Petcharaporn Yodjai | Computer Science | Best Researcher Award

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Ms. Petcharaporn Yodjai | Computer Science | Best Researcher Award

Ph.D. Student at King Mongkut’s University of Technology Thonburi, Thailand

Petcharaporn Yodjai is a dedicated researcher in the field of applied mathematics, with a particular focus on image processing and mathematical modeling. Currently a Ph.D. candidate at King Mongkut’s University of Technology Thonburi (KMUTT), Bangkok, Thailand, she has made significant contributions to the development of advanced techniques in image inpainting and completion. Her work integrates theoretical mathematical principles with practical applications, offering innovative solutions in digital image processing. Yodjai’s academic journey is marked by excellence, as she earned her Bachelor of Science in Mathematics with First Class Honours from Maejo University. She has been the recipient of prestigious scholarships and fellowships, allowing her to conduct research at renowned institutions worldwide.

Profile

Scopus

Education

Yodjai embarked on her academic journey at Maejo University, where she pursued a Bachelor of Science in Mathematics from July 2015 to April 2019. Her outstanding academic performance earned her First Class Honours. Continuing her passion for applied mathematics, she enrolled in the Ph.D. program at King Mongkut’s University of Technology Thonburi in July 2019. Throughout her doctoral studies, she has focused on developing mathematical methods for image processing, with an emphasis on structure propagation and sparse representation techniques. Her education has been supplemented by international research experiences through various exchange programs and fellowships.

Experience

Yodjai has accumulated significant research experience through international collaborations and exchange programs. In 2023, she conducted short-term research at the North University Center at Baia Mare, Technical University of Cluj-Napoca, Romania, followed by a long-term research stint at the University of Jaén, Spain, from September 2022 to February 2023. Earlier, she engaged in a research project at Gyeongsang National University, South Korea, in 2022. Additionally, she has served as a teaching assistant at KMUTT, assisting in undergraduate mathematics courses over multiple semesters, which has enhanced her pedagogical skills. Her participation in international conferences has allowed her to present her research findings and collaborate with experts in her field.

Research Interests

Yodjai’s research interests lie in applied mathematics, specifically in image processing, mathematical modeling, and computational methods. She has focused on developing efficient algorithms for image inpainting, structure propagation, and sparse representation. Her work incorporates techniques such as Bezier curves and deep learning segmentation to enhance image restoration processes. She is particularly interested in bridging the gap between mathematical theory and real-world applications, ensuring that her research contributes to advancements in digital imaging and computational science.

Awards and Scholarships

Yodjai has been recognized for her academic excellence and research contributions through several prestigious scholarships and awards. She is a recipient of the Royal Golden Jubilee Ph.D. Scholarship from the National Research Council of Thailand, which has supported her doctoral studies since 2019. She also received funding from the Japan Science and Technology Agency under the SAKURA Exchange Program in Science in 2023. Furthermore, she participated in the Erasmus+ program, funded by Romania, which facilitated her research collaboration with European institutions.

Publications

Yodjai, P., Kumam, P., & Martínez-Moreno, J. (2025). Image Completion Using Automatic Structure Propagation With Bezier Curves. Mathematical Methods in the Applied Sciences.

Jirakipuwapat, W., Sombut, K., Yodjai, P., & Seangwattana, T. (2025). Enhancing Image Inpainting With Deep Learning Segmentation and Exemplar-Based Inpainting. Mathematical Methods in the Applied Sciences.

Yodjai, P., Kumam, P., Martínez-Moreno, J., & Jirakitpuwapat, W. (2024). Image inpainting via modified exemplar-based inpainting with two-stage structure tensor and image sparse representation. Mathematical Methods in the Applied Sciences, 47(11), 9027-9045.

Awwal, A. M., Wang, L., Kumam, P., Sulaiman, M. I., Salisu, S., Salihu, N., & Yodjai, P. (2023). Generalized RMIL conjugate gradient method under the strong Wolfe line search with application in image processing. Mathematical Methods in the Applied Sciences, 46(16), 17544-17556.

Yodjai, P., Kumam, P., Kitkuan, D., Jirakitpuwapat, W., & Plubtieng, S. (2019). The Halpern approximation of three operators splitting method for convex minimization problems with an application to image inpainting. Bangmod International Journal of Mathematical and Computational Science, 5, 58-75.

Conclusion

Petcharaporn Yodjai’s research contributions in applied mathematics, particularly in image inpainting and completion, demonstrate her dedication to advancing computational methodologies. Through her international collaborations, numerous publications, and teaching experience, she has established herself as a promising scholar in the field. Her work continues to impact digital image processing, providing solutions that enhance the accuracy and efficiency of image restoration techniques. With her expertise and commitment to research, she is poised to make significant advancements in mathematical modeling and computational science in the coming years.

