HMIMSA Younes | Application of Artificial Intelligence in Agriculture | Best Researcher Award

Published on by Cognitive Scientist Awards

Prof. HMIMSA Younes | Application of Artificial Intelligence in Agriculture | Best Researcher Award

Abdelmalek Essaadi University | Morocco

Professor Younes Hmimsa is a distinguished Moroccan academic and researcher serving as a Full Professor at the Polydisciplinary Faculty of Larache, Abdelmalek Essaadi University. His academic background spans animal biology, plant biotechnology, ecology, and wealth management, reflecting a multidisciplinary approach to environmental and agricultural sciences. With advanced degrees from the University of Tetouan and the University of Alicante, he has developed extensive expertise in plant biology, agroecology, and biodiversity conservation. Professionally, he has been a key figure in multiple international research programs such as PRIMA, ARIMNET, and EVOlea, focusing on agrobiodiversity, climate resilience, and sustainable agricultural systems. His research interests include plant phenology, genetic diversity, agroecosystem sustainability, and the socio-ecological dynamics of traditional farming systems in Mediterranean regions. He possesses strong research skills in agromorphological characterization, environmental data modeling, and interdisciplinary collaboration. Professor Hmimsa has coordinated numerous international conferences, seminars, and research networks that bridge scientific innovation and rural development. His scholarly achievements are complemented by prestigious roles as a reviewer, evaluator, and collaborator with global research institutions. A recipient of several academic honors and author of influential publications, he continues to advance sustainable agricultural practices and ecological research in Morocco and beyond, inspiring both scientific and community engagement.

Profile: ORCID

Featured Publications

José David Cuesta Sáez de Tejada | Data Analysis in Social Sciences | Outstanding Educator Award

Published on by Cognitive Scientist Awards

Mr. José David Cuesta Sáez de Tejada | Data Analysis in Social Sciences | Outstanding Educator Award

University of Murcia | Spain

Dr. José David Cuesta Sáez de Tejada is a distinguished Spanish scholar and psychopedagogue recognized for his academic dedication to educational quality, innovation, and inclusive learning. He holds a Licentiate in Psychopedagogy and a Doctorate in the same discipline from the University of Granada, where his doctoral research focused on leadership as a determinant of quality in university teaching, earning the highest academic distinction. He further pursued a Master’s degree in Mediation for the Independent Living of Persons with Disabilities from the University of Murcia, reflecting his commitment to supporting autonomy and social integration for individuals with special needs. Professionally, Dr. Cuesta Sáez de Tejada has been actively engaged in higher education, teacher training, and research in psychopedagogy, with expertise in educational leadership, intervention strategies, and inclusive pedagogy. His research interests encompass the enhancement of teaching methodologies, educational innovation, disability studies, and the improvement of learning environments through multidisciplinary collaboration. He has participated in numerous national and international congresses dedicated to autism, educational innovation, and higher education reform, contributing to the exchange of best practices. Honored for his scholarly excellence and leadership in educational research, Dr. Cuesta Sáez de Tejada continues to promote inclusive education and pedagogical transformation in contemporary academia.

Profile: Google scholar

Featured Publications

Zhengyi Yao | Artificial Intelligence | Best Researcher Award

Published on by Cognitive Scientist Awards

Mr. Zhengyi Yao | Artificial Intelligence | Best Researcher Award

Sichuan Normal University |China

Zhengyi Yao, from Neijiang, Sichuan, China, is a dedicated researcher affiliated with Sichuan Normal University, holding both bachelor’s and master’s degrees in Computer Science and Technology. His work primarily focuses on the Internet of Things (IoT), cybersecurity, cryptography, and artificial intelligence (AI). With a growing presence in academic publishing, he has contributed to several high-impact journals indexed in SCI and Scopus. Mr. Yao has demonstrated a strong commitment to advancing secure, intelligent systems, particularly in logistics and industrial applications. His interdisciplinary approach blends theoretical research with practical implementation, contributing to emerging technologies such as blockchain-enabled IIoT and quantum cryptography. In addition to publishing five journal articles and securing seven patents, he actively contributes to the field through applied innovations aimed at enhancing privacy protection and data security. As a passionate technologist, Mr. Yao is continually exploring transformative solutions in smart systems, emphasizing the ethical and secure integration of AI in modern digital infrastructure.

Profile

Education

Zhengyi Yao completed his academic training at Sichuan Normal University, earning both his bachelor’s and master’s degrees in Computer Science and Technology. His undergraduate studies provided a solid foundation in software development, algorithms, and system architecture, while his postgraduate work emphasized advanced topics such as artificial intelligence, cybersecurity, and cryptographic methods. During his graduate years, he engaged deeply with interdisciplinary studies, aligning computer science with real-world applications in logistics, IoT, and secure communication systems. His academic performance has been marked by consistent excellence and a proactive engagement in research-driven projects. While enrolled, he also explored the practical aspects of emerging technologies, developing tools and frameworks to support digital transformation in industrial systems. His education has been instrumental in shaping his scientific outlook, fostering a commitment to ethical innovation and robust digital security. These academic experiences continue to inform his contributions to academic research and patent development in the tech and security domains.

