Sa Zhou | Human Machine Interface | Best Researcher Award

Published on by Computer Vision Awards

Dr. Sa Zhou | Human Machine Interface | Best Researcher Award

Postdoc at Stanford University | United States

Dr. Sa Zhou is a dedicated researcher in the fields of biomedical engineering, neuroscience, and psychiatry, currently working as a postdoctoral scholar at Stanford University. His research emphasizes multimodal neuroimaging, brain-machine interfaces, stroke rehabilitation, cognitive enhancement, and neuromodulation, bridging engineering and medicine to improve human health outcomes. He has published extensively in internationally recognized journals and contributed to conferences with global visibility. His innovative contributions extend beyond academic research into patents, translational projects, and clinical applications, demonstrating his ability to turn theory into practice. Through his involvement in teaching, mentoring, and editorial activities, he has shown leadership and commitment to advancing science and supporting the next generation of researchers. His global collaborations across Asia and the United States reflect his adaptability and international impact. With a strong foundation and innovative approach, he continues to make meaningful contributions with high potential for future leadership in research and society.

Professional Profiles 

Google Scholar | Scopus Profile | ORCID Profile 

Education

Dr. Sa Zhou pursued his higher education with a strong focus on engineering and biomedical sciences, which provided him with a multidisciplinary foundation for his research career. He earned his Bachelor and Master of Philosophy degrees in Electrical Engineering from Yanshan University, where he gained in-depth knowledge of signal processing, system development, and computational approaches to neural data. He then advanced his academic journey by completing his PhD in Biomedical Engineering at The Hong Kong Polytechnic University, where he developed expertise in neuroengineering, multimodal neuroimaging, and stroke rehabilitation. His doctoral research explored neural reorganization in sensorimotor impairments and recovery, involving systematic neurological evaluations, electrophysiological analyses, and clinical trials. This educational background not only honed his analytical and technical skills but also laid the groundwork for his interdisciplinary approach, bridging engineering principles with neuroscience and clinical applications. His academic training has shaped his ability to conduct impactful research at the interface of technology and medicine.

Professional Experience

Dr. Sa Zhou’s professional experience reflects a blend of academic research, teaching, and applied innovation in biomedical engineering and neuroscience. He is currently a postdoctoral scholar at Stanford University in the Department of Psychiatry and Behavioral Sciences, contributing to projects focused on personalized cognitive enhancement and digital interventions for aging-related disorders. Prior to this role, he worked extensively at The Hong Kong Polytechnic University, where he participated in pioneering projects on stroke rehabilitation, neuromodulation, and brain-machine interfaces. His experience also includes collaboration on international research initiatives that integrate engineering, neuroscience, and clinical practice, leading to high-impact publications and translational applications. Alongside research, he has actively contributed to education as a teaching assistant in neuroengineering, applied electrophysiology, and digital signal processing, mentoring undergraduate and postgraduate students. His diverse professional background demonstrates his ability to conduct innovative research, translate findings into practical solutions, and inspire future researchers through academic leadership.

Research Interest

Dr. Sa Zhou’s research interests span a wide spectrum of neuroscience, engineering, and clinical applications, with a particular emphasis on developing innovative technologies for human health and rehabilitation. His work focuses on multimodal neuroimaging techniques, including structural and functional MRI, DTI, and EEG, combined with advanced signal processing and machine learning approaches to understand brain networks. He is also deeply engaged in brain-machine interfaces, stroke rehabilitation, neuromotor interfaces, and robotic systems that enhance motor recovery and cognitive function. His interests extend to non-pharmacological interventions for preclinical Alzheimer’s disease and mild cognitive impairments, reflecting his commitment to addressing aging-related neurological disorders. He also explores neuromodulation methods, including electrical and ultrasound stimulation, to optimize therapeutic outcomes. These diverse interests demonstrate his interdisciplinary approach, integrating engineering innovations with clinical neuroscience to create personalized solutions. His research aims not only to advance scientific knowledge but also to deliver real-world impact in improving patient care and well-being.

