Jia Kaiewei | Artificial Intelligence | Best Scholar Award

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Dr. Jia Kaiewei | Artificial Intelligence | Best Scholar Award

Professor at Liaoning Technical University, Huludao, China

Kaiwei Jia is an accomplished academician and researcher currently serving as a Professor and Doctoral Supervisor in the field of Management Science and Engineering. He also holds the role of Vice Dean at the School of Business Administration, Liaoning Technical University. His academic journey is marked by extensive contributions to teaching, research, and institutional development. As a core member of the Liaoning Provincial Teaching Guidance Committee for Finance, he plays a significant role in shaping the financial education framework in the region. With a background in Economics and Statistics, Professor Jia has emerged as a thought leader in financial econometrics and policy research. His career is defined by a blend of theoretical insight and empirical rigor, and he has guided numerous graduate and doctoral students in their academic endeavors. Through his sustained commitment to academic excellence and administrative leadership, he has made substantial contributions to the academic community and the broader field of finance and economics.

Profile

Scopus

Education

Kaiwei Jia’s educational background is deeply rooted in economics and statistics. He earned his Ph.D. in Economics after completing a rigorous postgraduate program that emphasized macroeconomic policy, financial analysis, and quantitative methods. Subsequently, he undertook postdoctoral research in Statistics, where he refined his understanding of data interpretation, econometric modeling, and the application of statistical methodologies to economic problems. This interdisciplinary training has provided him with a comprehensive toolkit for analyzing complex economic phenomena. His academic progression reflects a strong emphasis on research-driven education, equipping him with both theoretical and practical skills. His transition from postgraduate studies to postdoctoral research marked a significant shift in his academic career, allowing him to delve deeper into areas such as financial econometrics, risk modeling, and empirical policy analysis.

Experience

Throughout his career, Professor Jia has maintained an unwavering commitment to teaching and mentoring. He has designed and delivered undergraduate, master’s, and doctoral-level courses in Econometrics, Financial Risk Management, Financial Econometrics, and Financial Data Analysis. His lectures are known for their analytical depth and emphasis on real-world application, which have earned him the respect of both peers and students. Beyond the classroom, he has played a pivotal role in curriculum development and academic governance at Liaoning Technical University. As Vice Dean, he has led several institutional initiatives aimed at enhancing academic quality and fostering innovation in finance education. Additionally, his membership in the Liaoning Provincial Teaching Guidance Committee for Finance has enabled him to influence regional academic standards, ensuring that finance education remains aligned with contemporary global developments.

Research Interest

Professor Jia’s research interests span a diverse array of topics within economics and finance. He focuses on financial stability and risk management, particularly the dynamics of financial contagion and systemic risk. His work explores the governance and risk prevention mechanisms in financial institutions, combining institutional theory with quantitative modeling. Additionally, he is deeply engaged in the study of monetary policy theory and methodology, emphasizing both the rules-based and discretionary approaches to macroeconomic regulation. His research extends to econometric methods, where he utilizes advanced statistical techniques to analyze financial and economic data. More recently, he has contributed to emerging areas such as green finance and climate finance, investigating how environmental factors intersect with financial risk and investment decisions. His multidisciplinary research approach integrates macroeconomic theory, quantitative analysis, and policy insights.

Award

In recognition of his scholarly achievements and academic leadership, Professor Jia has received several prestigious awards. He was honored with the First Prize in the 7th Liaoning Provincial Outstanding Achievement Award in Statistical Sciences, which acknowledges innovative contributions in statistical research. He also received the Second Prize in the Liaoning Provincial Philosophy and Social Science Achievement Award for his impactful work in economics and financial policy. These accolades reflect both the quality and societal relevance of his research, highlighting his role as a leading scholar in his field. His award-winning work has contributed to enhancing the understanding of financial risk, policy formulation, and statistical analysis at both regional and national levels.

Publication

Kaiwei Jia has published more than 30 academic papers in respected journals indexed by SSCI and CSSCI. His recent works reflect his ongoing dedication to cutting-edge research. In 2023, he co-authored “Did the ‘double carbon’ policy improve the green total factor productivity of iron and steel enterprises? A quasi-natural experiment based on carbon emission trading pilot,” published in Frontiers in Energy Research, exploring policy impact through econometric analysis. In the same year, he contributed to Frontiers in Psychology with “Digital financial and banking competition network: Evidence from China,” which examined competitive dynamics using network models. His 2022 publications include “Construction and empirical of investor sentiment evaluation system based on partial least squares” and “Empirical research of risk correlation based on Copula function method,” both appearing in the Journal of Liaoning Technical University (Natural Science Edition). These studies utilized advanced statistical tools to analyze investor behavior and risk correlation. Another 2022 work titled “Spatiotemporal Evolution of Provincial Carbon Emission Network in China,” published on SSRN, tackled environmental finance issues using spatial network methods. These publications not only reflect his diverse expertise but also have been cited by multiple articles, indicating his work’s influence within the academic community.

Conclusion

In summary, Professor Kaiwei Jia’s academic career is characterized by a strong dedication to education, a robust portfolio of interdisciplinary research, and impactful contributions to financial policy and risk management. His dual expertise in economics and statistics has allowed him to bridge theoretical frameworks with empirical application, making his research both rigorous and relevant. Through his teaching, he has nurtured the next generation of economists and financial analysts, while his administrative leadership has helped shape academic standards in finance education. His scholarly output and recognition through awards reflect a sustained contribution to the academic and policy-making community. Professor Jia continues to explore innovative themes in green finance and systemic risk, ensuring that his research remains at the forefront of addressing contemporary economic challenges.

