Maksym Koghut | Computer Science and Artificial Intelligence | United Kingdom

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Dr. Maksym Koghut | Computer Science and Artificial Intelligence | United Kingdom

Lecturer at Manchester Metropolitan University, United Kingdom

Dr. Maksym Koghut is an accomplished academic and researcher at Manchester Metropolitan University Business School, UK, with a robust interdisciplinary background spanning management, engineering, and financial sciences. He holds a PhD in Management from the University of Kent and has taught at several leading UK institutions, delivering modules in digital transformation, blockchain, strategy, and innovation. His research focuses on the strategic implications of digital technologies, inter-organisational trust, and AI in business contexts, with publications in high-quality journals and presentations at prominent international conferences. In addition to his academic credentials, Dr. Koghut brings substantial industry experience through leadership roles in multiple startups across the UK and Ukraine. He is a Fellow of the Higher Education Academy and has been recognized with several academic and teaching awards, reflecting his excellence in both research and pedagogy.

Professional Profile 

🎓 Education of Dr. Maksym Koghut

Dr. Maksym Koghut has pursued a dynamic and interdisciplinary educational journey across the UK and Ukraine. He earned his PhD in Management from the University of Kent (2018–2021), where he developed a strong foundation in strategic management and digital transformation. Prior to that, he completed a BA (Hons) in Business Information Management at the University of Huddersfield (2014–2017), and a BA (Hons) in Financial Management from the Inter-Regional Academy of Personnel Management, Ukraine (2010–2012), highlighting his grounding in both information systems and finance. His academic path began with a BEng (Hons) in Mechanical Engineering from Cherkassy Engineering and Technological Institute, Ukraine (1995–2000), demonstrating a solid technical and analytical base. This unique combination of disciplines enhances his expertise in digital business, innovation, and organizational strategy.

💼 Professional Experience of Dr. Maksym Koghut

Dr. Maksym Koghut brings a wealth of professional experience that bridges academia and industry. He is currently a Lecturer at Manchester Metropolitan University Business School, where he leads and teaches postgraduate and degree apprenticeship modules focused on blockchain, digital transformation, and Industry 4.0. His previous academic roles include lecturing positions at Coventry University London, the University of Kent, and the University of Huddersfield, where he developed and led modules in strategic management, digital information systems, innovation, and entrepreneurship. Beyond academia, Dr. Koghut has a strong entrepreneurial background, having founded and directed several businesses in the UK and Ukraine, including Script Software Ltd (a robotics software company), MotorHood Platform Ltd, and other ventures in automotive services, photography, and industrial equipment. This dual experience in research and real-world business operations uniquely positions him as a thought leader in digital enterprise and innovation.

🔬 Research Interests of Dr. Maksym Koghut

Dr. Maksym Koghut’s research interests lie at the intersection of digital transformation and strategic management in modern business environments. He focuses on the strategic implications of emerging technologies such as blockchain, artificial intelligence, and augmented/extended reality (XR), especially in the context of inter-organisational relationships and digital enterprises. His work explores how social capital, trust, and innovation evolve in digitally networked ecosystems, offering insights into how organisations adapt and thrive amid rapid technological change. Dr. Koghut also investigates consumer behavior in digital settings, including mobile payment discontinuance and AI-generated advertising. His research is both conceptually grounded and practically relevant, contributing to academic scholarship and informing industry practices in the digital age.

🏆 Awards and Honors of Dr. Maksym Koghut

Dr. Maksym Koghut has been recognized multiple times for his outstanding contributions to both research and teaching. He received the “Above & Beyond Award” twice from Kent Business School in 2022 for excellence in teaching at both undergraduate and postgraduate levels. His academic journey has been supported by prestigious scholarships, including the Vice Chancellor’s Research Scholarship from the University of Kent in 2018 and the Vice Chancellor’s Scholarship for PhD Studies from Huddersfield Business School in 2017. Additionally, he was awarded the Strategic Planning Society Prize for being the Best Student in Strategy at Huddersfield Business School in 2017. These honors highlight Dr. Koghut’s consistent excellence, dedication, and impact in the academic and professional communities.

