Kadir Uludag | Educational Psychology | Educational Psychology Impact

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Dr. Kadir Uludag | Educational Psychology | Educational Psychology Impact

Dr. Kadir Uludag is a postdoctoral researcher in psychology with a Ph.D. in Applied Psychology from the University of Chinese Academy of Sciences. His research bridges schizophrenia, brain imaging, and educational psychology. Dr. Uludag is passionate about disseminating scientific knowledge through his personal website (ifx0.com/psychology), YouTube channel (youtube.com/boooringlearning), and as the founder of the open-access journal Novelty in Psychology. He has published extensively, including 12 Web of Science (Q1) and 21 Scopus-indexed works, and serves on the editorial boards of 24 international journals. With over 670 manuscript reviews listed on ORCID, he has received multiple awards recognizing his scientific contributions. Dr. Uludag also manages four ongoing book projects. Skilled in Python-based machine learning and data analysis tools, he is eager to collaborate on innovative research that contributes meaningfully to psychology and society.

Profile

Education 🎓

Dr. Uludag earned his Ph.D. in Applied Psychology from the University of Chinese Academy of Sciences (2019–2023, GPA 3.93), focusing on brain imaging and mental health. He completed an M.A. in Forensic Sciences (Social Sciences) from Istanbul University (2016–2018, GPA 3.61), where he developed a strong foundation in psychological evaluation in legal settings. His undergraduate degree in Psychological Counseling and Guidance was obtained from Çanakkale Onsekiz Mart University (2012–2016, GPA 3.30), complemented by an associate degree in Laboratory Assistant and Veterinary Sciences from Eskisehir Anatolian University (2013–2015, GPA 3.79). He has also pursued training in TESOL, SPSS, machine learning (random forest, SVM, logistic regression, neural networks), Python programming, web development, and data visualization. His education has been guided by distinguished scholars including Prof. Xiang Yang Zhang, Prof. Erdinc Ozturk, and Prof. Neylan Ziyal. These experiences shaped his multidisciplinary approach to psychological research.

Experience 👨‍🏫

Dr. Kadir Uludag is currently a postdoctoral researcher at Shanghai Jiao Tong University (2023–Present) and has been appointed for a future role at Capital Medical University, Beijing (2025–). His expertise spans schizophrenia, neuroimaging, and educational psychology. Previously, he served as a special education teacher for autistic children at Karabük Municipality Autistic Children Education Center (2017), applying cognitive-behavioral and humanistic therapeutic approaches. He also completed internships as a psychological counselor at Toki Anadolu Lisesi (2016) and a veterinary technician at Safranbolu Veterinary Clinic (2015). He brings in-depth knowledge of psychological development and intervention techniques across diverse settings. In academia, Dr. Uludag serves on the editorial boards of 24 journals and has edited four book projects. His dynamic involvement in teaching, research, editing, and mentoring reflects a holistic commitment to the field of psychology and science communication.

Awards & Recognitions 🏅

Dr. Uludag has received numerous accolades, including the “Highest Number of Views” award (2023–2024) from the Journal of Clinical and Basic Psychosomatics for his narrative review on smoking and schizophrenia. He earned reviewer awards from Imeta Journal and Imetaomics for reviewing more than five papers each. Additionally, he holds a Certificate of Excellence from the Shanghai Table Tennis Museum and the American Chemical Society Reviewer Lab Certificate. His extensive peer-review contributions (over 670 reviews) are recognized by ORCID and editorial teams worldwide. His editorial involvement includes serving on boards of journals like Health Policy and Technology, Plos One, and Asean Journal of Psychiatry, among others. He has received invitations for guest editorships and honorary memberships in various scholarly outlets. These honors reflect his impactful presence in academia and his dedication to advancing global psychological research.

Research Interests 🔬

Dr. Kadir Uludag’s primary research interests include schizophrenia, neuroimaging (fMRI and EEG), and educational psychology. His doctoral work applied Python-based machine learning (random forest, SVM, logistic regression) to brain imaging data, emphasizing computational psychiatry and precision diagnostics. He has published in Q1 journals such as Asian Journal of Psychiatry, American Chemical Neuroscience, Psychology Research and Behavior Management, General Psychiatry, and Antioxidants. His Scopus-indexed contributions span educational psychology, forensic science, and neuroscience. His research applies interdisciplinary tools—Python, Psychopy, SPSS, R, NLP, and image processing libraries—to explore psychiatric conditions. He integrates theory and practice through data visualization, cognitive-behavioral therapy models, and open-science advocacy. Dr. Uludag actively shares findings via his YouTube channel and academic website, fostering transparency and education. His work aims to bridge gaps between neuroscience, education, and technology to improve mental health outcomes and knowledge dissemination.