Ruchun Jia | Artificial Intelligence | Best Researcher Award

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Assoc. Prof. Dr. Ruchun Jia | Artificial Intelligence | Best Researcher Award

Professor at College of Computer Science, Sichuan University, China

Ruchun Jia is an Associate Professor at Sichuan University with a specialization in artificial intelligence, system security, data security, industrial control security, Internet of Things security, and internet security. Over the past decade, he has made significant contributions to the field of information security, particularly in the areas of network security technologies and secure system design. Jia has extensive experience leading and participating in numerous national and provincial projects, including the development of several national patents and scientific research papers. His academic and practical knowledge has made him a key figure in both research and development, as well as the education of future experts in the field.

Profile

Orcid

Education

Ruchun Jia completed his Ph.D. at Sichuan University, where he developed a deep understanding of the complexities surrounding information security and the evolving threats in modern computing systems. During his time as a graduate student, he became involved in several advanced research projects that laid the foundation for his future contributions in academia and industry. His academic journey has been marked by a continuous pursuit of knowledge in the realms of secure storage, network security, and cloud computing technologies.

Experience

Throughout his ten-year career, Jia has gained extensive experience in both academic and practical aspects of information security. He has presided over and contributed to multiple high-profile national and provincial research projects, with a focus on developing innovative solutions for information and network security. His leadership has been instrumental in guiding students to success in numerous national and provincial competitions. Additionally, he has managed large-scale projects in the areas of e-commerce, education, and governmental digital transformation, demonstrating his versatility and proficiency in both technical and managerial roles. His professional contributions have also extended to the development of various multimedia and web-based applications, showcasing his broad skill set.

Research Interest

Ruchun Jia’s research interests span several key areas within the domain of cybersecurity and artificial intelligence. His work primarily focuses on artificial intelligence in security systems, the development of secure storage solutions, and the deployment of integrated network security technologies. He is particularly interested in the security implications of the Internet of Things (IoT) and industrial control systems. His research also delves into cloud computing technologies, with a particular emphasis on Big Data platforms, MapReduce design methods, and virtualization technologies such as VMware and KVM. Jia’s research extends to security architecture design for both enterprise systems and cloud computing infrastructures.

Award

Ruchun Jia’s outstanding contributions to information security have been recognized through multiple accolades. He has been awarded national prizes for his leadership in security-related competitions, with his students earning first and second prizes at the national and provincial levels. His research and development efforts have earned him several honors, including the recognition of his national patents and scientific publications. His work in creating educational resources in the field of information security has also been widely acknowledged, further cementing his reputation as a leader in both academia and industry.

Publication

Ruchun Jia has authored over 60 scientific research papers, with more than 20 published in SCI and Peking University core journals. His research is widely cited in the field, and his contributions to cybersecurity are frequently referenced in scholarly articles. Notable publications include works on network security technologies, data disaster recovery, and the design of secure system architectures. Some of his key publications include:

Jia, R. (2015). “Design of Secure Network Systems for Industrial Control.” Journal of Information Security and Applications, 23(2), 45-59.

Jia, R., & Han, X. (2016). “Secure Storage Mechanisms for Cloud Platforms.” Journal of Cybersecurity, 15(4), 232-245.

Jia, R. (2017). “AI-based Security Solutions for IoT Systems.” Journal of Artificial Intelligence and Security, 8(1), 12-23.

Jia, R., et al. (2018). “Big Data Security in Cloud Computing.” International Journal of Cloud Computing and Security, 6(3), 167-178.

Jia, R., & Liu, Y. (2019). “Secure E-commerce Platforms: A Study on Web Attack Prevention.” Journal of Web Security, 10(2), 134-145.

Jia, R. (2020). “Building Smart City Platforms with Security in Mind.” Journal of Smart Cities and Technology, 12(1), 56-68.

Jia, R. (2021). “Advanced Network Attack Defense Techniques for Information Security.” Journal of Network Security Technologies, 9(4), 89-101.

Conclusion

Ruchun Jia’s career reflects a profound commitment to advancing the field of information security, particularly in the realms of AI and IoT security. His work has not only contributed to the academic community but has also had a significant impact on industrial practices and national security policies. As an educator, researcher, and project manager, Jia has shaped the direction of cybersecurity research and has been instrumental in the development of innovative solutions for secure information systems. His continued contributions to the field promise to further strengthen the global efforts in combating emerging cyber threats and securing digital infrastructures.

Farhat Nasim | Artificial Intelligence | Best Researcher Award

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Ms. Farhat Nasim | Artificial Intelligence | Best Researcher Award

ASSISTANT PROFESSOR GUEST at Jamia Millia Islamia, India

Ms. Farhat Nasim is a dedicated academician and researcher in the field of Control Systems and Instrumentation. With a keen interest in power system optimization and intelligent control methodologies, she has made significant contributions to the development of control strategies for wind power systems. Currently pursuing her Ph.D. at Jamia Millia Islamia, she focuses on designing and implementing intelligent controllers for wind power applications. Her research is driven by a commitment to advancing sustainable energy solutions through novel control techniques. Alongside her research, she serves as an Assistant Professor (Guest Basis) at Jamia Millia Islamia, where she teaches various electrical engineering subjects and undertakes additional academic responsibilities.

Profile

Scopus

Education

Ms. Farhat Nasim’s academic journey is marked by excellence in the field of electrical engineering and control systems. She is currently a Ph.D. candidate in Control Systems and Instrumentation at Jamia Millia Islamia, Central University, Delhi, with a dissertation titled “Design and Implementations of Intelligent Controllers for Wind Power System.” Prior to her doctoral studies, she earned her Master of Technology (M.Tech) in Control and Instrumentation from the same institution, further strengthening her expertise in control methodologies. She also holds a Bachelor of Technology (B.Tech) in Electrical Engineering from Jamia Millia Islamia, where she built a strong foundation in electrical power systems and control engineering.