Experience

Zhengyi Yao has gained substantial experience as a researcher and innovator in the fields of IoT, cybersecurity, cryptography, and AI. While at Sichuan Normal University, he actively participated in multiple collaborative research efforts that examined the integration of blockchain with IIoT systems and privacy-focused AI applications in logistics. Despite limited consultancy and editorial appointments, his practical contributions are demonstrated through five SCI/Scopus-indexed journal publications and seven patents. He has co-authored research tackling challenges in smart logistics security, 5G-based blockchain sensors, and quantum cryptography, showcasing his capability to bridge theoretical and applied computing. Through independent and team-driven efforts, Mr. Yao has contributed to designing secure systems that support data integrity and user privacy in dynamic industrial environments. His hands-on research experience, supported by solid academic training, underpins his drive to innovate in secure computing technologies and has positioned him as a promising young professional in China’s growing digital research landscape

Research Focus

Zhengyi Yao’s research centers on the intersection of emerging technologies like IoT, blockchain, AI, and cybersecurity, with a strong focus on intelligent logistics systems. He explores secure device communication, privacy-preserving data protocols, and cryptographic models for industrial systems. His work on blockchain-enabled IIoT platforms aims to fortify command operations against cyber threats, while his investigations into quantum cryptography are pushing the boundaries of next-generation digital security. One of his key contributions is the development of 5G-based universal blockchain smart sensors, combining speed, scalability, and trust for dynamic logistics applications. His research also examines how AI can be ethically and securely integrated into cyber-physical environments to optimize data flow, user privacy, and system integrity. Through published works and patented innovations, he is shaping solutions to critical security challenges facing smart logistics and industrial platforms. His forward-thinking approach promotes safer, more resilient infrastructures in an increasingly connected digital world.

Publications

Sensitive Data Privacy Protection of Carrier in Intelligent Logistics System
Year: 2024
Citation:2

Blockchain-enabled device command operation security for Industrial Internet of Things
Year: 2023
Citation:12

5G-BSS: 5G-Based Universal Blockchain Smart Sensors
Year: 2022
Citation:2

Conclusion

Zhengyi Yao exemplifies the qualities of a dedicated and innovative researcher, with notable contributions to smart logistics, cybersecurity, and cryptographic technologies. His blend of academic rigor and applied invention positions him as a rising leader in secure digital systems.

Kihwan Nam | Artificial Intelligence | Best Faculty Award

Published on by Cognitive Scientist Awards

Prof. Kihwan Nam | Artificial Intelligence | Best Faculty Award

Dr. Kihwan Nam is an Assistant Professor in the Department of Management of Technology at Korea University and the founder of Aimtory, a high-technology AI company. With a unique blend of academic expertise and entrepreneurial insight, he specializes in Artificial Intelligence (AI), particularly Generative AI, Explainable AI, and Digital Transformation. He earned his Ph.D. in Information Systems from KAIST and holds degrees in Industrial Engineering and Statistics from Korea University and Yonsei University, respectively. Dr. Nam has an extensive research record, with publications in top-tier journals such as Journal of Marketing Research, Decision Support Systems, and Knowledge-Based Systems. His professional journey includes leadership roles in startups and significant AI industry contributions. He is passionate about bridging the gap between academia and industry through impactful, data-driven solutions that transform business strategies, smart factories, and healthcare systems. Dr. Nam is a leading figure in the fusion of cutting-edge AI technologies with business innovation.

Profile

🎓 Education

Dr. Kihwan Nam’s academic background spans statistics, engineering, and management. He holds a Ph.D. in Information Systems and Management Engineering from the prestigious KAIST College of Business, where he honed his expertise in AI-driven decision support and business analytics. Prior to his doctorate, he completed his M.S. in Industrial Engineering at Korea University, acquiring strong analytical and system optimization skills. His academic journey began with a B.A. in Statistics from Yonsei University, which laid a solid foundation in data analysis and quantitative modeling. This interdisciplinary academic training enables Dr. Nam to approach complex problems from technical, managerial, and data-driven perspectives. Throughout his studies, he cultivated a deep interest in predictive modeling, econometrics, and the integration of AI technologies in organizational contexts, which continues to shape his academic and industrial research today. His educational path reflects a consistent commitment to excellence and innovation across disciplines.

🧪 Experience

Dr. Nam has a dynamic career in both academia and industry. He currently serves as Assistant Professor in the Management of Technology at Korea University, following a faculty role in Management Information Systems at Dongguk University. In industry, he is the founder of Aimtory, a company focused on cutting-edge AI solutions, and previously led Basbai, an AI solution firm, as CEO. He also co-founded Sentience, reflecting his commitment to tech entrepreneurship. His dual roles have enabled him to conduct collaborative research with top-tier companies, implement AI in real-world applications, and train future innovators. Dr. Nam’s expertise extends across AI project development, big data analytics, and digital business transformation. His work in areas like smart factories, healthcare, and financial markets underscores his versatility. His diverse experience positions him as a thought leader at the intersection of research, innovation, and enterprise AI deployment.