Publications

Chunyu Liu | Cognitive Computing | Best Researcher Award

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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 📚

Xiuwei Zhang | Psychology | Best Researcher Award

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 Dr. Xiuwei Zhang | Psychology | Best Researcher Award

Xiuwei Zhang, PhD, is a researcher at Hefei University of Technology, specializing in traffic behavior and psychology. She holds a doctoral degree from Hefei University of Technology, where her work focuses on improving traffic safety through behavioral psychology methods. Zhang’s research addresses critical issues such as driver behavioral changes and children’s perception of street crossing hazards. She is deeply involved in advancing traffic safety by understanding how people interact with traffic environments, with an emphasis on psychological cognition. Zhang has also contributed significantly to the field through several published papers and patents, aiming to enhance both driver and pedestrian safety. With an established academic career and passion for traffic psychology, Zhang aims to provide actionable solutions to improve road safety globally.

Profile

Education 🎓

Xiuwei Zhang completed her undergraduate studies at Qingdao University of Science and Technology. She pursued her master’s and doctoral degrees at Hefei University of Technology, where she focused on traffic behavior and psychology. During her time at Hefei, Zhang developed a deep understanding of how psychological factors influence road safety, particularly in the context of driver behavior and children’s traffic hazard perception. Her academic training has allowed her to integrate cognitive psychology with transportation safety, paving the way for innovative solutions to reduce traffic-related accidents. Zhang’s educational background in this interdisciplinary field has made her a strong proponent of using behavioral psychology to improve urban traffic environments, with her research significantly contributing to traffic safety science.

Experience 👨‍🏫

Xiuwei Zhang has experience conducting impactful research on traffic psychology at Hefei University of Technology, where she has worked on driver behavior, risk perception, and children’s safety while crossing streets. She contributed to multiple key projects, such as the optimization of urban road intersections using intelligent detection and the evolution of driver’s risk perception in co-driving vehicles. Zhang participated in developing local and national standards, such as the “Evaluation Standard for Driver Takeover Ability of Autonomous Vehicles.” Her patents include solutions for assessing and preventing conflicts between human-vehicle interactions in signal intersections. Additionally, Zhang’s academic role extends to reviewing papers for Transportation Research Part F: Traffic Psychology and Behavior. She is an active participant in cutting-edge research projects, such as the National Natural Science Foundation of China and Anhui Province’s housing and urban development projects, focusing on making roads safer through innovative traffic designs and behavioral analysis.

Research Interests 🔬

Xiuwei Zhang’s research focuses on traffic behavior and psychology, with particular attention to driver behavior, children’s traffic safety, and cognitive biases in road environments. Her work aims to enhance the perception of road hazards, particularly among children, and to improve road safety through behavioral psychology techniques. One of her significant contributions is the study of children’s perception of street-crossing risks under visually occluded conditions, providing valuable insights into how environmental factors impact traffic behavior. Zhang’s research on driver behavior changes, particularly in co-driving scenarios with automated vehicles, seeks to develop better risk perception strategies to improve safety on the roads. Her interdisciplinary approach integrates traffic safety with cognitive science, making her work influential in both the practical and theoretical aspects of traffic safety. Zhang’s innovations also extend to the design of intelligent traffic systems and road intersections, contributing to the future of urban road safety in smart cities.

Awards & Recognitions 🏅

Xiuwei Zhang has received several prestigious awards and honors during her academic career, including the “Outstanding Graduate of the School Class of 2024” and multiple scholarships, such as the School Second Class Scholarship for the 2022-2023 academic year. Her excellence as a volunteer was recognized when she was named the “Outstanding Red Cross Volunteer” of Qingdao West Coast New District in 2018. Zhang’s consistent academic achievements are highlighted by her scholarships across multiple years and her significant contributions as a member of the Auto Traffic College Institute Graduate Student Association. These accolades reflect her dedication to research, teaching, and community service. Zhang’s awards demonstrate her potential as a leader in traffic safety research and behavioral psychology, highlighting her academic excellence and contributions to improving road safety.