Ali Nawaz Sanjrani | Big Data Analytics | Global Data Science Award

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Dr. Ali Nawaz Sanjrani | Big Data Analytics | Global Data Science Award

Assistant Professor at University of Electronic Science and Technology of China, China

Dr. Ali Nawaz Sanjrani is a distinguished academician and scholar with over 18 years of interdisciplinary expertise spanning research, teaching, and fieldwork. His contributions to mechanical engineering, particularly in reliability monitoring, quality control, and advanced diagnostics of complex machines, have earned him a strong reputation in the field. With a research focus on predictive modeling and artificial intelligence applications in mechanical systems, Dr. Sanjrani has consistently demonstrated a commitment to innovation and excellence in engineering and applied sciences.

Profile

Scopus

Education

Dr. Sanjrani earned his Ph.D. in Mechanical Engineering from the University of Electronics Science and Technology in Chengdu, China, specializing in reliability monitoring and diagnostics of complex machines. His doctoral research focused on advanced machine learning models for fault diagnosis and predictive maintenance. He also holds a Master’s degree in Industrial Manufacturing from NED University, Karachi, with a specialization in Lean Manufacturing. His undergraduate studies in Mechanical Engineering at QUEST, Nawabshah, laid a strong foundation in mechanical manufacturing and materials science.

Experience

Dr. Sanjrani has held key academic and industrial roles, including serving as an Assistant Professor at Mehran University of Engineering and Technology (MUET), where he mentored students in reliability engineering and manufacturing processes. He also served as a Lecturer at MUET and a Visiting Faculty Member at Indus University, Karachi. His industry experience includes working as a Quality Assurance and Quality Engineer at DESCON Engineering Works Limited, where he played a pivotal role in implementing international quality management systems and overseeing major engineering projects.

Research Interests

Dr. Sanjrani’s research interests lie in reliability engineering, predictive maintenance, and advanced diagnostics of mechanical systems. He integrates artificial intelligence and machine learning techniques to enhance fault detection and life cycle predictions of engineering components. His work also includes automation, control systems, and the application of deep learning for real-time condition monitoring. Additionally, he has explored lean manufacturing principles for improving industrial efficiency and safety.

Awards

Dr. Sanjrani has received several accolades for his academic and professional achievements, including the 3rd Prize for Academic Excellence and Performance Excellence at the University of Electronics Science and Technology, Chengdu, China, in 2024. He was also awarded a fully funded Chinese Government Scholarship (CSC) for his Ph.D. studies. His contributions to quality management earned him appreciation certificates from the Managing Director of Karachi Shipyard & Engineering Works (KSEW) for achieving international certifications and project execution.

Publications

Sanjrani, A. N. (2025). “High-Speed Train Bearing Health Assessment Based on Degradation Stages.” Quality and Reliability Engineering International Journal (Wiley).

Sanjrani, A. N. (2025). “Dynamic Temporal LSTM-Seqtrans for Long Sequence: Credit Card Fraud Detection.” ICCWAMTIP Conference.

Sanjrani, A. N. (2025). “High-Speed Train Wheel Set Bearing Analysis: Maintenance and Life Extension.” Results in Engineering.

Sanjrani, A. N. (2025). “Advanced Dynamic Power Management Using Model Predictive Control in DC Microgrids.” Journal of Energy Storage.

Sanjrani, A. N. (2024). “High-Speed Train Health Assessment Using Dual-Task LSTM with Attention Mechanism.” IEEE SRSE Conference.

Sanjrani, A. N. (2024). “C-band Sheet Beam Staggered Double Grating Extended Interaction Oscillator.” IEEE ICOPS Conference.

Sanjrani, A. N. (2023). “Prediction of Remaining Useful Life of Bearings Using Parallel Neural Networks.” ESREL Conference.

Conclusion

Dr. Ali Nawaz Sanjrani’s contributions to the fields of mechanical engineering, reliability analysis, and machine learning applications are highly regarded in both academia and industry. His innovative research on predictive maintenance and industrial automation has paved the way for advancements in diagnostics and system optimization. With a commitment to excellence in education, research, and project management, Dr. Sanjrani continues to influence the engineering community through his scholarly work and professional contributions.

Bara Mouslim | Statistical Analysis | Best Researcher Award

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Prof. Dr. Bara Mouslim | Statistical Analysis | Best Researcher Award

prof at Guelma university, Algeria

Dr. Bara Mouslim is a distinguished Algerian ecologist and professor specializing in bird ecology, animal population dynamics, and biodiversity management and conservation. With a strong background in academic teaching, research, and project management, he has dedicated his career to understanding and mitigating the effects of environmental changes on avian species and ecosystems. Currently serving as a Full Professor at the University 8 Mai 1945 in Guelma, Algeria, Dr. Mouslim is an expert in ecosystem perturbation, sustainable development, and conservation biology. His work has been instrumental in advancing knowledge on avian biodiversity and the impacts of ecological disturbances on species distribution and abundance.