🏅 Awards and Honors

Dr. Kihwan Nam has received numerous prestigious accolades for his impactful research and innovation. He was honored with the Best Paper Award from the Korea Intelligent Information System Society (2017) for his work on recommender systems in retail, and again in 2019 by the Information Systems Review Society for a field experiment in recommendation design. His deep learning-based financial distress prediction study was a Best Paper Nominee at the INFORMS Data Science Workshop (2020). In 2022, he secured top honors at the Korea Gas Corporation Big Data Competition and received an innovation award from the Startup Promotion Agency for the Big-Star Solution Platform. In 2023, he earned the Best Researcher Award at Dongguk University. These recognitions reflect his excellence in both theoretical contributions and practical applications of AI, reinforcing his role as a leading figure in AI-driven business analytics and intelligent systems research.

🔬 Research Focus

Dr. Nam’s research lies at the intersection of Artificial Intelligence, Business Analytics, and Digital Transformation. He specializes in Generative AI, Explainable AI, LLMs, NLP, and Computer Vision, aiming to drive intelligent decision-making in sectors like healthcare, finance, and manufacturing. His core research explores predictive analytics, recommender systems, robot advisory, and econometric modeling applied to real-world business and technological challenges. By incorporating econometrics with data mining and machine learning, he investigates user behavior, personalization strategies, and large-scale business optimization. His recent projects include stock and cryptocurrency prediction, smart factory optimization, and curated recommendation engines. He is also advancing research in digital transformation (DX) and blockchain-based token economies. Dr. Nam emphasizes bridging theory and application by applying AI innovations to actual business environments, often in collaboration with international enterprises. His work is deeply rooted in the integration of robust statistical methods with scalable, real-world AI systems.

✅ Conclusion

Dr. Kihwan Nam is a visionary academic and AI entrepreneur who merges deep theoretical knowledge with practical applications, shaping the future of AI-driven digital transformation across industries through innovative research, impactful teaching, and real-world solutions

Publications

Milena Živković | Artificial Intelligence in Medicine | Best Researcher Award

Published on by Cognitive Scientist Awards

Ms. Milena Živković | Artificial Intelligence in Medicine | Best Researcher Award

Research Associate| University of Kragujevac, Faculty of Science, Serbia

Milena Živković is a Research Associate at the University of Kragujevac, Faculty of Science, Serbia, with a background in physics and a research focus on the integration of artificial intelligence into medical physics and science education. Her expertise lies in AI-supported educational systems, Monte Carlo simulations in radiotherapy, and environmental radioactivity. With over 38 published papers, her work bridges physics, machine learning, and curriculum innovation. Milena is recognized for her mentorship of gifted students, contribution to interdisciplinary AI-based learning models, and international collaborations with researchers in Europe and the Middle East. She has co-authored dosimetric simulation software for cancer treatment optimization and earned accolades such as Best Oral Presentation Awards at international conferences. As an active member of the Serbian and German Physical Societies, she fosters science communication through national outreach projects and educational initiatives. Her contributions span both academic excellence and impactful community-based science promotion efforts.

Profile

🎓 Education

Milena Živković earned her formal education in physics, culminating in specialized research focused on medical physics, radiation dosimetry, and educational technology. She has completed advanced academic training in English for Academic Communication and Python programming, including Stanford’s “Code in Place.” She holds a Cambridge English Certificate and multiple certificates from the University of Kragujevac in academic writing and pedagogy. Her achievements during her student years include receiving the Annual Award for Best Student from 2015 to 2019, reflecting both academic excellence and extracurricular engagement. Additionally, she has participated in numerous interdisciplinary workshops, competitions, and science communication events, contributing to both her intellectual and pedagogical growth. With a strong foundation in applied physics, her academic journey has been characterized by the seamless integration of theoretical knowledge and practical research, which she continues to expand through post-academic training, conference participation, and interdisciplinary research collaboration with clinical and educational institutions.

🧪 Experience

Milena Živković has significant experience as a Research Associate at the University of Kragujevac, where she combines artificial intelligence with physics education and medical applications. Her research includes machine learning models for radiation dosimetry, classification systems in physics education, and anomaly detection in environmental radioactivity. She serves as a section editor and reviewer for journals like Imaging and Radiation Research and Radiation Science and Technology. Milena is also a contributor to national gifted education programs, curriculum development initiatives, and AI-assisted learning models. She has collaborated with international institutions, including projects with the Clinical Center Kragujevac and partners from Iraq, enhancing the practical application of her research. She has guided STEM projects for youth and mentored students in high school competitions. Her book on Monte Carlo simulations is used in academic and clinical contexts. Her scientific outreach projects further amplify her impact across the academic, educational, and public spheres.