Publications 📚

Emmanuel Kaboja Magna | Cognitive | Cognitive Rehabilitation Impact

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Dr. Emmanuel Kaboja Magna | Cognitive | Cognitive Rehabilitation Impact

CSIR-Water Research Institute, Ghana

Dr. Emmanuel Kaboja Magna is a Research Scientist at the Fisheries and Aquaculture Division of the Council for Scientific and Industrial Research-Water Research Institute (CSIR-WRI). He earned his Bachelor’s degree in Biological Sciences (Oceanography and Fisheries) from the University of Ghana in 2007, followed by a Master’s degree in Health Informatics from the Kwame Nkrumah University of Science and Technology, Ghana, in 2014. He completed his PhD in Environmental Science in 2020 at the Institute for Environment and Sanitation Studies (IESS), University of Ghana. His doctoral research focused on the ecological and human health implications of contaminants linked to cage aquaculture on the Volta Basin of Ghana. He investigated the levels of polychlorinated biphenyls, organochlorine pesticides, and heavy metals in water, sediment, and cage tilapia, highlighting the ecological risks and pollution status of sediment, as well as the health risks of consuming such fish. Dr. Magna has also conducted research on solid waste, the impact of climatic variables on crop yield, malaria distribution, and a review of Ghana’s mental health policy. His research has resulted in thirteen publications in reputable international journals. Apart from his work at WRI, he has participated in various research activities focusing on pesticides, antibiotics, PBDEs, and PAHs in different environmental matrices, wastewater quality treatment, and reuse. He is known for his innovation, intellectual acumen, and high research curiosity. Dr. Magna has jointly supervised undergraduate students at several Ghanaian universities and serves as a reviewer for the international journal Food Chemistry Advances. He also has about eight years of teaching experience at the senior high school level.

 

Profile

Education

Dr. Emmanuel Kaboja Magna holds a PhD in Environmental Science from the University of Ghana, which he completed between 2016 and 2020. His doctoral thesis focused on the ecological and human health implications of contaminants linked to cage aquaculture in the Volta Basin of Ghana. He earned a Master’s degree in Health Informatics from Kwame Nkrumah University of Science and Technology (KNUST) in 2014, with his thesis exploring the implementation of Electronic Medical Record (EMR) systems at Tema General Hospital, addressing the potential benefits and challenges. Dr. Magna obtained his Bachelor’s degree in Oceanography and Fisheries from the University of Ghana in 2007, where he completed his dissertation on the application of GIS to coastal tourism in Ghana. He also completed his SSSCE in General Science at St. Mary’s Seminary Secondary School in 2001. In addition to his academic qualifications, Dr. Magna has earned several professional certificates, including a certificate in System Thinking for Sustainable Development in Ghana from the Institute for Environment and Sanitation Studies (IESS), University of Ghana, and North Carolina State, in June 2017. He also completed training on pesticide, PAH, PCB, and antibiotic analysis using LC-MS/MS and GC-MS at the Ghana Standard Authority in Accra from December 2017 to April 2018.

MERITORIOUS AWARDS

Dr. Emmanuel Kaboja Magna has received several meritorious awards and recognitions for his academic and professional achievements. In 2000, he was awarded the Distinguished Award for being the 3rd Year Best Mathematics Student at St. Mary’s Seminary Secondary School in Lolobi, Ghana. He has also been actively involved in outreach and community service. In 2023, he earned a Certificate of Excellence as the 1st Runner-up for a poster presentation at the FDA Scientific Forum, where he presented on the risk assessment of antibiotics in cultured Nile tilapia at Tema Roundabout. Additionally, he served as a panel discussant at the 2023 National Fish Festival on promoting safe fish consumption, as well as at the 2023 National Budget Dialogue on Agro-Based Policy Interventions focusing on Fisheries and Aquaculture. Dr. Magna has contributed to the review of manuscripts for peer-reviewed journals such as Food Chemistry Advances, Water, Air, & Soil Pollution, and Heliyon. His co-supervision of student dissertations includes work on the physicochemical and heavy metals analysis of the Birim River impacted by illegal small-scale mining, completed by Cecelia Asimah at the University for Development Studies in 2023.

Research Project

Dr. Emmanuel Kaboja Magna is currently involved in several research projects, including assessing the impact of environmental change on freshwater species in River Oti, studying algal dynamics in freshwater ecosystems in the Saboba districts, and conducting a comparative analysis of the nutritional composition of different fish species cultured in Ghana, all under the CSIR-WRI, Ghana. His coursework and research modules cover a wide range of topics, including coastal ecology, freshwater ecology, aquatic biology, aquaculture, biodiversity and conservation, fish stock assessment, coastal hydrology, marine biogeochemistry, environmental management, and coastal management, with a particular focus on community aspects. He has also studied advanced quantitative research methods, emerging environmental issues for the 21st century, coastal ecosystems of West Africa, and the applications of remote sensing and GIS to fisheries and marine science. Dr. Magna is affiliated with the Ghana Chemical Society (GCS) since 2017 and was a member of the Ghana National Association of Teachers (GNAT) from 2009 to 2016. He holds leadership positions as the Deputy Secretary of the CSIR-Research Staff Association of Ghana since November 2023 and was the President of the St. Mary’s Old Boys Association (UG Charter) from September 2006 to May 2007.