Profile

Scopus

Dr. Mouslim earned his Ph.D. in Ecology and Biodiversity from the University Badji Mokhtar in Annaba, Algeria, completing his degree in 2014. His doctoral research focused on avian ecology, particularly studying the breeding and behavioral patterns of wetland bird species. In pursuit of further academic excellence, he completed his HDR (post-doctoral qualification) in Biology and Ecology at the University A-Mira in Bejaia, Algeria, in 2018. His extensive academic training has equipped him with a deep understanding of ecological dynamics, biodiversity conservation, and environmental management strategies.

Experience

Dr. Mouslim has an extensive academic and research career. Since November 2022, he has been a Full Professor at the University 8 Mai 1945 in Guelma, where he teaches master’s and Ph.D. courses in ecology and environmental science. As a vice dean of postgraduate studies, he plays a crucial role in shaping academic curricula and research programs. Additionally, he leads research initiatives focused on ecosystem perturbation, biodiversity conservation, and avian population dynamics. His expertise extends to project management, where he oversees initiatives related to environmental sustainability and wildlife conservation. With a wealth of experience in scientific research and higher education, Dr. Mouslim continues to make significant contributions to ecological sciences.

Research Interests

Dr. Mouslim’s research primarily revolves around avian ecology, biodiversity conservation, and the effects of environmental factors on bird populations. His studies investigate species distribution, habitat preferences, and population dynamics in response to climate change and anthropogenic disturbances. His work also includes monitoring the illegal wildlife trade, conservation of threatened bird species, and the ecological impact of habitat fragmentation. His interdisciplinary approach integrates field studies, statistical modeling, and conservation management strategies to better understand and protect avian biodiversity. Furthermore, he actively collaborates with national and international researchers to address global conservation challenges.

Awards and Recognitions

Dr. Mouslim has been recognized for his contributions to ecological research and conservation efforts. His work on biodiversity management has earned him accolades from academic institutions and conservation organizations. His involvement in environmental sustainability projects and research leadership in ecosystem perturbation have further solidified his reputation as a leading expert in avian ecology. Additionally, his participation in international conferences and scientific collaborations has highlighted the global significance of his research contributions.

Publications

Bara, M. (2014). “Aspects of the breeding ecology of the Purple Swamphen Porphyrio porphyrio in the wetland complex of Guerbes-Sanhadja, north-east Algeria.”

Bara, M. (2015). “Diurnal time budget of Gadwall Anas strepera in Guerbes-Sanhadja wetlands (Skikda, northeast Algeria).”

Bara, M. (2019). “Effect of air temperature and water depth on bird abundance: A case study of Rallidae and Anatidae in the northeastern Algerian Garaet Hadj Tahar.”

Bara, M. (2020). “The trade in the endangered African Grey Parrot Psittacus erithacus and the Timneh Parrot Psittacus timneh in Algeria.”

Bara, M. (2021). “Abundance and diurnal time activity budget of the threatened species White-Headed Ducks (Anatidae) in an unprotected area, Boussedra Marsh, Northeast Algeria.”

Bara, M. (2022). “Illegal wildlife trade in Algeria, insight via online selling platforms.”

Bara, M. (2023). “First report on animal-vehicle collisions impact on wild and domestic animals in northern Algeria.”

Conclusion

Dr. Bara Mouslim is an esteemed researcher and academic leader in the field of avian ecology and biodiversity conservation. His dedication to studying the effects of environmental changes on bird populations has provided valuable insights into species conservation and ecosystem management. Through his teaching, research, and project management roles, he continues to inspire the next generation of ecologists and conservationists. His contributions to scientific literature, policy development, and sustainable environmental practices underscore his commitment to preserving biodiversity and promoting ecological sustainability.

Jun-Woo Park | Next Generation Battery | Best Researcher Award

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Dr. Jun-Woo Park | Next Generation Battery | Best Researcher Award

Principal Researcher at Korea Electrotechnology Research Institute, South Korea

Dr. Jun-Woo Park is a distinguished researcher and academician specializing in battery technologies, particularly in the development of next-generation energy storage solutions. With a career spanning over a decade in electro-functional materials engineering, he has made significant contributions to solid-state battery research, lithium-sulfur battery advancements, and ionic liquid electrolytes. His extensive research portfolio includes high-impact publications, numerous patents, and several prestigious awards, highlighting his influence in the field of battery science. Dr. Park’s work focuses on developing innovative and sustainable energy storage technologies that contribute to the advancement of eco-friendly mobility solutions.

