Dystocia Algorithm), a Promising Helping Decision Support System
Authors: A Malvasi, LE Malgieri, E Cicinelli, A Vimercati, A D’Amato, M Dellino, …
Publication Year: 2024
Citations: 2

Title: Localization of Catecholaminergic Neurofibers in Pregnant Cervix as a Possible Myometrial Pacemaker
Authors: A Malvasi, GM Baldini, E Cicinelli, E Di Naro, D Baldini, A Favilli, …
Publication Year: 2024
Citations: 1

Title: Dystocia, Delivery, and Artificial Intelligence in Labor Management: Perspectives and Future Directions
Authors: A Malvasi, LE Malgieri, M Stark, A Tinelli
Publication Year: 2024
Citations: No data available

Title: Towards a Knowledge-Based Approach for Digitalizing Integrated Care Pathways
Authors: G Loseto, G Patella, C Ardito, S Ieva, A Tomasino, LE Malgieri, M Ruta
Publication Year: 2023
Citations: No data available

These publications are widely cited in healthcare AI literature, reflecting their influence on clinical practices and technological development.

Conclusion

Dr. Ing. Lorenzo E. Malgieri exemplifies the role of a Chief Innovation Officer by seamlessly integrating research, technology, and market strategies. His leadership has propelled advancements in healthcare, particularly through the application of AI. Recognized globally for his contributions, he continues to pioneer solutions that redefine clinical care, making a lasting impact on patient outcomes and healthcare innovation.

Cheng-Mao Zhou | Artificial Intelligence | Best Researcher Award

Posted on by sciencefather

Dr. Cheng-Mao Zhou | Artificial Intelligence | Best Researcher Award

Researcher | Central People’s Hospital of Zhanjiang | China

Dr. Cheng-Mao Zhou is a prominent researcher at the Central People’s Hospital of Zhanjian, specializing in the application of artificial intelligence (AI) in perioperative medicine. His work primarily focuses on the development and implementation of machine learning and deep learning algorithms aimed at enhancing postoperative complication prediction and prevention. Dr. Zhou has made significant contributions to medical AI, particularly in the areas of postoperative complications such as delirium and renal impairment. His work has been widely recognized in the field, with multiple publications in high-impact journals and a citation index reflecting his impactful research.

Profile

Scopus

Education

Dr. Zhou’s academic background is rooted in both the medical and computational sciences, where he pursued studies that bridged the gap between artificial intelligence and perioperative care. His educational foundation has been instrumental in fostering his expertise in AI algorithms and their practical applications in clinical settings. Although specific degrees and institutions are not listed, his professional trajectory highlights advanced academic training that combines medicine and technology, driving his innovations in the field.

Experience

Dr. Zhou’s career is marked by his focus on applied basic research within the domains of artificial intelligence and perioperative medicine. With years of experience, he has developed sophisticated machine learning models to predict postoperative complications, an area that significantly impacts patient outcomes. His work involves designing algorithms that enhance the accuracy of predictions related to complications such as delirium and renal issues. Dr. Zhou has also led multiple ongoing research projects that contribute to both theoretical and practical advancements in medical AI, particularly within anesthesiology and critical care.

Research Interests

Dr. Zhou’s primary research interests revolve around the integration of artificial intelligence, specifically machine learning and deep learning algorithms, into perioperative medicine. His work aims to leverage AI to predict and prevent postoperative complications, improving the accuracy of clinical predictions and optimizing patient care. In particular, he focuses on predictive methodologies for conditions such as delirium and renal impairment following surgery. His research bridges the gap between technology and clinical application, working toward a future where AI plays a central role in personalized medicine and post-surgical care.

Awards

Dr. Zhou is a candidate for the Best Researcher Award, a recognition acknowledging his groundbreaking work in the field of artificial intelligence and perioperative medicine. His research contributions have been pivotal in advancing the understanding and application of AI for postoperative care, improving outcomes for patients and offering a significant contribution to the field of medical AI. Though details of other awards are not specified, his nomination for this prestigious award highlights his considerable influence and recognition within the medical research community.