🏁 Conclusion

Dr. Maksym Koghut is a compelling and highly suitable candidate for the Best Researcher Award. He brings together a rich combination of academic excellence, cutting-edge research, teaching innovation, and industry engagement. His interdisciplinary expertise and consistent scholarly output in contemporary digital business themes position him as a thought leader in the digital transformation domain.

📚 Publications Top Noted

  1. Title: A Blockchain-based Inter-organisational Relationships: Social and Innovation Implications
    Authors: Maksym Koghut, Omar Al-Tabbaa, Soo Hee Lee, Martin Meyer
    Year: 2021
    Citation: Academy of Management Proceedings, 2021-08
  2. Title: A Blockchain-based Inter-organisational Relationships: Social and Innovation Implications
    Authors: Maksym Koghut, Omar Al-Tabbaa, Soo Hee Lee, Martin Meyer
    Year: 2021
    Citation: Academy of Management Proceedings, 2021-08
  3. Title: The Effects of Autonomous Contracting on Inter-organisational Relationships: A Process Model of Trust, Social Capital and Value Co-creation
    Authors: Maksym Koghut, Omar Al-Tabbaa, Soo Hee Lee, Martin Meyer
    Year: 2020
    Citation: British Academy of Management Annual Conference, 2020-09-04
  4. Title: The Blockchain-Trust Nexus: A New Era for Inter-organizational Trust Meaning and Formation
    Authors: Maksym Koghut, Omar Al-Tabbaa, Martin Meyer
    Year: 2019
    Citation: Academy of Management Proceedings, 2019-08
  5. Title: Modelling Decentralised Collaboration Between Engineering Teams: A Blockchain-based Solution
    Authors: Maksym Koghut, John Makokha
    Year: 2018
    Citation: VI International Scientific and Technical Conference, 2018-09-01

Prof. Shulan Hsieh | Cognitive Science | Best Researcher Award

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Prof. Shulan Hsieh | Cognitive Science | Best Researcher Award

Prof. Shulan Hsieh , Cognitive Science, National Cheng Kung University , Taiwan

Prof. Shulan Hsieh is a distinguished Chair Professor at National Cheng Kung University (NCKU), Taiwan, with a remarkable career in cognitive neuroscience and psychology. She earned her D.Phil. in Experimental Psychology from the University of Oxford in 1993. She began her academic journey at National Chung Cheng University, becoming Full Professor by 1999 and later serving as Department Chair and Dean (2003–2009).  she joined NCKU, where she held key academic roles in the Institute of Allied Health Sciences, Department of Psychology, and Department of Public Health. She also served as Director of the Institute of Allied Health Sciences (2010–2013) and Chair of the Department of Psychology (2015–2018). Prof. Hsieh has made major contributions to understanding cognitive flexibility, aging, and brain resilience. Her editorial leadership includes roles as Editor-in-Chief and Associate Editor in leading journals. With over 100 publications, she continues to lead interdisciplinary research and international collaborations.

Professional Profile:

Orcid

Scopus 

Education 🎓

Prof. Shulan Hsieh earned her D.Phil. in Experimental Psychology from the University of Oxford in 1993, where she developed a strong foundation in cognitive science and behavioral neuroscience. Her doctoral training provided expertise in experimental design, neuropsychological testing, and attentional processes. Prior to that, she completed undergraduate and postgraduate education in psychology in Taiwan, establishing her interest in the intersection of cognitive performance and neural mechanisms. This solid academic training enabled her to develop rigorous empirical approaches and establish herself early as a scholar in cognitive psychology. Her Oxford education also laid the groundwork for her international collaborations and editorial roles, and her ability to build comprehensive cross-cultural research paradigms. Her educational path reflects a blend of Western scientific rigor and Eastern academic dedication, supporting her mission to enhance brain health and resilience through research, mentoring, and interdisciplinary training in Taiwan and globally.