Profile

Scopus

Education

Dr. Park pursued his higher education at Yokohama National University, Japan, where he obtained his Ph.D. in Chemical Engineering in 2013 under the mentorship of Prof. Masayoshi Watanabe. His doctoral research centered on ionic liquid electrolytes for lithium-based batteries, leading to fundamental insights into electrochemical reactions and battery performance. Prior to his Ph.D., he earned a Master’s degree from the same institution in 2010, where he conducted research on electrochemical compatibility and energy storage materials. His educational foundation laid a strong platform for his later groundbreaking work in advanced battery technologies.

Experience

Dr. Park’s professional journey commenced at the Korea Electrotechnology Research Institute (KERI) in 2013, where he has been serving as a Principal Researcher in the Battery Research Division. His role at KERI has been instrumental in advancing solid-state battery technologies, contributing to the development of high-performance secondary batteries. Additionally, he has been an Associate Professor at the University of Science and Technology (UST) in Daejeon, Korea, since 2022, and he was promoted to a full Professor in 2025. Dr. Park has also been actively involved in policy and technological evaluations as a committee member for various South Korean governmental agencies, including the Ministry of Trade, Industry, and Energy and the Ministry of SMEs and Startups. Furthermore, his editorial role at the Korea Battery Society (KOBS) underscores his commitment to disseminating cutting-edge research in the field.

Research Interests

Dr. Park’s research interests lie at the intersection of materials science and electrochemical engineering, focusing primarily on next-generation battery technologies. His work involves the synthesis and optimization of solid-state electrolytes, lithium-sulfur batteries, and high-energy-density flexible batteries. He has been a pioneer in developing sulfide-based all-solid-state batteries and has contributed to improving energy efficiency and safety in battery applications. His studies also explore novel methods for electrolyte synthesis, aiming for cost-effective and scalable production of battery components. Through his research, Dr. Park seeks to bridge the gap between fundamental electrochemistry and real-world battery applications, with a particular emphasis on sustainable and high-performance energy storage solutions.

Awards and Honors

Dr. Park’s contributions have been widely recognized through numerous prestigious awards. Notably, he received the KERI Grand Award in 2024 for his outstanding research on all-solid-state batteries, including publications in top-tier journals. He was honored with the Minister of Trade, Industry, and Energy Award in 2023 for his role in planning the lithium-sulfur battery sector for the national high-performance secondary battery project. Additionally, he received the Minister of Science and ICT Award for developing cost-effective mass-production technology for sulfide-based solid electrolytes. His accolades also include commendations for advancing the domestic battery industry, developing flexible high-energy-density batteries, and significantly contributing to secondary battery energy efficiency improvements.

Publications

Dr. Park has authored numerous high-impact publications in the field of battery research. Below are some selected works:

Park, J-W., et al. (2013). “Li-S Batteries with Ionic Liquid Electrolytes.” The Journal of Physical Chemistry C. [Cited by 200+ articles]

Park, J-W., et al. (2011). “Limiting current density in bis(trifluoromethylsulfonyl)amide-based ionic liquid for lithium batteries.” Journal of Power Sources. [Cited by 350+ articles]

Park, J-W., et al. (2018). “Effect of solvated ionic liquids on the ion-conducting property of composite membranes for lithium-ion batteries.” Research on Chemical Intermediates. [Cited by 180+ articles]

Park, J-W., et al. (2020). “Facile fabrication of solution-processed solid electrolytes for high-energy-density all-solid-state batteries by enhanced interfacial contact.” Scientific Reports. [Cited by 220+ articles]

Park, J-W., et al. (2021). “A novel strategy to overcome the hurdle for commercial all-solid-state batteries via low-cost synthesis of sulfide solid electrolytes.” Small Methods. [Cited by 280+ articles]

Park, J-W., et al. (2023). “Engineering green and sustainable solvents for scalable wet synthesis of sulfide electrolytes in high-energy-density all-solid-state batteries.” Green Chemistry. [Cited by 150+ articles]

Park, J-W., et al. (2024). “Size-controlled wet-chemical synthesis of sulfide superionic conductors for high-performance all-solid-state batteries.” Energy Storage Materials. [Cited by 200+ articles]

Conclusion

Dr. Jun-Woo Park’s career is a testament to his dedication to advancing battery technology through innovative research and practical applications. His contributions to lithium-sulfur and solid-state battery advancements have not only earned him widespread recognition but have also significantly influenced the future of energy storage solutions. Through his academic, industrial, and policy-driven engagements, Dr. Park continues to shape the landscape of next-generation batteries, driving progress toward more efficient, safe, and sustainable energy storage technologies.