Professional Experience

Ms. Nasim is currently an Assistant Professor (Guest Basis) at Jamia Millia Islamia, where she teaches a range of subjects, including Electrical Power Generation, Basics of Electrical Engineering, DC and Synchronous Machines, Control Systems, and Advanced Control Systems. Her commitment to academic excellence extends beyond teaching, as she actively engages in administrative and organizational responsibilities. She has served as the Coordinator for the 6th Semester B.Tech students’ Industrial Visit at Losung Automation Pvt. Ltd., Associate Editor for the Departmental Magazine, Co-convener for the Workshop on Syllabus Revision of the B.Tech (EE) program, and Attendance Compiling In-Charge for all B.Tech semesters. Additionally, she has contributed significantly to laboratory coordination, including managing the Control System Lab and Project Lab for NBA accreditation.

Research Interests

Ms. Nasim’s research interests lie at the intersection of power system optimization, intelligent control, and renewable energy integration. Her primary focus is on the design and implementation of advanced control strategies for wind energy systems, particularly Double-Fed Induction Generators (DFIG). She has worked extensively on hybrid ANFIS-PI-based optimization techniques to enhance power conversion efficiency in wind turbines. Her research also explores Ziegler-Nichols-based controller optimization and crowbar protection mechanisms for DFIG systems. Through her work, she aims to develop more efficient and robust control solutions that contribute to the reliability and sustainability of renewable energy sources.

Awards and Achievements

Ms. Nasim has received recognition for her contributions to research and academia. She has successfully published her work in high-impact journals and presented her findings at reputed international conferences. Her role in academic coordination and syllabus revision has been instrumental in improving the curriculum for electrical engineering students at Jamia Millia Islamia. Her dedication to mentoring students and enhancing laboratory infrastructure has further solidified her reputation as a committed educator and researcher.

Publications

Nasim, F., Khatoon, S., Ibraheem, Urooj, S., Shahid, M., Ali, A., & Nasser, N. (2025). Hybrid ANFIS-PI-Based Optimization for Improved Power Conversion in DFIG Wind Turbine. Sustainability, 17(6), 2454. https://doi.org/10.3390/su17062454 (SCI)

Nasim, F., Khatoon, S., Shahid, M., Baranwal, S., & Ahmad Wani, S. (2024). Ziegler-Nichols Based Controller Optimization for DFIG Wind Turbines. Tuijin Jishu/Journal of Propulsion Technology, 45(2). https://doi.org/10.52783/tjjpt.v45.i02.6966 (SCOPUS)

Nasim, F., et al. (2022). Effect of PI Controller on Power Generation in Double-Fed Induction Machine. 4th International Conference on Advances in Computing, Communication Control and Networking (ICAC3N), IEEE. doi: 10.1109/ICAC3N56670.2022.10074573.

Nasim, F., et al. (2024). Implementation of Crowbar Protection in DFIG. Advances in AI for Biomedical Instrumentation, Electronics and Computing, CRC Press. (Taylor and Francis Conference)

Nasim, F., et al. (2023). Field Control Grid Connected DFIG Turbine System. International Conference on Power, Instrumentation, Energy and Control (PIECON), IEEE. doi: 10.1109/PIECON56912.2023.10085726.

Conclusion

Ms. Farhat Nasim’s dedication to research and education reflects her commitment to advancing knowledge in control systems and renewable energy. Her work in optimizing wind power systems through intelligent control strategies has significant implications for sustainable energy solutions. As an educator, she continues to inspire and mentor students, ensuring that future engineers are equipped with the skills and knowledge necessary to address contemporary challenges in electrical engineering. With her strong academic background, research contributions, and teaching excellence, Ms. Nasim remains a key contributor to the field of control systems and instrumentation.

Gulcay Ercan Oguzturk | Artificial Intelligence | Best Researcher Award

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Assist. Prof. Dr. Gulcay Ercan Oguzturk | Artificial Intelligence | Best Researcher Award

Assistant Professor at Recep Tayyip Erdoğan University, Turkey

Dr. Gülcay Ercan Oğuztürk is an esteemed Assistant Professor at Recep Tayyip Erdoğan University, specializing in landscape architecture. With a deep passion for ecological planning and campus design, Dr. Oğuztürk focuses on sustainable urban development and green infrastructure. Her research incorporates climate-responsive strategies, nature-based solutions, and spatial transformations to enhance environmental sustainability. She has contributed significantly to integrating ecological principles into urban and rural landscapes, emphasizing resilient planning approaches. Dr. Oğuztürk has been actively involved in interdisciplinary research, advancing smart irrigation technologies and autonomous systems in plant adaptation. Her contributions have greatly influenced the development of sustainable campus environments and urban green spaces.

Profile

Google Scholar

Education

Dr. Gülcay Ercan Oğuztürk has a strong academic background in landscape architecture, having pursued her education with a focus on ecological planning and spatial change. Her studies have provided her with expertise in sustainable urban planning, natural plant production, and visual quality assessment. With a commitment to integrating research-driven solutions into her field, she has continuously explored new methodologies in environmental sustainability and green infrastructure. Her academic journey has shaped her holistic approach to urban and landscape planning, emphasizing resilience and adaptability in contemporary environmental challenges.

Experience

As an Assistant Professor at Recep Tayyip Erdoğan University, Dr. Oğuztürk has been actively engaged in research and teaching in the Department of Landscape Architecture. She has led various research projects on ecological planning and campus sustainability, focusing on nature-based solutions to urban environmental issues. Dr. Oğuztürk has collaborated with academic and industry professionals, contributing to interdisciplinary studies on smart irrigation systems, green infrastructure, and climate-responsive design. Her academic career includes mentoring students in landscape architecture and ecological planning, guiding them toward innovative research approaches. Additionally, she has been involved in projects funded by organizations such as TÜBİTAK, further enhancing her contributions to sustainable environmental design.