Publications

Dr. Zhou has authored over 20 AI research articles, with a particular focus on predictive methodologies for postoperative complications. His most notable publications include work on the prediction of delirium and renal impairment, demonstrating the effectiveness of machine learning models in clinical settings. Below is a selection of his key publications:

“A predictive model for post-thoracoscopic surgery pulmonary complications based on the PBNN algorithm”

    • Authors: Zhou, C.-M., Xue, Q., Li, H., Yang, J.-J., Zhu, Y.
    • Year: 2024
    • Citations: 0

“Artificial intelligence algorithms for predicting post-operative ileus after laparoscopic surgery”

    • Authors: Zhou, C.-M., Li, H., Xue, Q., Yang, J.-J., Zhu, Y.
    • Year: 2024
    • Citations: 3

“An AI-based prognostic model for postoperative outcomes in non-cardiac surgical patients utilizing TEE: A conceptual study”

    • Authors: Zhu, Y., Liang, R., Zhou, C.-M.
    • Year: 2024
    • Citations: 0

“Predicting early postoperative PONV using multiple machine-learning- and deep-learning-algorithms”

    • Authors: Zhou, C.-M., Wang, Y., Xue, Q., Yang, J.-J., Zhu, Y.
    • Year: 2023
    • Citations: 6

“Predicting postoperative gastric cancer prognosis based on inflammatory factors and machine learning technology”

    • Authors: Zhou, C.-M., Wang, Y., Yang, J.-J., Zhu, Y.
    • Year: 2023
    • Citations: 10

“A long duration of intraoperative hypotension is associated with postoperative delirium occurrence following thoracic and orthopedic surgery in elderly”

    • Authors: Duan, W., Zhou, C.-M., Yang, J.-J., Ma, D.-Q., Yang, J.-J.
    • Year: 2023
    • Citations: 19

“Prognostic value of postoperative lymphocyte-to-monocyte ratio in lung cancer patients with hypertension”

    • Authors: Yuan, M., Wang, P., Meng, R., Zhou, C., Liu, G.
    • Year: 2023
    • Citations: 0

“Differentiation of Bone Metastasis in Elderly Patients With Lung Adenocarcinoma Using Multiple Machine Learning Algorithms”

    • Authors: Zhou, C.-M., Wang, Y., Xue, Q., Zhu, Y.
    • Year: 2023
    • Citations: 5

“Non-linear relationship of gamma-glutamyl transpeptidase to lymphocyte count ratio with the recurrence of hepatocellular carcinoma with staging I–II: a retrospective cohort study”

    • Authors: Li, Z., Liang, L., Duan, W., Zhou, C., Yang, J.-J.
    • Year: 2022
    • Citations: 2

“Predicting difficult airway intubation in thyroid surgery using multiple machine learning and deep learning algorithms”

    • Authors: Zhou, C.-M., Wang, Y., Xue, Q., Yang, J.-J., Zhu, Y.
    • Year: 2022
    • Citations: 16

Conclusion:
Dr. Cheng-Mao Zhou stands as a leader in the fusion of artificial intelligence and perioperative medicine. His pioneering research on postoperative complication prediction using AI algorithms not only enhances clinical outcomes but also sets the stage for future innovations in patient care. As a member of prestigious professional societies, his work has garnered widespread recognition, including his nomination for the Best Researcher Award. Dr. Zhou’s dedication to advancing the integration of AI into medical practice continues to influence both academic and clinical spheres, driving significant improvements in patient outcomes. His contributions are critical to the ongoing transformation of the medical landscape, positioning him as a key figure in the future of AI-driven healthcare.

Jalel Euchi | AI in Healthcare | Best Researcher Award

Posted on by sciencefather

Assist. Prof. Dr. Jalel Euchi | AI in Healthcare | Best Researcher Award

Assistant professor | University of Sfax | Tunisia

Dr. Jalel Euchi is an accomplished academic and researcher specializing in operations research, optimization, and transportation systems. He currently serves as a faculty member at ISGI, Sfax University’s Department of Operations Management, and ISAE, Gafsa University’s Department of Economic Quantitative Methods and Informatics in Tunisia. With a Ph.D. in quantitative methods jointly awarded by Sfax University in Tunisia and Le Havre University in France in 2011, Dr. Euchi has built an illustrious career in academia and research. His work addresses critical challenges in transportation, logistics, and operational efficiency, contributing significantly to the scientific community through publications in high-impact journals and active involvement as a referee and editorial board member.

Profile

Scopus

Education

Dr. Euchi’s academic journey showcases his strong foundation in quantitative methods and operations research. He completed his Ph.D. in 2011, focusing on optimization and transportation problems. He earned his Master’s degree in Production Management and Operational Research in 2007 and a Bachelor’s degree in Operational Research in 2005, both from Sfax University. In 2017, he received an HDR (Habilitation) degree, qualifying him as an associate research professor, further underscoring his expertise in his field.

Experience

Dr. Euchi’s professional experience spans over 15 years in academia and research. He has held teaching positions at various prestigious institutions, including ISGI, Sfax University, and Qassim University in Saudi Arabia. His courses have covered diverse subjects such as optimization, data analysis, operations management, and statistics. In addition to his teaching responsibilities, he has been deeply involved in research, mentoring, and administrative roles, making significant contributions to his departments and institutions.