Experience 💼

Prof. Hsieh began her academic career at National Chung Cheng University, Taiwan, where she became Full Professor in 1999. She served as Department Chair and Dean (2003–2009), significantly influencing curriculum and faculty development. In 2009, she transitioned to National Cheng Kung University (NCKU), taking on roles in the Institute of Allied Health Sciences, Department of Psychology, and Department of Public Health. She served as Director of the Institute of Allied Health Sciences (2010–2013) and later as Chair of the Department of Psychology (2015–2018). Her leadership across departments reflects her interdisciplinary strengths in cognitive science, public health, and psychology. She has supervised numerous Ph.D. and graduate students, led national research initiatives, and managed international collaborations with cognitive scientists in Europe and Israel. With decades of service, she remains an active figure in Taiwan’s academic and research policy landscape, contributing significantly to the global cognitive neuroscience community.

Awards and Honors 🏆

Prof. Shulan Hsieh has received widespread recognition for her scientific contributions and academic leadership. She is a Fellow of the Association for Psychological Science (APS) since 2012, and a Fellow of the Psychonomic Society since 1998—both honors reserved for researchers with outstanding contributions to psychological science. She is a Member of the American Psychological Association (APA) since 2021 and a Member of the Society for Neuroscience (SFN) since 2018, reflecting her active involvement in global neuroscience and psychology communities. She is also a Member of the Association for the Scientific Study of Consciousness since 2008. These memberships underscore her international reputation and sustained contributions to the scientific study of cognition, consciousness, and aging. Through her editorial roles and participation in research councils and academic reviews, she has significantly influenced research funding, policy, and graduate education. Her work continues to shape the future of cognitive neuroscience in Asia and beyond.

Research Focus 🔬

Prof. Hsieh’s research centers on cognitive science, brain resilience, and aging across the adult lifespan. She explores how executive functions, particularly task-switching and cognitive flexibility, change with age, and how these changes relate to brain organization, especially in the prefrontal cortex. Using both behavioral paradigms and neuroimaging techniques, she investigates mechanisms underlying age-related cognitive decline and strategies for enhancing brain resilience. She leads several multi-year projects funded by Taiwan’s National Science and Technology Council (NSTC), including longitudinal studies profiling cognitive resilience and the development of task-switching paradigms validated across cultures. Her interdisciplinary approach spans psychology, neuroscience, public health, and allied health sciences. She collaborates internationally to translate findings into tools for cognitive health assessment and intervention. Her work contributes to a deeper understanding of healthy aging and informs both clinical applications and educational practices for lifelong cognitive enhancement.

Publications 📚

1. Age-related Electrophysical Correlates of Cross-modal Attention Switching

2. Alternation of Psychological Resilience May Moderate Mentalization Toward Mental Health Conditions from Macro- and Microstructure Aspects

3. Age Prediction Using Resting-State Functional MRI

4. Age Differences in the Functional Organization of the Prefrontal Cortex: Analyses of Competing Hypotheses

5. The Mediating Role of Brain Structural Imaging Markers in Connecting Adverse Childhood Experiences and Psychological Resilience

6. DNA Methylation Signature Aberration as Potential Biomarkers in Treatment-Resistant Schizophrenia: Constructing a Methylation Risk Score Using a Machine Learning Method

7. Age Differences of the Hierarchical Cognitive Control and the Frontal Rostro–Caudal Functional Brain Activation

8. Age-related Post-error Slowing and Stimulus Repetition Effect in Motor Inhibition During a Stop-signal Task

9. Adverse Childhood Experiences Are Associated with Reduced Psychological Resilience in Youth: A Systematic Review and Meta-Analysis

10. Brain Structural-Behavioral Correlates Underlying Grooved Pegboard Test Performance Across Lifespan

 

 

 

 

Yue Wu | Machine Learning | Best Researcher Award

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Yue Wu | Machine Learning | Best Researcher Award

Assist. Prof. Dr Yue Wu, Hangzhou Dian, China

Assist. Prof. Dr. Yue Wu is a promising young academician whose work bridges the gap between automation, machine learning, and electronic design automation. Currently serving as an Assistant Professor at the School of Electronics and Information Engineering, Hangzhou Dianzi University, China, he exemplifies research excellence through his interdisciplinary expertise. He earned his Ph.D. from Zhejiang University in Aeronautics and Astronautics and a B.S. from Wuhan University of Technology in Automation. His scholarly interests focus on logic synthesis, physical design, and intelligent prediction algorithms using graph neural networks. Despite his early career stage, Dr. Wu has demonstrated impactful contributions to both academia and industry-relevant applications. His recent publication on pre-routing slack prediction using graph attention networks stands out as a novel solution in the realm of EDA. With a strong academic foundation and active research output, Dr. Wu is a fitting nominee for the Best Researcher Award, representing the next generation of innovation in AI-driven engineering.