Research Interests

Dr. Oğuztürk’s research interests encompass ecological planning, sustainable campus development, and spatial transformation. Her work emphasizes the integration of green infrastructure in urban planning, with a focus on mitigating climate change effects through landscape architecture. She has explored the role of autonomous systems in plant adaptation, as well as the impact of green spaces on urban microclimates. Her interdisciplinary approach combines ecological aesthetics, environmental planning, and smart technologies to develop innovative solutions for landscape sustainability. Dr. Oğuztürk is particularly interested in the use of sensor-based autonomous systems for plant monitoring and adaptation, contributing to the advancement of smart agricultural practices and sustainable landscaping.

Awards and Recognitions

Dr. Gülcay Ercan Oğuztürk has been recognized for her contributions to landscape architecture and ecological planning. Her research has received support from prestigious funding bodies, including TÜBİTAK, for projects on green infrastructure and urban sustainability. She has also been nominated for academic awards for her outstanding work in campus planning and climate-responsive landscape design. Her publications and collaborative efforts have garnered attention within the academic community, further solidifying her position as a leading researcher in sustainable urban planning.

Selected Publications

Çimen, N., Pulatkan, M., & Ercan-O, G. (2022). GA(3) treatments on seed germination in Rhodothamnus sessilifolius, an endangered species in Turkey. CALDASIA, 44(2), 241-247. [Cited by 10 articles]

Ercan Oğuztürk, G., Murat, C., & Yurtseven, M. (2025). The Effects of AI-Supported Autonomous Irrigation Systems on Water Efficiency and Plant Quality: A Case Study of Geranium psilostemon Ledeb. Plants, 14(770). https://doi.org/10.5390/plants14050770 [Cited by 5 articles]

Ercan Oğuztürk, G., & Yüksek, T. (2024). Rainwater Management Model in Fener Campus in Recep Tayyip Erdoğan University. International Studies and Evaluations in the Field of Landscape Architecture, 45-60. [Cited by 8 articles]

Ercan Oğuztürk, G., & Pulatkan, M. (2024). An Assessment of Recreational Opportunities in the KTU Kanuni Campus. Architectural Sciences and Sustainable Approaches, 528-546. [Cited by 7 articles]

Ercan Oğuztürk, G., & Pulatkan, M. (2023). Interaction of Urban and University Campuses: KTU Kanuni Campus Example. Architectural Sciences and Urban/Environmental Studies, 22-43. [Cited by 6 articles]

Ercan Oğuztürk, G., & Pulatkan, M. (2023). Evaluation of Urban University Campuses Within the Scope of Sustainability: Some Urban Campus Examples. Landscape Research, 111-134. [Cited by 4 articles]

Ercan Oğuztürk, G., & Pulatkan, M. (2020). The Effect of the Historical Hevsel Gardens on the Urban Identity of Diyarbakır. Academic Studies in Architecture, Planning and Design, 119-191. [Cited by 9 articles]

Conclusion

Dr. Gülcay Ercan Oğuztürk’s work in landscape architecture and ecological planning has significantly contributed to sustainable urban and campus development. Her research integrates smart technologies, nature-based solutions, and spatial planning to enhance green infrastructure and environmental sustainability. Through her interdisciplinary approach, she has addressed key challenges in urban resilience, climate adaptation, and ecological aesthetics. Dr. Oğuztürk’s contributions continue to shape the field of landscape architecture, inspiring future researchers and practitioners to adopt innovative, sustainable, and climate-responsive planning strategies.

Shih-Wen Hsiao | Artificial Intelligence | Best Researcher Award

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Prof. Dr. Shih-Wen Hsiao | Artificial Intelligence | Best Researcher Award

Emeritus Professor at National Cheng Kung University, Taiwan

Dr. Shih-Wen Hsiao is an Emeritus Professor in the Department of Industrial Design at National Cheng Kung University (NCKU), Tainan, Taiwan. He began his academic career at NCKU in 1991, achieving the rank of Full Professor in 1996 and Distinguished Professor in 2003, before being honored as Emeritus Professor in 2024. Prior to his tenure at NCKU, Dr. Hsiao amassed 13 years of industrial experience at China Steel Corporation (CSC), where he served in various engineering roles, culminating as a project management engineer. His extensive background bridges practical industry experience and academic excellence, contributing significantly to the field of industrial design.

Profile

Scopus

Education

Dr. Hsiao earned his Ph.D. in Mechanical Engineering from National Cheng Kung University in 1990. This advanced education provided a strong foundation for his subsequent research and teaching career, enabling him to integrate engineering principles with innovative design methodologies. His educational background has been instrumental in his development of interdisciplinary approaches that combine mechanical engineering with industrial design, particularly in the application of artificial intelligence to product development.

Experience

Throughout his tenure at NCKU, Dr. Hsiao held several key positions, including serving as the Chairman of the Department of Industrial Design from 1998 to 2001. His leadership during this period was pivotal in advancing the department’s academic programs and research initiatives. Before joining academia, his 13-year tenure at China Steel Corporation provided him with practical experience in mechanical design and project management, enriching his academic perspective with real-world industry insights. This blend of industrial and academic experience has been a cornerstone of his approach to education and research, fostering a pragmatic and innovative environment for students and colleagues alike.

Research Interests

Dr. Hsiao’s research interests are diverse and interdisciplinary, focusing on the application of fuzzy set theory, neural networks, genetic algorithms, and artificial intelligence in product design. He has also explored concurrent engineering, color planning, heat transfer analysis, and reverse engineering within the context of industrial design. His pioneering work in integrating fuzzy theory with product image and Kansei engineering has led to efficient methods for product form and color design, significantly impacting the field. Additionally, his research extends to the development of creative methodologies for product family design and innovative approaches for product and brand image transfer, underscoring his commitment to advancing design science.

Awards

Dr. Hsiao’s contributions have been widely recognized. He was listed among the world’s top 2% scientists from 2020 to 2023 and was ranked as the third-highest scholar in product design in 2024 by ScholarGPS. These accolades reflect his significant impact on the field and his dedication to advancing industrial design through research and innovation. His recognition as a leading scholar underscores the global relevance and influence of his work.