Yongqian Sun | Anomaly Detection | Best Researcher Award

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Assoc. Prof. Dr. Yongqian Sun | Anomaly Detection | Best Researcher Award

Associate Professor at Nankai University, China

Dr. Yongqian Sun is an accomplished Associate Professor at Nankai University, with a strong background in artificial intelligence, intelligent operations, and network management. With a career dedicated to advancing AI-driven solutions for fault detection and service reliability, Dr. Sun has collaborated extensively with leading technology enterprises, contributing significantly to AI research and its real-world applications. With over 70 high-quality publications and multiple prestigious awards, Dr. Sun remains at the forefront of AI research, driving innovation and fostering industry-academic collaborations.

Profile

Google Scholar

Education

Dr. Sun holds a Ph.D. from Tsinghua University (2012–2018) and a Bachelor of Science degree from Northwestern Polytechnical University (2008–2012). His academic journey reflects a strong foundation in computer science, artificial intelligence, and software engineering, which has enabled him to make significant contributions to the field of AI-driven intelligent operations and maintenance.

Experience

Dr. Sun has been serving as an Associate Professor at Nankai University since July 2018. Over the years, he has led various research initiatives, collaborated with top-tier technology companies such as Huawei, ByteDance, Alibaba, and Tencent, and played a pivotal role in shaping AI-driven network management solutions. His expertise in operational intelligence has significantly impacted the development of automated fault detection and resolution systems in large-scale online services.

Research Interests

Dr. Sun’s research focuses on artificial intelligence, intelligent operation and maintenance, and network intelligent management. His work delves into fault detection using machine learning, causal relationship analysis of faults with operational knowledge graphs, and root cause localization through recommendation algorithms. His research aims to improve service reliability, reduce downtime, and enhance user experience in large-scale IT infrastructures.

Awards

Dr. Sun has been recognized for his contributions with several prestigious awards, including:

  • Best Paper Award, ISSRE 2024
  • Best Industrial Paper Award, ISSRE 2024
  • First Prize for Scientific and Technological Progress, China Electronics Society These accolades underscore his significant contributions to AI research and its applications in service operations and network management.

Publications

Dr. Sun has authored over 70 high-quality papers, with more than 30 as the first or corresponding author. Some of his notable publications include:

Sun, Y., et al. (2023). “AI-Driven Fault Detection in Large-Scale Networks.” IEEE Transactions on Network Science and Engineering. (Cited by 125 articles)

Sun, Y., et al. (2022). “Operational Knowledge Graphs for AI-Based Network Management.” Journal of Artificial Intelligence Research. (Cited by 98 articles)

Sun, Y., et al. (2021). “Machine Learning Approaches to Automated Fault Resolution in Cloud Environments.” ACM Transactions on Intelligent Systems. (Cited by 82 articles)

Sun, Y., et al. (2020). “Deep Learning for Predictive Maintenance in Large-Scale IT Systems.” IEEE Transactions on Services Computing. (Cited by 67 articles)

Sun, Y., et al. (2019). “Enhancing User Experience through AI-Driven Network Optimization.” ACM SIGCOMM Computer Communication Review. (Cited by 59 articles)

Sun, Y., et al. (2018). “Big Data Analytics for Fault Diagnosis in Enterprise Networks.” Journal of Big Data Research. (Cited by 50 articles)

Sun, Y., et al. (2017). “A Hybrid AI Framework for Network Fault Management.” IEEE Transactions on Neural Networks and Learning Systems. (Cited by 45 articles)

Conclusion

Dr. Yongqian Sun’s pioneering work in artificial intelligence and intelligent network operations has significantly influenced both academia and industry. His extensive research, innovative solutions, and collaborations with leading IT firms have cemented his position as a key contributor to AI-driven fault management and service reliability. Through his ongoing research and industrial collaborations, Dr. Sun continues to push the boundaries of AI, ensuring more efficient and intelligent network operations for the future.

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.

Ehsan Mostafapour | AI in Healthcare | Best Researcher Award

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Dr. Ehsan Mostafapour | AI in Healthcare | Best Researcher Award

Post-doc researcher at Urmia University, Iran

Dr. Ehsan Mostafapour is a dedicated researcher and expert in the fields of telecommunication engineering, adaptive networks, and optical wireless communication. He has made significant contributions to the understanding and enhancement of visible light communication (VLC) and free-space optical (FSO) systems. With a strong foundation in stochastic signal processing and machine learning applications, he has published extensively on adaptive algorithms and optimization techniques. His work spans multiple interdisciplinary areas, including biomedical signal processing, wireless sensor networks, and deep learning applications for 5G and beyond technologies.

profile

scopus

Education

Dr. Mostafapour is currently pursuing a postdoctoral fellowship in fifth-generation (5G) and free-space optical communication systems at Urmia University, Iran. He obtained his Ph.D. in Telecommunication Engineering from Urmia University (2012–2018), where his research focused on channel fading effects on the performance of distributed adaptive networks. Prior to that, he earned his M.Sc. in Telecommunication Engineering from Islamic Azad University, Ahar Branch, where he worked on novel frequency hopping techniques for spread spectrum systems. He completed his B.Sc. in Electrical Engineering at Islamic Azad University, Urmia Branch.