🏅 Awards and Honors

Milena Živković has been the recipient of numerous awards recognizing both academic and community contributions. She received the Best Researcher Award at the University of Kragujevac in 2023 and multiple Best Oral Presentation Awards at international conferences in gynecology, women’s health, and ophthalmology. She also won the Bridge of Mathematics First Place Projects (2023, 2024), highlighting innovative physics education. From 2015 to 2019, she was honored with the Annual Best Student Award and continues to receive high praise for promoting science through projects funded by Serbia’s Center for the Promotion of Science. These include thematic campaigns like Brian May and the Queen of Physics, Our Air = Our Health, and Work + Active = Radioactive. Additionally, she holds advanced training certifications in pedagogy, communication, academic writing, and programming. Her dedication to science communication, youth mentorship, and educational innovation has made her a strong contender for the Young Scientist or Best Researcher Award.

🔬 Research Focus

Milena Živković’s research sits at the intersection of artificial intelligence, medical physics, and education technology. She focuses on developing machine learning-based models for radiation dose analysis, anomaly detection in environmental radioactivity, and AI-assisted problem classification in physics education. Her contributions to the FOTELP-VOX Monte Carlo platform enable precision 3D dose distribution modeling, now applied in clinical settings. She also investigates the ecological effects of radionuclide transfer and food safety. Milena’s interdisciplinary work includes collaborations with philosophers, clinicians, educators, and AI developers to improve curriculum delivery and treatment outcomes. She actively integrates AI into educational strategies to support gifted students and has co-authored software tools used in radiotherapy optimization. Her studies are not only technical but are aimed at real-world impact—ensuring safer radiation practices, informed public health strategies, and accessible science education. Her research promotes knowledge translation, making complex physics applicable to both education and healthcare.

✅ Conclusion

Milena Živković exemplifies a new generation of researchers merging artificial intelligence with applied physics to transform education, healthcare, and science communication. Through interdisciplinary projects, academic excellence, and outreach initiatives, she continues to redefine how science serves society while mentoring future innovators and advancing clinical safety and educational equity.

Publications

  • FOTELP-VOX-OA: Enhancing radiotherapy planning precision with particle transport simulations and Optimization Algorithms

    Computer Methods and Programs in Biomedicine
    2025-08 | Journal article
    DOI: 10.1016/j.cmpb.2025.108838
    CONTRIBUTORS: Milena Zivkovic; Filip Andric; Marina Svicevic; Dragana Krstic; Lazar Krstic; Bogdan Pirkovic; Tatjana Miladinovic; Mohamed El Amin Aichouche

  • FOTELP-VOX 2024: Comprehensive overview of its capabilities and applications

    Nuclear Technology and Radiation Protection
    2024 | Journal article
    DOI: 10.2298/NTRP2403212Z
    CONTRIBUTORS: Milena Zivkovic, P.; Tatjana Miladinovic, B.; Zeljko Cimbaljevic, M.; Mohamed Aichouche, E.A.; Bogdan Pirkovic, A.; Dragana Krstic, Z.

  • Radionuclide contamination in agricultural and urban ecosystems: A study of soil, plant, and milk samples

    Kragujevac Journal of Science
    2024 | Journal article
    DOI: 10.5937/KgJSci2400011A
    CONTRIBUTORS: Mohamed Aichouche, E.A.; Mihajlo Petrović, V.; Milena Živković, P.; Dragana Krstić, Ž.; Snežana Branković, R.

  • Development of DynamicMC for PHITS Monte Carlo package

    Radiation Protection Dosimetry
    2023-11-13 | Journal article
    DOI: 10.1093/rpd/ncad278
    Part of ISSN: 0144-8420
    Part of ISSN: 1742-3406
    CONTRIBUTORS: Hiroshi Watabe; Tatsuhiko Sato; Kwan Ngok Yu; Milena Zivkovic; Dragana Krstic; Dragoslav Nikezic; Kyeong Min Kim; Taiga Yamaya; Naoki Kawachi; Hiroki Tanaka et al.

Farshad Sadeghpour | Data prediction | Best Researcher Award

Published on by Cognitive Scientist Awards

Dr. Farshad Sadeghpour | Data prediction | Best Researcher Award

Farshad Sadeghpour (b. 1996) 🇮🇷 is a Petroleum Engineer and Data Scientist 💻🛢️ with expertise in reservoir engineering, petrophysics, and AI applications in the energy sector. Based in Tehran, Iran 📍, he holds a Master’s and Bachelor’s in Petroleum Exploration. With extensive experience in EOR, SCAL/RCAL analysis, and machine learning, Farshad has contributed to both academic and industrial R&D at RIPI, NISOC, and PVP. He has published multiple research articles 📚, won international awards 🏆, and participated in key petroleum projects. He served in the military 🪖 and actively collaborates with academia and industry on AI-driven energy solutions.