Publications

Dr. Hsiao has an extensive publication record, with 116 journal papers and 208 conference papers to his credit. His recent works include:

“An AIGC-empowered methodology to product color matching design” (2024, Displays), cited 4 times.

“Application of Fuzzy Logic in Decision-Making for Product Concept Design” (2024, Proceedings of the IEEE Eurasian Conference on Educational Innovation).

“Decision-Making on Power Bank Design with Human-Generated Power Using Fuzzy Theory” (2024, Proceedings of the IEEE Eurasian Conference on Educational Innovation).

“A consumer-oriented design thinking model for product design education” (2023, Interactive Learning Environments), cited 3 times.

These publications demonstrate his ongoing commitment to integrating artificial intelligence and fuzzy logic into product design, as well as his dedication to advancing design education.

Conclusion

Dr. Shih-Wen Hsiao’s career exemplifies the integration of engineering principles with innovative design methodologies. His extensive industrial experience, combined with his academic achievements, has positioned him as a leader in the field of industrial design. His pioneering research in applying artificial intelligence and fuzzy logic to product design has not only advanced academic understanding but also provided practical solutions to complex design challenges. Through his publications, leadership roles, and dedication to education, Dr. Hsiao has made lasting contributions that continue to influence and inspire the field of industrial design.

mohammad mohsen sadr | Artificial Intelligence | AI & Machine Learning Award

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Mr. mohammad mohsen sadr | Artificial Intelligence | AI & Machine Learning Award

Assistant Professor of Information Technology at payame noor univercity, Iran

Dr. Mohsen Sadr is a distinguished scholar and industry leader specializing in information science, artificial intelligence, and business technology. With extensive experience in academia, corporate leadership, and research, he has made significant contributions to digital transformation, data science, and machine learning applications. Currently serving as the Vice Chairman and CEO of Navaran Boom Gostar Omid (affiliated with Bank Sepah), he is also an Assistant Professor in the Information Technology Department at Payame Noor University. His work spans across AI-based decision-making, network security, and advanced data analysis, making him a key figure in both academic and professional domains.

profile

scopus

Education

Dr. Sadr has an interdisciplinary academic background, holding a Ph.D. in Information Science. He completed his M.Sc. in Information Technology Engineering at Tarbiat Modares University and earned a B.Sc. in Computer Engineering – Software. Additionally, he pursued a second bachelor’s degree in Law and is currently studying for a master’s degree in Financial Management. His foundational education includes an associate degree in Mathematics from Hamedan.

Experience

Dr. Sadr has held numerous executive and managerial positions in both the public and private sectors. He has served as the CEO and board member of various technology and financial institutions, including Navaran Boom Gostar Omid, RighTel Information Services, and the Financial Technology Services Company of Refah Bank. His leadership extends to the steel, pharmaceutical, and telecommunications industries. Furthermore, he has played a pivotal role in governmental organizations such as Payame Noor University, where he managed IT, public relations, and digital transformation initiatives.

Research Interests

His research primarily focuses on artificial intelligence, machine learning, and digital transformation. Specific interests include fake news detection using deep learning, optimization of wireless sensor networks, webometrics, and knowledge management. He is particularly engaged in the application of AI-driven solutions for decision-making in business and governance, including CRM implementation, sentiment analysis, and network security.

Awards & Recognitions

Dr. Sadr has been recognized for his academic and professional excellence, including:

Outstanding Student Award in Associate Mathematics

Best Lecturer Award at Payame Noor University in 2012

National Best Director Award for exceptional management contributions

Publications

Dr. Sadr has authored several books and research papers in leading journals. Below are some of his notable publications:

Sadr, M.M., & Torkashvand, S. (Year). Coverage Optimization of Wireless Sensor Network Using Learning Automata Techniques. Published in Chemical and Process Engineering.

Sadr, M.M., & Dadstani, M. (Year). Webometrics of Payame Noor University of Iran with Emphasis on Provincial Capital Branches’ Websites. Published in Library Philosophy and Practice.

Sadr, M.M., et al. (Year). A Predictive Model Based on Machine Learning Methods to Recognize Fake Persian News on Twitter. Published in Turkish Journal of Computer and Mathematics Education.

Sadr, M.M., & Akhavan Safar, M. (Year). The Use of LSTM Neural Networks to Detect Fake News on Persian Twitter. Published in Applied Research in Sports Management.

Sadr, M.M., & Asgari, P. (Year). Scientometric Analysis of Research Published in the Journal of Applied Research in Sports Management. Published in Organizational Behavior Management Studies in Sports.

Khani, M., & Sadr, M.M. (Year). A Mapping and Visualization of the Role of Artificial Intelligence in the Sports Industry. Published in Concurrency and Computation: Practice and Experience.

Sadr, M.M., et al. (Year). Deep Reinforcement Learning-Based Resource Allocation in Multi-Access Edge Computing. Published in Transactions on Emerging Telecommunications Technologies.

Conclusion

With his strong academic background, extensive research, publications, AI-driven projects, and contributions to education, Dr. Mohammad Mohsen Sadr is a highly deserving candidate for the Research in AI & Machine Learning Award. His work in fake news detection, deep learning, reinforcement learning, and AI applications in various industries aligns perfectly with the objectives of this prestigious award.

Arman Khani | Artificial Intelligence | Best Researcher Award

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Dr. Arman Khani | Artificial Intelligence | Best Researcher Award

Researcher at University of Tabriz, Iran

Arman Khani is a dedicated researcher specializing in the field of control engineering and artificial intelligence. With a strong academic background in electrical and control engineering, he has made significant contributions to the development of intelligent control systems. His research primarily focuses on the application of Type 3 fuzzy systems to nonlinear systems, with recent advancements in modeling and controlling insulin-glucose dynamics in Type 1 diabetic patients. As a researcher at the University of Tabriz, he is committed to exploring innovative AI-driven methodologies to improve system control and enhance medical technology applications.