Award and Honor

Dr. Sa Zhou has been recognized with numerous awards and honors that highlight his academic excellence, research achievements, and leadership potential. He has received prestigious fellowships, including support from international neuroscience and brain aging associations, acknowledging his contributions to advancing cognitive enhancement research. During his doctoral studies, he was awarded the PolyU Research Postgraduate Scholarship for outstanding performance, along with national-level scholarships that placed him among the top-performing postgraduates in China. He has also earned multiple competitive awards in research and innovation competitions, such as the Hong Kong Medical and Healthcare Device Industries Association Student Research Award and the Champion Award in the Three-Minute Thesis Competition. His teaching excellence was recognized with Best Teaching Assistant Awards, demonstrating his impact in both research and education. These accolades reflect his consistent pursuit of excellence, his ability to compete at international levels, and his dedication to advancing science while inspiring peers and students.

Research Skill

Dr. Sa Zhou possesses a wide range of research skills that integrate advanced engineering techniques with clinical neuroscience applications. His expertise includes real-time robotic control, rehabilitation system design, and multimodal neuroimaging analysis, enabling him to develop and test innovative technologies for stroke rehabilitation and cognitive enhancement. He is proficient in conducting clinical trials with stroke patients, performing neuroimaging scans such as fMRI, DTI, and structural MRI, and analyzing electrophysiological signals including EEG, EMG, and LFP. His skillset also extends to neuromodulation experiments using transcranial ultrasound stimulation and neuromuscular electrical stimulation, combined with advanced kinematic signal recording systems. In addition, he has strong programming and analytical abilities in machine learning, Matlab, Python, and C/C++, which support his work in neural decoding and brain network analyses. These skills, coupled with experience in mentoring, peer review, and system development, demonstrate his ability to design, implement, and translate research into impactful clinical and technological outcomes.

Publications Top Notes

Title: Pathway-specific cortico-muscular coherence in proximal-to-distal compensation during fine motor control of finger extension after stroke
Year: 2021
Citation: 32

Title: Corticomuscular integrated representation of voluntary motor effort in robotic control for wrist-hand rehabilitation after stroke
Year: 2022
Citation: 24

Title: Effect of pulsed transcranial ultrasound stimulation at different number of tone-burst on cortico-muscular coupling
Year: 2018
Citation: 20

Title: Optimization of relative parameters in transfer entropy estimation and application to corticomuscular coupling in humans
Year: 2018
Citation: 18

Title: Low-intensity pulsed ultrasound modulates multi-frequency band phase synchronization between LFPs and EMG in mice
Year: 2019
Citation: 17

Title: Impairments of cortico-cortical connectivity in fine tactile sensation after stroke
Year: 2021
Citation: 15

Title: Medical image segmentation using deep semantic-based methods: A review of techniques, applications and emerging trends
Year: 2022
Citation: 5

Title: Automatic theranostics for long-term neurorehabilitation after stroke
Year: 2023
Citation: 4

Title: Estimation of corticomuscular coherence following stroke patients
Year: 2017
Citation: 4

Title: Decoding Visual Experience and Mapping Semantics through Whole-Brain Analysis Using fMRI Foundation Models
Year: 2024
Citation: 1

Title: Personalized cognitive enhancement for older adults: An aging-friendly closed-loop human-machine interface framework
Year: 2025

Title: Relationships between neuropsychiatric symptoms, subtypes of astrocyte activities, and brain pathologies in Alzheimer’s disease and Parkinson’s disease
Year: 2025

Title: Neural Correlates of Dual‐Functional Local Dynamic Stability in Older Adults
Year: 2024

Title: Profiles of brain topology for dual-functional stability in old age
Year: 2024

Title: Neuromuscular networking connectivity in sensorimotor impairments after stroke
Year: 2023

Conclusion

Dr. Sa Zhou is highly deserving of the Best Researcher Award for his outstanding contributions at the intersection of biomedical engineering, neuroscience, and psychiatry, with impactful research in neuroimaging, brain-machine interfaces, stroke rehabilitation, and cognitive enhancement for aging populations. His work has advanced both theoretical understanding and practical applications, supported by high-quality publications, patents, and international collaborations that bridge engineering and medicine. Beyond research, his leadership in teaching, mentoring, and reviewing reflects a strong commitment to the scientific community and knowledge dissemination. With his growing expertise, innovative approaches, and dedication to addressing critical health challenges, Dr. Zhou shows great promise for future research breakthroughs and leadership in shaping the fields of neuroengineering and translational neuroscience.