Publication Profile

Orcid

Education

Dr. Yue Wu has a solid educational foundation in engineering and automation. He earned his Bachelor of Science (B.S.) in Automation from the Wuhan University of Technology in 2018. There, he developed a robust understanding of control systems, signal processing, and computational modeling. Pursuing his academic passion, he undertook doctoral studies at the School of Aeronautics and Astronautics, Zhejiang University, one of China’s premier research institutions. He completed his Ph.D. in 2023, focusing on interdisciplinary topics combining aeronautical engineering, data science, and intelligent systems. His doctoral work incorporated advanced machine learning techniques and their applications in hardware-aware environments, preparing him to lead novel research at the intersection of automation and electronics. This strong academic background equips him with the theoretical depth and practical experience essential for future-forward research in intelligent systems and electronic design automation.

Experience

Dr. Yue Wu is currently serving as an Assistant Professor at the School of Electronics and Information Engineering, Hangzhou Dianzi University, since 2023. Despite being in the early phase of his academic career, he has demonstrated exceptional scholarly promise through teaching, mentorship, and high-impact research. His role involves designing and delivering advanced courses on machine learning, logic circuits, and digital system design while actively supervising undergraduate and graduate research projects. He collaborates with interdisciplinary teams, focusing on the integration of machine learning techniques into physical design and logic synthesis processes, bridging hardware and AI innovations. Prior to this, he was involved in multiple research projects at Zhejiang University during his Ph.D., contributing to algorithm development and experimental validation of graph-based learning techniques. Dr. Wu’s combined expertise in automation, EDA tools, and machine learning positions him as a rising leader in academic research and technological advancement.

Awards and Honors

As a rising scholar, Dr. Yue Wu has been recognized for his academic achievements and research contributions. While specific institutional or national awards are yet to be recorded in the public domain, his selection as a faculty member at Hangzhou Dianzi University, known for its emphasis on electronic and information technology research, is a testament to his academic caliber. His recent first-author publication in the peer-reviewed journal “Automation” (2025) highlights his research excellence and innovation in the application of graph attention networks to pre-routing slack prediction, a complex problem in VLSI design. Additionally, his collaborative projects during his Ph.D. at Zhejiang University received internal recognition and contributed to multiple research grants. Dr. Wu’s research profile is steadily growing, and he is well on the path toward future accolades at the national and international levels as he continues to publish and lead in cutting-edge interdisciplinary domains.

Research Focus

Dr. Yue Wu’s research focuses on the intersection of machine learning and electronic design automation (EDA). His primary interest lies in developing intelligent systems that enhance the physical design and logic synthesis processes used in integrated circuit (IC) design. By leveraging advanced models like graph neural networks (GNNs) and attention-based architectures, Dr. Wu aims to address critical challenges such as slack prediction, timing analysis, and routing optimization. His expertise also extends to hardware-aware machine learning, wherein algorithmic efficiency is optimized for real-world applications in chip manufacturing. His recent work—“Pre-Routing Slack Prediction Based on Graph Attention Network”—demonstrates his ability to combine theoretical AI models with practical EDA problems. By pushing the boundaries of design automation through AI integration, Dr. Wu contributes to faster, smarter, and more power-efficient chip design—critical for the next generation of computing devices. His vision is to make intelligent design automation a core component of future electronics engineering.

Publication Top Notes

Pre-Routing Slack Prediction Based on Graph Attention Network

 

Shuai Cao | Computer Science and Artificial Intelligence | Best Researcher Award

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Shuai Cao | Computer Science and Artificial Intelligence | Best Researcher Award

Dr Shuai Cao, School of Automation, Wuhan University of Technology, China

Dr. Shuai Cao is a dynamic researcher in the field of Computational Intelligence, currently pursuing graduate studies at Kunming University of Science and Technology and engaging in joint research at the Guangdong Academy of Sciences. With a focus on enhancing meta-heuristic algorithms, Dr. Cao has contributed significantly to engineering optimization, especially in AGV path planning and offset printing machine design. He is the mind behind the innovative Piranha Foraging Optimization Algorithm (PFOA) and co-author of several impactful SCI/EI publications. His expertise in algorithm improvement, machine learning, and pattern recognition is reflected through funded projects and hands-on roles in top research institutions like the South China Intelligent Robot Innovation Institute. With a remarkable blend of theoretical insight and practical application, Dr. Cao is a promising candidate for the Best Researcher Award, embodying academic rigor and real-world impact.