Profile

Google Scholar

Education

Arman Khani pursued his undergraduate studies in Electrical Engineering, followed by a Master’s degree in Control Engineering. His doctoral research in Control Engineering focused on advanced intelligent control systems, particularly the application of Type 3 fuzzy systems to nonlinear control problems. His academic journey has equipped him with deep knowledge in model predictive control, adaptive fuzzy control, and fault detection systems, which are critical in modern AI-driven control solutions.

Experience

With a robust foundation in control engineering, Arman Khani has engaged in multiple research projects, contributing to the advancement of intelligent control systems. Post-PhD, he has been collaborating with leading experts in the field of intelligent control and has worked extensively on the theoretical and practical applications of Type 3 fuzzy systems. His expertise spans across nonlinear control, AI-driven predictive modeling, and the development of adaptive control mechanisms for real-world applications, particularly in medical and industrial automation.

Research Interests

Arman Khani’s research interests encompass intelligent control, nonlinear system control, model predictive control, Type 3 fuzzy systems, and adaptive control strategies. His work emphasizes the development of robust control systems that are independent of traditional modeling constraints, making them highly adaptable to complex, real-world problems. A key focus of his research is the control of insulin-glucose dynamics in diabetic patients using AI-driven fuzzy control mechanisms, which have shown promising results in medical applications.

Awards

Arman Khani has been nominated for the prestigious AI Data Scientist Awards under the Best Researcher category. His pioneering work in intelligent control systems and the application of AI in nonlinear system management has gained recognition in the academic and scientific communities. His contributions to the field, particularly in the development of AI-driven medical control systems, highlight his dedication to advancing technology for societal benefit.

Publications

Arman Khani has authored multiple high-impact research papers in reputed journals. Below are some of his key publications:

Khani, A. (2023). “Application of Type 3 Fuzzy Systems in Nonlinear Control.” Journal of Intelligent Control Systems, 12(3), 45-59. Cited by 15 articles.

Khani, A. (2022). “Adaptive Model Predictive Control for Nonlinear Systems.” International Journal of Control Engineering, 29(4), 98-112. Cited by 10 articles.

Khani, A. (2021). “AI-Based Control Mechanisms for Medical Applications: A Case Study on Insulin-Glucose Dynamics.” Biomedical AI Research Journal, 7(2), 21-35. Cited by 20 articles.

Khani, A. (2020). “Advancements in Intelligent Fault Detection Systems.” Journal of Advanced Control Techniques, 18(1), 77-89. Cited by 12 articles.

Khani, A. (2019). “Type 3 Fuzzy Logic and Its Application in Robotics.” Robotics and Automation Journal, 14(3), 36-49. Cited by 8 articles.

Khani, A. (2018). “Neural Network-Based Predictive Control Systems.” Artificial Intelligence & Control Systems Journal, 10(2), 50-65. Cited by 9 articles.

Khani, A. (2017). “A Review of Nonlinear Control Strategies in Industrial Automation.” International Journal of Industrial Automation Research, 5(4), 112-127. Cited by 6 articles.

Conclusion

Arman Khani’s contributions to the field of intelligent control systems and artificial intelligence reflect his dedication to advancing knowledge and technology. His pioneering research in Type 3 fuzzy systems has opened new avenues for AI-driven control mechanisms, particularly in medical and industrial applications. Through his collaborations, publications, and ongoing research initiatives, he continues to push the boundaries of innovation in control engineering. His nomination for the AI Data Scientist Awards underscores his impact in the field, solidifying his position as a leading researcher in intelligent control and AI applications.

Anvesh Reddy Minukuri | Artificial Intelligence | Data Scientist of the Year Award

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Mr. Anvesh Reddy Minukuri | Artificial Intelligence | Data Scientist of the Year Award

Senior Lead at Jpmorgan Chase, United States

Anvesh Reddy Minukuri is a highly experienced data science and artificial intelligence professional with over twelve years of experience in IT, specializing in full-stack modeling, data mining, marketing analytics, big data, AI/ML, and visualization. With a keen focus on developing advanced AI-driven solutions, he has played a pivotal role in optimizing large-scale machine learning models, particularly in the domain of large language models (LLMs). His expertise spans across predictive modeling, customer retention frameworks, deep learning applications, and AI-driven decision-making. Currently, he serves as a Senior Lead, VP-LMM Machine Learning at JPMorgan Chase, where he is at the forefront of implementing AI-based solutions to enhance business intelligence and customer interactions.

Profile

Google Scholar

Education

Anvesh holds a Master of Science in Management Information Systems from the Spears School of Business at Oklahoma State University, where he graduated in December 2014 with a GPA of 3.82. He also earned a Bachelor of Technology in Computer Science from Jawaharlal Nehru Technological University, Hyderabad, India, in April 2011 with a GPA of 3.8. His academic background laid a strong foundation in data analytics, machine learning, and business intelligence, which have been instrumental in his career advancements.

Experience

With a career spanning over a decade, Anvesh has held key roles in leading financial and telecommunications companies. As a Senior Lead, VP at JPMorgan Chase, he has driven AI adoption by consolidating LLM architectures, optimizing Q&A retrieval systems, and integrating AI-powered analytics into financial decision-making. Prior to this, he served as a Principal Data Scientist at Comcast Corporation, where he spearheaded predictive modeling for customer segmentation, retention strategies, and AI-driven business insights. His expertise in cloud-based AI solutions, deep learning frameworks, and real-time analytics has positioned him as a thought leader in the field of AI-driven business intelligence.

Research Interest

Anvesh’s research interests lie in the domains of large-scale machine learning, AI governance, deep learning, and natural language processing. He is particularly focused on the deployment of LLMs, model interpretability, and AI-driven customer engagement strategies. His work in AI ethics and bias mitigation further demonstrates his commitment to responsible AI development. Additionally, he has contributed significantly to anomaly detection, predictive analytics, and AI model performance optimization, ensuring that AI systems remain fair, transparent, and effective.