Profile

Education 🎓

🧑‍🎓 Master’s in Petroleum Engineering (Petroleum Exploration), Petroleum University of Technology, Abadan 🇮🇷 (2019–2022) | GPA: 18.82/20
🎓 Bachelor’s in Petroleum Engineering, Islamic Azad University (Science & Research Branch), Tehran 🇮🇷 (2015–2019) | GPA: 19.14/20
📚 Courses covered include reservoir engineering, geomechanics, well-logging, and advanced data analytics.
🛠️ Projects include CO₂ storage modeling, permeability prediction via AI, and LWD-based mud loss forecasting.
📊 Developed key industry collaborations with NISOC, RIPI, and OEID through thesis, internships, and military service projects.
💡 Honed computational and simulation skills using MATLAB, Python, COMSOL, Petrel, and ECLIPSE.
🏛️ Academic mentors: Dr. Seyed Reza Shadizadeh, Dr. Bijan Biranvand, Dr. Majid Akbari.

Experience 👨‍🏫


🔬 Computer Aided Process Engineering (CAPE) – Petroleum Reservoir Engineer (Nov 2024–Present)
🛢️ Petro Vision Pasargad – Reservoir Engineer & Lab Operator (Sep 2023–May 2024)
🧠 Research Institute of Petroleum Industry (RIPI) – Petroleum Engineer, Data Scientist (Mar 2023–Apr 2024)
🏭 National Iranian South Oil Company (NISOC) – Petroleum Engineer, Petrophysicist (Mar 2021–Nov 2024)
🧪 Internships: NIOC – Exploration Management, Oil & Energy Industries Development (OEID)
📊 Key contributions include EOR analysis, SCAL/RCAL lab testing, permeability modeling, machine learning pipelines, and field data analysis.
🧾 Delivered reports, simulations, and AI models supporting production optimization and reservoir characterization.

Awards & Recognitions 🏅

🥉 3rd Prize Winner – EAGE Laurie Dake Challenge 2022 (Madrid, Spain) 🌍
🎖️ Recognized for thesis excellence in AI-driven mud loss prediction with NISOC collaboration
📌 Acknowledged during military service project with RIPI for developing ANN-based well log models
🏅 Published in high-impact journals such as Energy, Geoenergy Science and Engineering, and JRMGE
✍️ Co-author of multiple peer-reviewed papers and under-review articles across petroleum engineering disciplines
🔬 Worked alongside top researchers including Dr. Ostadhassan, Dr. Gao, and Dr. Hemmati-Sarapardeh
🛠️ Actively participated in multidisciplinary teams combining AI, geomechanics, and petrophysics
📢 Regular presenter and contributor at petroleum conferences and AI-in-energy seminars.

Research Interests 🔬

📌 AI & ML applications in petroleum engineering 🧠🛢️ – including ANN, genetic algorithms, and deep learning
📊 Mud loss zone prediction, formation permeability modeling, CO₂ storage feasibility using ML
🧪 Experimental rock mechanics: nanoindentation, geomechanical upscaling, SCAL/RCAL testing
📈 Petrophysical property estimation in carbonate and unconventional reservoirs
🌍 Reservoir simulation, LWD analysis, and smart data integration using Python, Petrel, COMSOL
📖 Notable studies include: elastic modulus upscaling, kerogen behavior under pyrolysis, RQI/FZI modeling
🔬 Interdisciplinary projects bridging data science with geoscience and reservoir engineering
🤝 Collaboration with academic and industry leaders to develop practical, AI-driven solutions for energy challenges.

Publications 

  • Elastic Properties of Anisotropic Rocks Using an Stepwise Loading Framework in a True Triaxial Testing Apparatus

    Geoenergy Science and Engineering
    2025-04 | Journal article
    DOI: 10.1016/j.geoen.2025.213883
    CONTRIBUTORS: Farshad Sadeghpour; Hem Bahadur Motra; Chinmay Sethi; Sandra Wind; Bodhisatwa Hazra; Ghasem Aghli; Mehdi Ostadhassan

  • Storage Efficiency Prediction for Feasibility Assessment of Underground CO2 Storage: Novel Machine Learning Approaches

    Energy
    2025-04 | Journal article
    DOI: 10.1016/j.energy.2025.136040
    CONTRIBUTORS: Farshad Sadeghpour

  • A new petrophysical-mathematical approach to estimate RQI and FZI parameters in carbonate reservoirs

    Journal of Petroleum Exploration and Production Technology
    2025-03 | Journal article
    DOI: 10.1007/s13202-025-01952-6
    CONTRIBUTORS: Farshad Sadeghpour; Kamran Jahangiri; Javad Honarmand

  • Effect of stress on fracture development in the Asmari reservoir in the Zagros Thrust Belt