Jong-Hyun Kim | Applied Visual Computing | Best Researcher Award

Published on by Computer Vision Awards

Prof. Jong-Hyun Kim | Applied Visual Computing | Best Researcher Award

Associate Professor at Inha University, South Korea

Prof. Jong-Hyun Kim is an Associate Professor at the College of Software and Convergence, Department of Artificial Intelligence, Design Technology at Inha University, with a joint appointment at the Graduate School of Electrical and Computer Engineering. He is a distinguished researcher with expertise spanning computer graphics, visual effects, physically based simulation, physics engines, artificial intelligence, VR/AR, geometry processing, and GPU optimization. His career bridges academia and industry, having led and participated in numerous national research projects and industry collaborations in areas such as digital twin technology, immersive simulation systems, and AI convergence. With an impressive record of award-winning publications in reputed conferences and journals indexed in IEEE and Scopus, he has contributed significantly to advancing emerging technologies. His leadership in collaborative initiatives and dedication to innovative research continue to strengthen his impact on both scientific communities and practical applications.

Professional Profile 

ORCID Profile

Education

Prof. Jong-Hyun Kim completed his Ph.D. in Computer Science and Engineering from Korea University, following his master’s degree and bachelor’s degree in the same field from Korea University and Sejong University, respectively. His academic journey reflects a strong foundation in both theoretical and applied aspects of computer science, equipping him with advanced skills in simulation, visualization, and artificial intelligence. His studies covered a broad spectrum of technical disciplines, from physics-based modeling and geometry processing to interactive graphics and human-computer interaction. The rigorous academic training at prestigious institutions provided him with the expertise to excel in interdisciplinary research and to address complex computational challenges. This solid educational background has enabled him to integrate advanced computing techniques with creative technological solutions, laying the groundwork for his influential research contributions in academia and his ability to collaborate effectively with industry partners on innovative projects.

Professional Experience

Prof. Jong-Hyun Kim currently serves as an Associate Professor at Inha University, having previously held the same position at Kangnam University. He has also served as a lecturer and teaching fellow at Korea University, contributing to the development of academic programs and mentoring students in advanced computing topics. Before his academic career, he worked extensively in the industry as a senior research engineer and research engineer at multiple companies, gaining hands-on experience in simulation technologies, visual effects, and interactive systems. His professional trajectory reflects a balance between academic scholarship and practical application, with roles that involved designing innovative solutions, leading research teams, and collaborating on both government-funded and industry-driven projects. His combined academic and industrial experience has strengthened his expertise in bridging theoretical research with real-world implementation, enhancing his ability to deliver impactful outcomes in both educational and technological domains.

Research Interest

Prof. Jong-Hyun Kim’s research interests cover a broad and interdisciplinary range of topics, including computer graphics, visual effects, physically based simulation, physics engines, and game physics. He actively explores artificial intelligence techniques for scientific visualization, geometry processing, image processing, and immersive VR/AR experiences. His work often focuses on GPU optimization to achieve real-time performance in complex simulations, enabling practical applications in gaming, virtual reality, and industrial simulations. Additionally, he is interested in human-computer interaction, particularly in developing intuitive interfaces for creative expression and realistic virtual environments. His projects integrate physics-based modeling with AI-driven approaches to address challenges in simulation accuracy, interactivity, and scalability. By combining deep technical expertise with creativity, his research aims to advance the capabilities of simulation and visualization technologies, making them more efficient, accessible, and adaptable for diverse fields ranging from entertainment and education to engineering and healthcare.