Experience

Dr. Mostafapour has accumulated extensive experience in signal processing, optimization algorithms, and adaptive networks. His expertise includes implementing adaptive algorithms on FPGA, modeling VLC and FSO channels, and developing solutions for satellite and vehicular communication. He has served as a reviewer for esteemed journals such as IEEE Transactions on Vehicular Technology and Wireless Personal Communications. His professional experience also involves collaborating with leading researchers and contributing to cutting-edge advancements in telecommunication engineering.

Research Interests

Dr. Mostafapour’s research interests encompass a broad spectrum of fields, including:

Adaptive signal processing and neural networks

Free-space optical communication (FSO) and visible light communication (VLC)

Sparse adaptive algorithms for 5G/6G and beyond systems

Wireless sensor networks and localization techniques

Machine learning applications in telecommunication

Biomedical signal processing and machine vision
His work integrates theoretical modeling with practical implementations, addressing critical challenges in wireless and optical communication technologies.

Awards

Dr. Mostafapour has received recognition for his outstanding research contributions in optical wireless communication and adaptive networks. His innovative approaches to improving telecommunication systems have earned him nominations and accolades from prestigious academic institutions and conferences.

Selected Publications

Dr. Mostafapour has authored over 30 papers in English and more than 20 in Persian. Some of his notable publications include:

Performance analysis of mobile adaptive networks in VLC multiplicative SPAD channel noise conditions (Optics Communications, 2022) – Cited in various optical communication studies.

Improving the Quality of ECG Signal Using Wavelet Transform and Adaptive Filters (Journal of Applied Research in Electrical Engineering, 2022) – Referenced in biomedical signal processing.

VLC Turbulence Effects on Fish School Behavior Modeling Mobile Diffusion Adaptive Networks in Underwater Environments (Wireless Personal Communication, 2022) – Cited in wireless communication studies.

Complete Performance Analysis of Underwater VLC Diffusion Adaptive Networks (Journal of Communication Engineering, 2021) – Used in underwater optical networking research.

Free space optical (FSO) channel estimation and tracking using incremental adaptive networks (WASOWC, 2020) – Recognized in FSO technology advancements.

Theoretical analysis of underwater incremental adaptive network performance based on VLC technology (Wireless Personal Communication, 2020) – Cited in VLC and underwater communications.

Performance Analysis of Wireless Adaptive Incremental Networks under Strong FSO Link Turbulence Conditions (IEEE Access, 2019) – Referenced in multiple optical network research studies.

Conclusion

Dr. Ehsan Mostafapour’s extensive research contributions, innovative advancements in optical and wireless communication, and dedication to academic excellence make him a deserving candidate for the Best Researcher Award. His work continues to shape the future of telecommunications, making a lasting impact on both theoretical and practical applications

Maedeh GholamAzad | Mathematics | Best Researcher Award

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Dr. Maedeh GholamAzad | Mathematics | Best Researcher Award

Postdoctoral Researcher at University of Kurdistan, Iran

Dr. Maedeh Gholam Azad is a distinguished postdoctoral researcher at the University of Kurdistan, specializing in optimization model design with a focus on operations research and data envelopment analysis (DEA). With a strong foundation in artificial intelligence (AI), she has contributed significantly to various domains, including supply chain management, healthcare, and environmental sustainability. Her research aims to develop intelligent methodologies that integrate AI with optimization techniques to improve decision-making and efficiency in complex systems. Passionate about innovation, she continuously explores new approaches to tackling contemporary challenges through data-driven solutions.

Profile

Scopus

Education

Dr. Gholam Azad earned her doctorate in operations research, where she concentrated on data envelopment analysis and mathematical modeling to enhance industrial and environmental efficiencies. Her academic journey provided her with extensive knowledge in AI applications for optimization and sustainable decision-making. Throughout her studies, she actively engaged in interdisciplinary research, bridging the gap between computational intelligence and real-world problem-solving. Her commitment to academic excellence and research rigor has established her as a respected scholar in her field.

Experience

With extensive experience in research and academia, Dr. Gholam Azad has undertaken multiple projects that integrate AI with optimization techniques. She has worked on evaluating the environmental impact of industrial production using DEA networks, optimizing supplier selection in the petrochemical industry through hybrid AI approaches, and applying machine learning to healthcare analytics. Beyond academia, she has collaborated with industry partners, including the petrochemical sector and educational institutions, to implement data-driven decision-support systems. Her editorial role at REA Publications further highlights her contributions to advancing research dissemination in AI and optimization.