    Journal of Rock Mechanics and Geotechnical Engineering
    2024-11 | Journal article
    DOI: 10.1016/j.jrmge.2023.12.027
    CONTRIBUTORS: Ghasem Aghli; Babak Aminshahidy; Hem Bahadur Motra; Ardavan Darkhal; Farshad Sadeghpour; Mehdi Ostadhassan

  • Comparison of geomechanical upscaling methods for prediction of elastic modulus of heterogeneous media

    Geoenergy Science and Engineering
    2024-08 | Journal article
    DOI: 10.1016/j.geoen.2024.212915
    CONTRIBUTORS: Farshad Sadeghpour; Ardavan Darkhal; Yifei Gao; Hem B. Motra; Ghasem Aghli; Mehdi Ostadhassan

Yuanming Zhang | Intelligent data processing and analysis | Best Researcher Award

Published on by Cognitive Scientist Awards

Dr. Yuanming Zhang | Intelligent data processing and analysis | Best Researcher Award

Yuanming Zhang is an Associate Professor at the College of Computer Science and Technology, Zhejiang University of Technology, Hangzhou, China. He earned his Ph.D. in Information Science from Utsunomiya University, Japan, in 2010. His research focuses on data processing, graph neural networks, knowledge graphs, prognostics, health management, and condition monitoring. With expertise in deep learning and artificial intelligence, he has contributed significantly to neural network advancements. His work integrates cutting-edge technologies for intelligent data analysis and predictive maintenance. 📊🧠🔍

Profile

Education 🎓

Yuanming Zhang obtained his Ph.D. in Information Science from Utsunomiya University, Japan, in 2010. His academic journey emphasized computational intelligence, machine learning, and advanced data analytics. He developed expertise in deep learning models, including convolutional and graph neural networks. His education laid a strong foundation for interdisciplinary research, integrating artificial intelligence with real-world applications. 📚🧑‍🎓📈

Experience 👨‍🏫

Yuanming Zhang has been an Associate Professor at Zhejiang University of Technology since completing his Ph.D. in 2010. His professional journey spans over a decade in academia, focusing on AI, neural networks, and knowledge graphs. He has supervised research projects, collaborated on industry applications, and contributed to advancements in predictive analytics and condition monitoring. His expertise extends to teaching, mentoring, and interdisciplinary AI applications. 🏫🤖📡

Research Interests 🔬

Yuanming Zhang specializes in deep learning, attention mechanisms, graph neural networks, and AI-driven predictive analytics. His research explores neural architectures for data processing, knowledge representation, and condition monitoring. His expertise spans convolutional networks, LSTMs, GRUs, and deep belief networks. His work contributes to advancements in AI-driven diagnostics, intelligent systems, and real-time health monitoring applications. 🧠📊🖥️

Awards & Recognitions 🏅

Yuanming Zhang has received recognition for his contributions to AI, machine learning, and data analytics. His work in deep learning and knowledge graphs has earned him accolades from research institutions and conferences. His papers in neural networks and predictive maintenance have been highly cited, solidifying his impact in the field. His research excellence has been acknowledged through grants and academic distinctions. 🎖️📜🔬

Publications 

 

Chunyu Liu | Cognitive Computing | Best Researcher Award

Published on by Cognitive Scientist Awards

Dr. Chunyu Liu | Cognitive Computing | Best Researcher Award

Chunyu Liu is a Lecturer at North China Electric Power University, specializing in machine learning, neural decoding, and visual attention. 📚 She earned her B.S. in Mathematics and Applied Mathematics from Henan Normal University, an M.S. in Applied Mathematics from Northwest A&F University, and a Ph.D. in Computer Application Technology from Beijing Normal University. 🎓 She completed postdoctoral training at Peking University. 🔬 Her research integrates AI methodologies with cognitive neuroscience, focusing on neural encoding, decoding, and attention mechanisms. 🧠 She has published over 10 research papers, including six SCI-indexed publications as the first author. 📝 Her work aims to bridge artificial intelligence with human cognitive function understanding, contributing significantly to computational neuroscience. 🌍 Liu has also been involved in several major research projects, furthering advancements in neural signal analysis and cognitive computing. 🚀

Profile

Education 🎓

Chunyu Liu holds a strong academic background in mathematics and computational sciences. She obtained her B.S. degree in Mathematics and Applied Mathematics from Henan Normal University. ➕ She pursued her M.S. in Applied Mathematics at Northwest A&F University, where she deepened her expertise in mathematical modeling. 🔢 Continuing her academic journey, she earned a Ph.D. in Computer Application Technology from Beijing Normal University. 🖥️ Her doctoral research explored advanced AI techniques applied to neural decoding and cognitive processing. 🧠 To further refine her skills, she completed postdoctoral training at Peking University, focusing on integrating artificial intelligence with neural mechanisms. 🔬 Her academic pathway reflects a multidisciplinary approach, merging mathematics, computer science, and cognitive neuroscience to address complex challenges in brain science and AI. 📊 Liu’s education laid the foundation for her contributions to machine learning, visual attention studies, and neural encoding research.