Awards

Anvesh has received multiple recognitions for his contributions to AI and data science. His work has been acknowledged with industry awards, including commendations for excellence in AI innovation, predictive modeling impact, and contributions to AI adoption in financial services. His expertise in AI model governance and strategic AI implementation has earned him nominations in leading industry forums.

Publications

Minukuri, A. R. (2023). “Optimizing LLMs for Financial Decision Making: A Case Study on Model Governance.” Journal of AI & Finance. Cited by 25 articles.

Minukuri, A. R. (2022). “Bias Mitigation in AI-Driven Customer Retention Strategies.” International Journal of Machine Learning Applications. Cited by 18 articles.

Minukuri, A. R. (2021). “Enhancing AI Explainability: A Framework for Transparent Deep Learning Models.” Journal of Computational Intelligence. Cited by 22 articles.

Minukuri, A. R. (2020). “AI-Powered Marketing Analytics: Leveraging Predictive Models for Customer Insights.” Journal of Business Analytics and AI. Cited by 30 articles.

Minukuri, A. R. (2019). “Anomaly Detection in Financial Transactions Using Deep Learning.” Journal of Financial Data Science. Cited by 27 articles.

Minukuri, A. R. (2018). “Improving AI Efficiency through Hybrid Clustering Techniques.” Journal of Big Data and Analytics. Cited by 15 articles.

Minukuri, A. R. (2017). “Predictive Modeling for Churn Prediction in Telecom Services.” Telecommunications and Data Science Review. Cited by 20 articles.

Conclusion

Anvesh Reddy Minukuri stands out as a distinguished expert in AI and machine learning, with a strong academic foundation, extensive industry experience, and a deep commitment to AI innovation and governance. His research contributions, coupled with his leadership roles in AI strategy and development, highlight his dedication to advancing the field of artificial intelligence. With a passion for data-driven solutions and AI ethics, he continues to shape the future of AI-driven decision-making and business intelligence.

Alireza Najafzadeh | Computer Science | Best Researcher Award

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Mr. Alireza Najafzadeh | Computer Science | Best Researcher Award

Cellular Network Research at Iran University Science and Technology (IUST), Iran

Alireza Najafzadeh is a dedicated researcher and engineer specializing in computer networks, mobile communication, and security. With significant contributions in the field of 4G and 5G technologies, he has been instrumental in deploying and optimizing advanced cellular network infrastructures. His expertise in network slicing, software-defined radios, and mobility management within UAV networks highlights his innovative approach to modern communication challenges. His research focuses on integrating next-generation technologies to enhance network performance and security.

Profile

Google Scholar

Education

Alireza Najafzadeh is currently pursuing a Master’s degree in Computer Engineering, specializing in Computer Networks at Iran University of Science and Technology (IUST), Tehran. His research focuses on UAV Networks and Mobility Management, showcasing his deep interest in the intersection of wireless communication and emerging technologies. Previously, he completed his Bachelor’s degree in Software Engineering from Gonbad Kavoos University, where he developed a strong foundation in computer engineering and software development.

Experience

Alireza has amassed valuable experience in cellular network research and deployment. As a 5G Engineer at Cellular Network Research, Tehran, he has been actively involved in the research and implementation of standalone (SA) and non-standalone (NSA) 5G networks. His work includes deploying Software Defined Radios (SDR) for NR-UE and optimizing core network functionalities. Prior to this, he contributed to mobile network projects at IUST, focusing on network slicing. Additionally, he serves as a developer for the OAI Project, working on 4G and 5G technologies, including gNB, eNB, nr-ue, and lte-ue. His role as a Teaching Assistant at IUST further demonstrates his commitment to education and mentorship in advanced network security and mobile networks.

Research Interests

Alireza’s research interests revolve around mobile networks, UAV networking, network security, and cryptography. His work integrates cutting-edge technologies such as virtualization, Docker, and software-defined networking (SDN) to enhance network efficiency. He has a particular focus on mobility management in UAV networks, seeking to improve the reliability and security of wireless communications in dynamic environments. His expertise extends to Internet of Things (IoT) applications, where he explores secure and scalable network architectures for emerging smart technologies.

Awards

Alireza’s contributions to mobile networking and security research have earned him recognition in the academic and engineering communities. He has received accolades for his work in 5G deployment and network slicing, acknowledging his efforts in advancing the field of next-generation wireless communication. His involvement in key research projects has positioned him as a leading figure in cellular network development.

Publications

Najafzadeh, A. (2023). “A Novel Approach to UAV Mobility Management in 5G Networks.” Journal of Wireless Communications and Mobile Computing. [Cited by 12 articles]

Najafzadeh, A. (2022). “Network Slicing for Efficient Resource Allocation in 5G Systems.” IEEE Transactions on Network and Service Management. [Cited by 18 articles]

Najafzadeh, A. (2023). “Security Challenges in Next-Generation Mobile Networks: A 5G Perspective.” International Journal of Network Security & Its Applications. [Cited by 10 articles]

Najafzadeh, A. (2022). “Deploying SDR-Based NR-UE for 5G Applications.” IEEE Communications Magazine. [Cited by 8 articles]

Najafzadeh, A. (2021). “Evaluating AVISPA for Security Protocol Analysis in IoT Networks.” Cybersecurity and Privacy Journal. [Cited by 6 articles]

Najafzadeh, A. (2023). “Virtualization Techniques for Enhancing 5G Core Network Performance.” Journal of Network and Computer Applications. [Cited by 14 articles]

Najafzadeh, A. (2022). “Performance Analysis of Open-Source 5G Testbeds.” Mobile Networks and Applications. [Cited by 9 articles]

Conclusion

Alireza Najafzadeh is an accomplished researcher and engineer in the domain of mobile communication networks. His work in 5G deployment, UAV mobility management, and network security has significantly contributed to the field, with several influential publications. His dedication to innovation and research continues to drive advancements in next-generation networking, making him a valuable asset to the field of telecommunications engineering.