Publication Profile 

Orcid

Education

Dr. Shuai Cao’s academic journey began at Baotou Rare Earth High-tech No. 1 High School (2014–2017), where he laid a strong foundation in the sciences. He pursued his undergraduate degree in Mechanical and Electronic Engineering at Chongqing University of Humanities, Science and Technology (2017–2021), gaining critical insights into systems design and robotics. Since 2021, he has been a postgraduate student in Electronic Information at Kunming University of Science and Technology, further sharpening his expertise in computational theory and algorithmic systems. Complementing his studies, Dr. Cao has been engaged in a joint training program at the Intelligent Manufacturing Institute of the Guangdong Academy of Sciences since 2022. His coursework includes meta-heuristic algorithms, machine learning, digital signal processing, and pattern recognition, all of which feed directly into his research in Computational Intelligence and engineering optimization. His interdisciplinary background empowers him to tackle complex problems with innovative solutions.

Experience

Dr. Shuai Cao has held impactful roles in prestigious research institutions. From May 2022 to July 2023, he worked at the Intelligent Manufacturing Institute of the Guangdong Academy of Sciences, where he conducted advanced research on AGV handling robots. This included applying improved intelligent algorithms for path planning and optimization scheduling—work closely aligned with his master’s thesis. Since July 2023, he has been with the South China Intelligent Robot Innovation Institute, applying swarm intelligence methods to optimize the structure of high-speed multi-color offset printing machines. Dr. Cao’s work integrates theoretical research with industrial application, setting a benchmark for practical relevance. His involvement in key science and innovation projects also reflects his growing leadership in the field. From optimization algorithms to real-world robotic systems, Dr. Cao’s hands-on approach is shaping the future of intelligent manufacturing.

Awards and Honors

Dr. Shuai Cao has earned distinguished recognition in both academic and research circles for his innovative contributions to engineering optimization. As a lead researcher on multiple government-funded projects—including “Research and Application of Intelligent Scheduling of Mobile Collaborative Robot Clusters for Intelligent Manufacturing” (Project Code: 2130218003022) and the “Foshan Science and Technology Innovation Team Project” (Project Code: FS0AA-KJ919-4402-0060)—he has demonstrated expertise in bridging theory with practical industrial solutions. His pioneering research has been published in high-impact SCI and EI journals and conferences, such as IEEE ACCESS and the International Conference on Robotics and Automation Engineering (ICRAE). A highlight of his work is the development of the Piranha Foraging Optimization Algorithm (PFOA), which has garnered considerable attention in the optimization community for its novelty and effectiveness. Dr. Cao’s sustained dedication to cutting-edge innovation, along with his leadership in collaborative, cross-disciplinary projects, makes him a compelling nominee for the Best Researcher Award.

Research Focus

Dr. Shuai Cao’s research is centered on Computational Intelligence, specifically the improvement and engineering application of swarm intelligence algorithms. His work addresses key challenges in traditional optimization methods, such as premature convergence, low population diversity, and slow optimization speeds. He has successfully designed algorithms that overcome these limitations, notably the Piranha Foraging Optimization Algorithm (PFOA). His research extends to practical applications like automated guided vehicle (AGV) path planning, scheduling in smart factories, and mechanical structure optimization for high-speed printing systems. Through interdisciplinary methods, he combines machine learning, pattern recognition, and digital signal processing to bring theoretical advancements into real-world manufacturing challenges. With a clear aim of enhancing intelligent manufacturing systems, his research contributes to both academic knowledge and industrial innovation. His growing body of work reflects originality, technical rigor, and a strong alignment with modern engineering demands.

Publication Top Notes

Research on the Design and Application of Multi-Port Energy Routers