Experience 👨‍🏫

Dr. Chunyu Liu is currently a Lecturer at North China Electric Power University, where she teaches and conducts research in cognitive computing and machine learning. 🎓 She has led and collaborated on multiple projects related to neural encoding and decoding, investigating how the brain processes object recognition, emotions, and attention. 🧠 Prior to her current role, she completed postdoctoral research at Peking University, where she worked on advanced AI-driven models for neural signal analysis. 🔍 Over the years, Liu has gained extensive experience in analyzing multimodal neural signals, including magnetoencephalography (MEG) and functional MRI (fMRI). 📡 She has also served as a reviewer for esteemed scientific journals and collaborated with interdisciplinary research teams on AI and brain science projects. 🔬 Her expertise extends to both academia and industry, where she has contributed to the development of novel computational models for decoding brain activity. 🚀

Research Interests 🔬

Dr. Chunyu Liu’s research integrates artificial intelligence and brain science to understand cognitive functions through neural decoding. 🧠 She employs multi-modal neural signals such as magnetoencephalography (MEG) and functional magnetic resonance imaging (fMRI) to analyze brain activity. 📡 Her work explores neural encoding and decoding, focusing on object recognition, emotion processing, and multiple-object attention. 🎯 She develops AI-based models to extract human brain features and gain insights into cognitive mechanisms. 🤖 By integrating psychological experimental paradigms with AI, Liu aims to advance computational neuroscience. 🏆 Her research also inspires the development of new AI theories and algorithms based on principles of brain function. 📊 She has led major projects in cognitive computing, contributing significantly to both theoretical advancements and practical applications in neural signal processing. 🚀 Through her work, she bridges the gap between human cognition and artificial intelligence, driving innovations in brain-computer interface research. 🏅

 

Awards & Recognitions 🏅

Dr. Chunyu Liu has received recognition for her outstanding contributions to cognitive computing and AI-driven neuroscience research. 🏅 She has been nominated for the prestigious International Cognitive Scientist Award for her pioneering work in neural decoding and visual attention mechanisms. 🎖️ Liu’s research publications have been featured in high-impact journals, earning her accolades from the scientific community. 📜 Her first-author papers in IEEE Transactions on Neural Systems and Rehabilitation Engineering, Science China Life Sciences, and IEEE Journal of Biomedical and Health Informatics have been widely cited. 📝 She has also been honored with research grants and funding for AI-driven cognitive studies. 🔬 Her innovative work in decoding brain signals has been recognized in international AI and neuroscience conferences. 🌍 Liu’s academic excellence and contributions continue to shape the field of computational neuroscience and machine learning applications in cognitive science. 🚀

Publications 📚

Gokhan Yildirim | Marketing analytics | Best Researcher Award

Published on by Cognitive Scientist Awards

Dr. Gokhan Yildirim | Marketing analytics | Best Researcher Award

Gokhan Yildirim is an Associate Professor of Marketing at Imperial College Business School, specializing in marketing analytics and return on investment. His expertise spans digital marketing, long-term marketing effectiveness, and customer mindset metrics. With a strong foundation in applied time series econometrics and machine learning, he has made significant contributions to the field of marketing science. Yildirim has held academic positions at Lancaster University and has been a visiting researcher at Tilburg University. His research has been widely published in top-tier journals, influencing both academia and industry.

Profile

Education 🎓

Gokhan Yildirim earned his PhD in Business Administration and Quantitative Methods from Universidad Carlos III de Madrid (UC3M) in 2012, with a dissertation on marketing dynamics. His academic journey began with a BA in Business Administration (1999–2003) and an MSc in Quantitative Methods (2003–2006) from Marmara University, Istanbul. He also conducted research as a visiting scholar at Tilburg University, Netherlands, further strengthening his expertise in marketing analytics and econometrics.

Experience 👨‍🏫

Yildirim has been an Associate Professor of Marketing at Imperial College Business School since 2019, following his tenure as an Assistant Professor from 2016 to 2019. Before that, he was an Assistant Professor of Marketing Analytics at Lancaster University (2012–2016). His industry collaborations focus on marketing resource allocation, customer analytics, and data-driven decision-making. His research integrates econometric modeling and machine learning to optimize marketing strategies and enhance business performance.

Research Interests 🔬

Yildirim’s research centers on return on marketing investment, digital marketing effectiveness, and customer mindset metrics. He applies advanced econometric and machine learning techniques to analyze marketing resource allocation and long-term advertising impacts. His work explores how marketing strategies influence consumer behavior and business growth, contributing to both academic literature and real-world marketing practices

Awards & Recognitions 🏅

Yildirim has received several prestigious awards, including the 2017–2018 Gary Lilien ISMS-MSI-EMAC Practice Prize for his work on multichannel marketing at L’Occitane. He has also secured multiple research grants, such as the Wharton Customer Analytics Initiative (2015–2016) and the Spanish Ministry of Science and Innovation grants (2012–2018). His contributions have been recognized through funding from AiMark and other leading research bodies, further cementing his influence in marketing analytics.