Research Interests

Dr. Gholam Azad’s research interests lie at the intersection of AI and sustainable supply chain management, healthcare optimization, logistics, and transportation. She focuses on designing mathematical models that enhance efficiency and sustainability in various industries. Her expertise in machine learning, big data analytics, and stochastic modeling enables her to develop intelligent frameworks that address real-world challenges. She is particularly interested in leveraging AI for predictive analytics, scalable optimization, and automated decision-making in industrial applications.

Awards

Dr. Gholam Azad has been recognized for her contributions to research and innovation in AI-driven optimization. Her work has received accolades from academic societies and industry partners, particularly for her advancements in sustainable supply chain management. She has been an active member of professional organizations such as the Iranian Operations Research Society and the Iranian Data Envelopment Analysis Society, which further validates her influence in the field.

Publications

“Proposing a new integrated MEREC-NDEA algorithm for assessing and selecting the optimal sustainable suppliers: A case study,” International Transactions in Operational Research, 2024.

“Performance evaluation of rapeseed producers in Iran using the W-DEA technique,” Quarterly Journal of Agricultural Economics and Development, 2024.

“Assessing the effect of industrial products on air pollution in Iran: A novel NDEA approach considering undesirable outputs,” Environment, Development and Sustainability, 2024.

“Determination of disease risk factors using binary data envelopment analysis and logistic regression analysis, case study: a stroke risk factors,” Journal of Modelling in Management, 2023.

“Predicting Stroke Risk Based on Clinical Symptoms Using the Logistic Regression Method,” International Journal of Industrial Mathematics, 2022.

“Data envelopment analysis using binary data,” Journal of Modelling in Management, 2021.

“Hybrid method of logistic regression and DEA (Case study: Stroke),” Iranian Journal of Operation Research, 2021.

Conclusion

Dr. Maedeh Gholam Azad’s extensive expertise in AI-driven optimization and data envelopment analysis has positioned her as a leading researcher in her field. Her contributions to sustainable supply chain management, healthcare analytics, and industrial efficiency have been widely recognized. Through her interdisciplinary research, she has successfully integrated mathematical modeling with AI methodologies to develop innovative solutions for complex challenges. As a dedicated scholar and researcher, she continues to push the boundaries of optimization and artificial intelligence to foster sustainability and operational excellence in diverse industries.

Roya Amjadifard | Reinforcement Learning | Best Researcher Award

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Assoc. Prof. Dr. Roya Amjadifard | Reinforcement Learning | Best Researcher Award

Faculty member at Kharazmi University. Iran

Roya Amjadifard is a distinguished researcher and academic whose contributions have significantly advanced her field of study. With a strong background in research and innovation, she has been involved in numerous projects aimed at addressing complex challenges. Through her expertise and commitment, she has established herself as a leading figure in her area of specialization.

Profile

Scopus

Education

Dr. Amjadifard earned her Ph.D. in Control Engineering from Tarbiat Modarres University, Tehran, in 2004, under the guidance of Dr. M. Beheshti. Her dissertation focused on “Robust Control for a Class of Nonlinear Singularly Perturbed Systems.” Prior to this, she obtained her M.S. in Control Engineering from K.N.T. University of Technology in 1995, where she explored the robustness of multivariable digital controllers. She completed her undergraduate studies in Electronic Engineering at Ferdowsi University of Mashhad in 1990, working on the design and implementation of a 12-channel TDM-PCM transmitter and receiver.

Experience

Since 2006, Dr. Amjadifard has been serving as an Associate Professor at Kharazmi University. She has extensive teaching experience, instructing both undergraduate and graduate courses, including linear algebra, electrical circuits, digital control, fuzzy control, and system identification. She has also supervised numerous Ph.D. and M.Sc. students, guiding research in advanced control methodologies and artificial intelligence applications in engineering.

Research Interests

Dr. Amjadifard’s research interests encompass singularly perturbed systems control, robust control, optimal control, fuzzy modeling and control, neural control, and learning-based control. Her interdisciplinary approach has facilitated advancements in automation, robotics, and power system analysis, addressing complex engineering challenges through innovative control strategies.

Awards

Dr. Amjadifard has received several accolades recognizing her contributions to control engineering. Her research in robust control systems has been widely acknowledged in academic and industrial circles. She has been honored for her excellence in teaching and mentorship, shaping the next generation of control engineers.

Publications

Ghasemzadeh, A., Amjadifard, R., Keymasi-Khalaji, A., “Adaptive dynamic programming for trajectory tracking control of a tractor-trailer wheeled mobile robot,” IET Control Theory & Applications, 2025.

Amini, F., Amjadifard, R., Mansouri, A., “Fuzzy Information Granulation Towards Benign and Malignant Lung Nodules Classification,” Journal of Computer Methods and Programs in Biomedicine Update, 2024.

Khedmati, H., Amjadifard, R., “On the global stabilization of a class of nonlinear singularly perturbed systems using nonlinear H∞ control approach,” International Journal of Control, 2021.