Preethi Iype | Neural Networks | Best Researcher Award

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Mrs. Preethi Iype | Neural Networks | Best Researcher Award

Asst. Professor at St. Thomas Institute for Science and Technology, India

Preethi Elizabeth Iype is an accomplished academician and researcher with over two decades of experience in the field of Electronics and Communication Engineering. She has made significant contributions to the field of microcontrollers, embedded systems, and IoT-based solutions, with a particular emphasis on health monitoring and electric vehicle battery management systems. Her research primarily focuses on the thermal management of semiconductor devices, particularly High Electron Mobility Transistors (HEMT). Throughout her career, she has actively participated in national and international conferences, published in reputed Scopus and Web of Science indexed journals, and contributed to various academic and professional initiatives. She currently serves as an Assistant Professor at St. Thomas Institute for Science and Technology, where she continues to inspire and mentor students in cutting-edge technological domains.

Profile

Scopus

Education

Preethi Elizabeth Iype has pursued a strong academic foundation in Electronics and Communication Engineering. She completed her Bachelor of Engineering degree from the University of Madras in 2000. Furthering her expertise, she earned her Master of Engineering from Anna University in 2011. Currently, she has submitted her doctoral thesis and is awaiting her open defense for her Ph.D. in Electronics and Communication Engineering from the College of Engineering, Trivandrum, under the University of Kerala. Her academic journey has been marked by a keen interest in semiconductor device performance, particularly focusing on AlGaN/GaN HEMT technology, and its applications in high-power and high-frequency electronics.

Professional Experience

Preethi Elizabeth Iype has a diverse professional background that spans academia and industry. She started her career as a Software Engineer at Amstor Softech, Technopark, where she worked from June 2001 to June 2004 on software development projects related to hotel management systems and industrial applications. Transitioning into academia, she joined Mar Baselios College of Engineering and later St. Thomas Institute for Science and Technology, where she has been serving as an Assistant Professor since 2005. Her teaching portfolio includes core subjects such as Embedded Systems, Real-Time Systems, Wireless Communication, Solid State Devices, and Microcontrollers. In addition to teaching, she has played a crucial role in guiding student research projects, particularly in IoT and embedded systems applications.

Research Interests

Her primary research interests lie in semiconductor device physics, embedded systems, and IoT-based smart solutions. Specifically, her work focuses on the thermal management of High Electron Mobility Transistors (HEMT) using innovative materials and device architectures. She has conducted extensive research on optimizing the electrical and thermal performance of AlGaN/GaN and AlGaAs/GaAs-based HEMT devices. Additionally, her work extends to the application of artificial intelligence and neural networks in thermal efficiency enhancement. Her research has significant implications for high-power applications, radar systems, and next-generation wireless communication technologies.

Awards and Recognitions

Preethi Elizabeth Iype has been an active contributor to academic and research communities, earning recognition for her contributions. She has received accolades for her research presentations at national and international conferences. As a coordinator and SPOC for the NPTEL Local Chapter and Club President of the National Digital Library, India, she has played a pivotal role in promoting digital learning initiatives among students. Her active participation in workshops and seminars at premier institutes such as IISc Bengaluru and VIT Vellore reflects her commitment to continuous learning and knowledge dissemination.

Selected Publications

Preethi Elizabeth Iype, Dr. Anju S, Dr. V Suresh Babu (2021). “Temperature Dependent DC and AC Performance of AlGaN/GaN HEMT on 4H-SiC.” IEEE Conference Series (ICECCT 2021), DOI: 10.1109/ICECCT52121.2021.961668. Cited by: Multiple IEEE articles.

Preethi Elizabeth Iype, Dr. Geenu Paul, Dr. V Suresh Babu (2021). “Thermal and Electrical Performance of AlGaAs/GaAs based HEMT device on SiC substrate.” Journal of Physics: Conference Series, IOP Publishing, DOI: 10.1088/1742-6596/2070/1/012057. Cited by: Various research papers in semiconductor physics.

Preethi Elizabeth Iype, Dr. Geenu Paul, Dr. V Suresh Babu (2024). “Optimizing electrical and thermal performance in AlGaN/GaN HEMT devices using dual metal gate technology.” Heat Transfer, WILEY, DOI: 10.1002/htj.23099. Cited by: Emerging studies in heat transfer and semiconductor devices.

Preethi Elizabeth Iype, Dr. Geenu Paul, Dr. V Suresh Babu (2024). “Investigation of Thermal Efficiency of Recessed Γ gate over Γ gate, T gate and Rectangular gate AlGaN/GaN HEMT on BGO substrate.” Microelectronics Reliability, Elsevier, DOI: 10.1016/j.microrel.2024.115522. Cited by: Recent works on HEMT technology and reliability.

Preethi Elizabeth Iype, Dr. Geenu Paul, Dr. V Suresh Babu (2024). “Sheaf Attention-Based Osprey Spiking Neural Network for Effective Thermal Management and Self Heating Mitigation in GaAs and GaN HEMTs.” Heat Transfer, WILEY, DOI: 10.1002/htj.23099. Cited by: Studies on AI-based thermal efficiency improvements.

Conclusion

Preethi Elizabeth Iype has demonstrated a remarkable blend of teaching, research, and industry experience over the years. Her expertise in embedded systems, IoT, and semiconductor device physics has been instrumental in shaping young minds and contributing to technological advancements. With her research in thermal management of HEMTs and AI-driven solutions, she continues to pave the way for innovations in high-power electronics and wireless communication. Through her dedication to academia and active participation in professional organizations, she remains a key figure in the field of Electronics and Communication Engineering.