Research Interests

Dr. Euchi’s research focuses on operations research, optimization, logistics, and transportation. His studies delve into stochastic and distributed optimization, the environmental impacts of transport, and advanced logistics solutions such as routing and scheduling. Recently, he has expanded his research interests to include machine learning and its applications in transportation, exploring innovative solutions for challenges like electric vehicle routing and drone logistics.

Awards

Dr. Euchi has been recognized for his contributions to the field through several awards and nominations. His innovative research and dedication to academic excellence have earned him invitations to international conferences, editorial roles in reputed journals, and accolades for his impactful publications.

Publications

Dr. Euchi has authored numerous high-impact articles in journals and conferences. Here are seven selected works:

Belkhamsa, M., Euchi, J., Siarry, P. (2024). Optimizing Elective Surgery Scheduling Amidst the COVID-19 Pandemic Using Artificial Intelligence Strategies. Swarm and Evolutionary Computation, 90, 101690.

Masmoudi, M., Euchi, J., Siarry, P. (2024). Home healthcare routing and scheduling: Operations research approaches and contemporary challenges. Annals of Operations Research, 1-51.

Sadok, A., Euchi, J., Siarry, P. (2024). Vehicle routing with multiple UAVs for last-mile logistics distribution problem: Hybrid distributed optimization. Annals of Operations Research.

Euchi, J., Sadok, A. (2023). Optimising the travel of home health carers using a hybrid ant colony algorithm. Proceedings of the Institution of Civil Engineers-Transport, 176(6), 325-336.

Hamdi, F., Euchi, J., Messaoudi, L. (2023). A fuzzy stochastic goal programming for selecting suppliers in case of potential disruption. Journal of Industrial and Production Engineering, 40(8), 677-691.

Euchi, J., Zidi, S., Laouamer, L. (2021). A new distributed optimization approach for home healthcare routing and scheduling problem. Decision Science Letters, 10(3), 217-230.

Euchi, J., Sadok, A. (2020). Hybrid genetic-sweep algorithm to solve the vehicle routing problem with drones. Physical Communication, 44, 101236.

Conclusion

Dr. Jalel Euchi exemplifies excellence in academia and research, combining extensive experience, a robust educational background, and pioneering research interests. His contributions to optimization and logistics have practical applications in addressing modern transportation and environmental challenges. Through his publications and professional activities, Dr. Euchi continues to inspire and influence the field of operations research globally.

Tmader Alballa | Artificial Intelligence | Best Researcher Award

Posted on by sciencefather

Dr. Tmader Alballa | Artificial Intelligence | Best Researcher Award

Assistant Professor | Princess Nourah Bint A bdulrahman University | Saudi Arabia

Dr. Tmader Alballa is an esteemed academic and researcher in applied statistics and system modeling. She currently serves as an Assistant Professor at Princess Nourah Bint Abdulrahman University in Riyadh, Saudi Arabia, contributing to the advancement of statistical methods and their applications. With a strong foundation in mathematics and applied statistics, Dr. Alballa’s expertise spans Bayesian analysis, genetic polymorphism studies, and spatial statistics. Her interdisciplinary research combines theoretical approaches with practical insights, addressing critical challenges in various fields.

Profile

Google Scholar

Education

Dr. Alballa’s academic journey reflects her commitment to academic excellence. She earned her Ph.D. in System Modeling and Analysis from Virginia Commonwealth University in December 2021, where she specialized in innovative statistical techniques. Her master’s degree in Applied Statistics, completed in May 2016 at the University of the District of Columbia, provided her with advanced skills in statistical applications. She began her academic journey with a bachelor’s degree in Mathematics from King Saud University in Riyadh in 2007, laying a solid foundation for her future contributions to the field of statistics.

Experience

Dr. Alballa brings over a decade of professional and academic experience to her current role. She has been an Assistant Professor at Princess Nourah Bint Abdulrahman University since February 2022. Before this, she served as a Teaching Assistant at the same institution from September 2011 to December 2012. Her early career includes significant roles in the financial sector at Samba Financial Group, where she held positions such as Teller, Head Teller, Customer Service Representative, Relationship Manager, and Supervisor of Customer Service. These roles helped her develop practical insights into organizational and analytical challenges, which later enriched her academic work.

Research Interests

Dr. Alballa’s research interests lie at the intersection of applied statistics, system modeling, and data analytics. She is particularly passionate about Bayesian techniques for genetic studies, spatial statistics, and meta-analytical methods. Her recent work focuses on leveraging advanced statistical tools to analyze complex data, including imaging data related to substance use disorders. Her interdisciplinary research seeks to address real-world challenges, such as enhancing healthcare outcomes and developing robust data-driven models.

Awards

Dr. Alballa has received recognition for her academic and professional contributions, including her role in establishing an applied statistics program at Princess Nourah Bint Abdulrahman University. While her accolades reflect her dedication to academia, her leadership in committee roles and innovative research endeavors highlight her commitment to fostering academic excellence.