Publications 📚

Pritpal Singh | Ambiguous set theory | Best Researcher Award

Published on by Cognitive Scientist Awards

Dr. Pritpal Singh | Ambiguous set theory | Best Researcher Award

Pritpal Singh is an Assistant Professor at the Department of Data Science and Analytics, Central University of Rajasthan, India. He earned his Ph.D. in Computer Science and Engineering from Tezpur (Central) University in 2015 and has held various academic and research positions in India, Taiwan, and Poland. His expertise includes soft computing, optimization algorithms, time series forecasting, image analysis, and machine learning. He has published extensively in high-impact journals like IEEE Transactions, Elsevier, and Springer. His research focuses on advanced computational techniques, including quantum-based optimization and fMRI data analysis. Dr. Singh has received prestigious research fellowships, including a Postdoctoral Fellowship from Taiwan’s Ministry of Science and Technology and an International Visiting Research Fellowship from Poland’s Foundation for Polish Science. His work significantly contributes to artificial intelligence, data science, and computational modeling, making him a key figure in these fields. 🚀📊📚

Profile

Education 🎓

Dr. Pritpal Singh obtained his Ph.D. in Computer Science and Engineering from Tezpur (Central) University, Assam, India, in 2015, specializing in soft computing applications for time series forecasting. He completed his Master in Computer Applications (MCA) from Dibrugarh University, Assam, in 2008, following a B.Sc. in Physics, Chemistry, and Mathematics from the same university in 2005. His academic journey began with Higher Secondary (2002) from the Assam Higher Secondary Education Council and HSLC (1999) from the Secondary Education Board of Assam. His doctoral dissertation focused on improving fuzzy time series forecasting models through hybridization with neural networks and optimization techniques like particle swarm optimization. His strong foundation in computational sciences, mathematics, and engineering has shaped his research in AI-driven predictive modeling, optimization, and data analytics. 🎓📚🔬

Experience 👨‍🏫

Dr. Singh has extensive academic and research experience. He is currently an Assistant Professor at the Central University of Rajasthan (since June 2022). Previously, he was an Assistant Professor at CHARUSAT University, Gujarat (2015-2019), and a Lecturer at Thapar University, Punjab (2013-2015). His research experience includes serving as an Adjunct Professor (Research) at Jagiellonian University, Poland (2020-2022) and a Postdoctoral Research Fellow at National Taipei University of Technology, Taiwan (2019-2020). Throughout his career, he has mentored students, led research projects, and contributed significantly to data science, artificial intelligence, and computational modeling. His global exposure has enriched his expertise in optimization, machine learning, and interdisciplinary AI applications. 🌍📊

Research Interests 🔬

Dr. Singh’s research revolves around ambiguous set theory, optimization algorithms, time series forecasting, image analysis, and machine learning. He specializes in hybrid computational techniques, particularly quantum-based optimization and soft computing applications. His work extends to fMRI data analysis, mathematical modeling, and simulation. His research has been published in leading journals such as IEEE Transactions on Systems, Elsevier’s Information Sciences, and Artificial Intelligence in Medicine. His focus on interdisciplinary AI applications, particularly in healthcare and data science, has positioned him as a key contributor to advancing machine learning methodologies. 🧠📊🤖Awards & Recognitions 🏅

Dr. Singh has received multiple prestigious fellowships and recognitions. In 2019, he was awarded a Postdoctoral Research Fellowship by the Ministry of Science and Technology, Taiwan. In 2020, he received the International Visiting Research Fellowship from the Foundation for Polish Science, Poland. His contributions to artificial intelligence, optimization, and data science have been recognized globally through research grants, invited talks, and publications in top-tier journals. His work in soft computing and AI-driven predictive modeling continues to impact both academic and industrial research. 🏅🎖️📜

Publications 📚

  • Scopus 1-2023: P. Singh, An investigation of ambiguous sets and their application to
    decision-making from partial order to lattice ambiguous sets. Decision Analytics
    Journal (Elsevier), 08, 100286, 2023.
  • Scopus 2-2023: P. Singh, A general model of ambiguous sets to a single-valued ambiguous numberswith aggregation operators. Decision Analytics Journal (Elsevier), 08,
    100260, 2023.
  • Scopus 3-2023: P. Singh, Ambiguous set theory: A new approach to deal with unconsciousness and ambiguousness of human perception. Journal of Neutrosophic and
    Fuzzy Systems (American Scientific Publishing Group), 05(01), 52–58, 2023.
  • Scopus 4-2022: P. Singh, Marcin W ˛atorek, Anna Ceglarek, Magdalena F ˛afrowicz, and
    Paweł O´swi˛ecimka, Analysis of fMRI Time Series: Neutrosophic-Entropy Based
    Clustering Algorithm. Journal of Advances in Information Technology, 13(3), 224–
    229, 2022.