Publications

Ling Mei | Cognitive Science | Best Researcher Award

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Dr. Ling Mei | Cognitive Science | Best Researcher Award

Doctorate at Wuhan University of Science and Technology, China

Dr. Ling Mei is an accomplished researcher in artificial intelligence and cognitive science, with a robust academic and professional background. He holds a Ph.D. in Engineering from Sun Yat-sen University, one of China’s top universities, and completed a prestigious visiting scholar program at the University of British Columbia (UBC). Currently serving as a tenured faculty and master’s supervisor, Dr. Mei has published 16 papers, including 7 in SCI-indexed journals, contributed to nine books, and has three national invention patents granted. Recognized as a Provincial Research Talent of China in 2024, he work integrates advanced computational models with societal needs, such as urban planning and public safety. Dr. Mei has collaborated internationally with top-tier institutions like UBC and Carnegie Mellon University, cementing he reputation as a leader in he field.

Profile

Google Scholar

Orcid

Education 🎓

Dr. Mei earned he Ph.D. in Engineering from Sun Yat-sen University in 2021, a prestigious institution ranked among China’s top 10 universities. He academic journey also includes a year-long visiting scholar program at the Department of Computer Science, UBC, as part of the National Outstanding Young Researchers Program. This international exposure provided he with cutting-edge knowledge and interdisciplinary skills, enabling he to excel in artificial intelligence and cognitive science.

Work Experience 💼

Currently, Dr. Mei is a tenured faculty member and master’s supervisor at a leading Chinese university. He experience includes overseeing multiple research projects, consulting on seven industry-sponsored projects, and serving as a reviewer for the IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY. He has also been instrumental in fostering international collaborations with institutions like UBC and CMU, contributing to impactful research publications and patents.

Awards and Honors

In 2024, Dr. Mei was recognized as a Provincial Research Talent of China, highlighting he exceptional contributions to science and technology. He has also earned accolades through he impactful patents and high-quality publications.

Research Interests

Dr. Mei’s research focuses on artificial intelligence, pedestrian trajectory prediction, and public safety strategies. He innovations include the LSN-GTDA framework, which integrates behavioral and stochastic factors for better uncertainty management. He interdisciplinary approach bridges cognitive science, computational models, and societal applications, ensuring he work’s relevance and impact.

Research Skills

Dr. Mei possesses advanced skills in AI modeling, thermal diffusion processes, and signal and system theory. He expertise includes patent development, SCI journal publications, and interdisciplinary collaborations. He is adept at integrating computational techniques with practical applications, as seen in he trajectory prediction research.

📚 Publications

Crowd Density Estimation via Global Crowd Collectiveness Metric

  • Journal: Drones
  • Date: 2024-10-28
  • DOI: 10.3390/drones8110616
  • Contributors: Ling Mei, Mingyu Yu, Lvxiang Jia, Mingyu Fu

More Quickly-RRT: Improved Quick Rapidly-Exploring Random Tree Star Algorithm Based on Optimized Sampling Point with Better Initial Solution and Convergence Rate*

  • Journal: Engineering Applications of Artificial Intelligence
  • Date: 2024-07
  • DOI: 10.1016/j.engappai.2024.108246
  • Contributors: Xining Cui, Caiqi Wang, Yi Xiong, Ling Mei, Shiqian Wu

Learning Domain-Adaptive Landmark Detection-Based Self-Supervised Video Synchronization for Remote Sensing Panorama

  • Journal: Remote Sensing
  • Date: 2023-02-09
  • DOI: 10.3390/rs15040953
  • Contributors: Ling Mei, Yizhuo He, Farnoosh Fishani, Yaowen Yu, Lijun Zhang, Helge Rhodin

Illumination-Invariance Optical Flow Estimation Using Weighted Regularization Transform

  • Journal: IEEE Transactions on Circuits and Systems for Video Technology
  • Date: 2020-02
  • DOI: 10.1109/TCSVT.2019.2890861
  • Contributors: Ling Mei, Jianhuang Lai, Xiaohua Xie, Junyong Zhu, Jun Chen

Feature Visualization Based Stacked Convolutional Neural Network for Human Body Detection in a Depth Image

  • Type: Book Chapter
  • Year: 2018
  • DOI: 10.1007/978-3-030-03335-4_8
  • Contributors: Xiao Liu, Ling Mei, Dakun Yang, Jianhuang Lai, Xiaohua Xie

Conclusion 

Dr. Ling Mei is a strong contender for the Best Researcher Award due to he robust academic background, impactful research, and significant contributions to AI and cognitive science. To further enhance he candidacy, increasing citation influence and emphasizing community impact would solidify he position as an exemplary researcher deserving of recognition. 🌟