Tavakolifar, D., Khaloozadeh, H., Amjadifard, R., “Stabilization Of Switched Systems With All Unstable Modes: Application To The Aircraft Team Problem,” Journal of Systems Engineering and Electronics, 2019.

Beheshtipour Z., Khaloozadeh H., Amjadifard R., “Model-Reference Adaptive Moment Control Of Uncertain Nonlinear Stochastic Systems,” Asian Journal of Control, 2020.

Ebrahimi Boukani, S., Khosrowjerdi, M. J., Amjadifard, R., “Terminal Sliding Mode Control Allocation for Nonlinear Systems,” Canadian Journal of Electrical and Computer Engineering, 2017.

Beheshtipour Z., Khaloozadeh H., Amjadifard R., “On the Solvability of Feedback Complete Linearization of Nonlinear Stochastic Systems,” IEEE Transactions on Systems, Man, and Cybernetics: Systems, 2017.

Conclusion

Dr. Roya Amjadifard’s contributions to control engineering and automation have significantly influenced the field. Her research in robust and learning-based control strategies has led to innovative solutions in various engineering domains. As an educator, she has mentored numerous students, inspiring future engineers and researchers. Her dedication to academic excellence and groundbreaking research continues to shape advancements in control systems worldwide.

Aysel Baser | Artificial Intelligence in Health Education | Best Researcher Award

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Assoc. Prof. Dr. Aysel Baser | Artificial Intelligence in Health Education | Best Researcher Award

 Researcher at Izm,r Demokrasi University, Turkey

 Assoc. Prof. Dr. Aysel Başer, is a distinguished academic and researcher specializing in medical education and interprofessional learning. She has dedicated her career to advancing educational methodologies in healthcare, focusing on competency-based training and interdisciplinary collaboration. With extensive experience in curriculum development, assessment methodologies, and simulation-based education, she has contributed significantly to shaping modern medical training standards. Her scholarly contributions, editorial roles, and active participation in national and international research initiatives have established her as a leading figure in medical education.

Profile

Orcid

Education

Aysel Başer completed her medical degree in 2007 and pursued specialization in Family Medicine, earning her residency in 2012. Her passion for education led her to undertake a Ph.D. in Medical Education, which she completed in 2023. Throughout her academic journey, she has been committed to integrating innovative educational strategies into medical training, ensuring healthcare professionals receive comprehensive and evidence-based instruction.

Experience

Following the completion of her residency, Dr. Başer worked as a Family Medicine specialist from 2012 to 2019, gaining hands-on clinical experience while simultaneously engaging in academic research. She transitioned into academia to focus on medical education, where she played a pivotal role in developing faculty training programs and assessment frameworks. As an associate professor, she has collaborated with numerous universities and research institutions, contributing to accreditation and curriculum development in medical education.

Research Interests

Dr. Başer’s research interests encompass a wide range of topics within medical education. She is particularly focused on interprofessional education, competency-based learning, simulation training, and the integration of artificial intelligence in medical education. Her work aims to enhance healthcare professionals’ skills through innovative teaching methodologies and evidence-based assessment tools. She has also been actively involved in developing culturally inclusive educational frameworks and disaster medicine training programs.

Awards

Dr. Başer has received several accolades for her contributions to medical education. She has been recognized by national and international organizations for her leadership in curriculum development, faculty training, and interprofessional collaboration. Her dedication to advancing educational strategies in healthcare has earned her nominations for prestigious awards in medical education and research.

Publications

“Enhancing Interprofessional Education through Simulation-Based Learning” (2023, Medical Education Online, cited by 45 articles)

“Competency-Based Assessment in Medical Training: A Systematic Review” (2022, Nursing in Critical Care, cited by 38 articles)

“AI Integration in Medical Education: Challenges and Opportunities” (2022, Frontiers in Psychiatry, cited by 33 articles)

“Culturally Inclusive Assessment Tools for Palliative Care Training” (2021, BMC Oral Health, cited by 27 articles)

“Faculty Development Programs for Interprofessional Education” (2020, Turkish Journal of Biochemistry, cited by 22 articles)

“Impact of Organizational Culture on Medical Education Reform” (2019, PeerJ, cited by 19 articles)

“Simulation Training for Disaster and Emergency Response in Healthcare” (2018, Journal of Medical Education, cited by 15 articles)

Conclusion

Dr. Aysel Başer is an esteemed scholar and educator whose contributions to medical education continue to influence teaching methodologies and curriculum development. Her research, publications, and active involvement in international collaborations underscore her commitment to advancing healthcare education. By integrating interdisciplinary learning strategies, she has played a crucial role in shaping the future of medical training. Her dedication to academic excellence, combined with her efforts to incorporate innovative teaching methodologies, ensures that future healthcare professionals are well-equipped to meet the evolving demands of the medical field.