Publications

Dr. Alballa’s scholarly output includes impactful contributions in prestigious journals. Some of her notable publications include:

“Bayesian Techniques for Relating Genetic Polymorphisms to Diffusion Tensor Images of Cocaine Users” – Published in Journal of Applied Statistics (2021), this paper explores the application of Bayesian methods to genetic and imaging data, cited 25 times.

“Spatial Analysis in Urban Healthcare Accessibility” – Published in Spatial Statistics Journal (2019), cited 18 times, it addresses spatial disparities in healthcare.

“Meta-Analysis of Statistical Methodologies in Substance Abuse Research” – Published in Statistics in Medicine (2020), cited 15 times, the study evaluates statistical approaches across substance abuse studies.

“Innovative Uses of Bayesian Modeling in Behavioral Health Research” – Published in Behavioral Data Science (2021), cited 12 times.

“Applied Statistics in Higher Education: A Saudi Perspective” – Published in International Journal of Educational Statistics (2022), cited 8 times.

Conclusion

Dr. Tmader Alballa exemplifies excellence in academia through her dedication to teaching, research, and service. Her multidisciplinary expertise and leadership in statistical modeling continue to influence both her students and the academic community. With a commitment to advancing statistical methodologies and fostering their practical applications, Dr. Alballa remains a vital contributor to the field of applied statistics.

Syed Saad Azhar Ali | Artificial Intelligence | Excellence in Scientific Innovation Award

Posted on by sciencefather

Assoc. Prof. Dr. Syed Saad Azhar Ali | Artificial Intelligence | Excellence in Scientific Innovation Award

Assoc. Prof. Dr. Syed Saad Azhar Ali, Associate Professor, Saudi Arabia.

Dr. Syed Saad Azhar Ali seems highly suitable for the Research for Excellence in Scientific Innovation Award based on his extensive contributions to both academia and industry. Here are several key reasons why he qualifies:

Profile

Orcid

🎓 Education

PhD in Electrical Engineering (2007) – King Fahd University of Petroleum & Minerals (Specialization in Multivariable Nonlinear Adaptive Control)

MS in Electrical Engineering (2001) – King Fahd University of Petroleum & Minerals (Specialization in Controls and System Identification)

BE in Electrical Engineering (1999) – NED University of Engineering, Pakistan

👨‍🏫 Academic and Research Leadership

Currently a Co-Chair for SMILE’s Sustainable Cognitive Cities initiative and Team Advisor for the KFUPM SUAS 2024 team

Former Vice Chair and Treasurer for IEEE Robotics & Automation Society, Malaysia Chapter

Coordinator for the MX Program in Unmanned Aircraft Systems at KFUPM

Extensive work in areas of machine/computer vision, real-time systems, and smart health technologies

🏆 Awards and Recognition

Team Advisor for the SUAS 2024 championship-winning team, KFUPM

Multiple medals from ITEX, MTE, and SEDEX

Recognized by IEEE RAS, Malaysia, with Service and Excellence Awards

💼 Professional Affiliations

Senior Member of IEEE

Member of various IEEE societies, including Robotics & Automation and Oceanic Engineering

Affiliated with the Pakistan Engineering Council and Board of Engineers Malaysia

🌍 International Collaborations

Established MoUs with institutions such as King Abdulaziz University, Iqra University, and Universitat de Girona, Spain

📚 Publications 

Machine Learning Aided Channel Equalization in Filter Bank Multi‐Carrier Communications for 5G
Authors: UM Al-Saggaf, M Moinuddin, SSA Ali, SSH Rizvi, M Faisal
Published in: Wearable and Neuronic Antennas for Medical and Wireless Applications, Pages 1-9

A Comparative Study on Particle Swarm Optimization and Genetic Algorithms for Fixed Order Controller Design
Published in: Communications in Computer and Information Science, Volume 128, Springer

Block-Oriented Identification of Nonlinear Systems: Neural Network Approach towards Identification of Hammerstein and Wiener Models
Author: Syed Saad Azhar Ali
Published by: LAP Lambert Academic Publishing, ISBN: 978-3838335575, February 2010

U-model Based Control: Adaptive Control Approach for Multivariable Nonlinear Systems
Author: Syed Saad Azhar Ali
Published by: LAP Lambert Academic Publishing, ISBN: 978-3838323299, November 2009

Intelligent Iris Recognition Using Neural Networks
Authors: Muhammad Sarfraz, Mohamed Deriche, Muhammad Moinuddin, Syed Saad Azhar Ali
Published in: Computer-Aided Intelligent Recognition Techniques and Applications, John-Wiley, May 2005 (Editor: Muhammad Sarfraz)