Award and Honor

Prof. Jong-Hyun Kim has received numerous awards and honors recognizing his excellence in research, innovation, and academic contributions. His accolades include multiple Best Paper Awards from prestigious conferences such as those organized by the Korea Society of Computer and Information and the Korean Association of Data Science, acknowledging his groundbreaking work in simulations, VR frameworks, AI-driven modeling, and GPU optimization. He has been honored by the Ministry of Science and ICT and the Korean Ministry of Education for his creative and impactful research ideas. His achievements extend beyond academia, with awards recognizing his leadership in industry-academic cooperation and excellence in teaching. These recognitions reflect his sustained contributions to advancing cutting-edge technologies, fostering collaboration between academia and industry, and mentoring future innovators. His consistent recognition at national and professional levels underscores his influence in both research and education, and his ongoing commitment to delivering impactful technological advancements.

Research Skill

Prof. Jong-Hyun Kim possesses advanced research skills in multiple technical domains, including physically based simulation, visual effects, GPU optimization, and complex animation systems. He is proficient in designing real-time interactive environments, implementing physics engines, and integrating artificial intelligence into simulation and visualization frameworks. His expertise includes scientific visualization, geometry processing, VR/AR development, and image processing, enabling him to create innovative solutions that merge creativity with computational precision. He has extensive experience managing large-scale research projects funded by national agencies and industry partners, demonstrating strong project management, team leadership, and cross-disciplinary collaboration skills. His technical abilities are complemented by his capacity to translate theoretical models into practical applications across entertainment, engineering, and scientific research. By combining analytical thinking, problem-solving, and creative design, he continues to push the boundaries of simulation and visualization technologies, contributing significantly to both academic advancements and industry innovation.

Publications Top Notes

Title: A Geometric Approach to Efficient Modeling and Rendering of Opaque Ice With Directional Air Bubbles
Authors: Jong-Hyun Kim
Year: 2025

Title: Advanced GPU Techniques for Dynamic Remeshing and Self-Collision Handling in Real-Time Cloth Tearing
Authors: Jong-Hyun Kim; Jung Lee
Year: 2025

Title: Improved Air Mesh Refinement for Accurate Strand-Solid and Self-Collision Handling
Authors: Jong-Hyun Kim
Year: 2025

Title: Neural Network-Based Projective Grid Model for Learning Representation of Surface and Wave Foams
Authors: Jong-Hyun Kim
Year: 2025

Title: Porous Models for Enhanced Representation of Saturated Curly Hairs: Simulation and Learning
Authors: Jong-Hyun Kim; Jung Lee
Year: 2025

Title: A 3D Visual Tool for Analyzing Changes in Hair Volume and Length Caused by Medications
Authors: Jong‐Hyun Kim; Jung Lee; Seungbin Kwon; Minji Jo; Yunjin Hwang; In‐Sook An
Year: 2025

Title: Numerical Dispersed Flow Simulation of Fire-Flake Particle Dynamics and Its Learning Representation
Authors: Jong-Hyun Kim; Jung Lee
Year: 2025

Title: Unified GPU Framework for Simulating Wave Turbulence, Diffusion, and Wrinkling in Fluid-Cloth Interaction
Authors: Eun Su Park; Juyong Lee; In Kyu Park; Jong-Hyun Kim
Year: 2025

Title: Scalable and Rapid Nearest Neighbor Particle Search Using Adaptive Disk Sector
Authors: Jong-Hyun Kim; Shaofeng Xu; Jung Lee
Year: 2025

Title: Depth-of-Field Region Detection and Recognition From a Single Image Using Adaptively Sampled Learning Representation
Authors: Jong-Hyun Kim; Youngbin Kim
Year: 2024

Title: Motion Generation and Analyzing the User’s Arm Muscles via Leap Motion and Its Data-Driven Representations
Authors: Jong-Hyun Kim; Jung Lee; Youngbin Kim
Year: 2024

Title: Visualization of Vector Fields from Density Data Using Moving Least Squares Based on Monte Carlo Method
Authors: Jong-Hyun Kim
Year: 2024

Title: Isoline Tracking in Particle-Based Fluids Using Level-Set Learning Representation
Authors: Jun Yeong Kim; Chang Geun Song; Jung Lee; Jong-Hyun Kim; Jong Wan Lee; Sun-Jeong Kim
Year: 2024

Title: Efficient and Stable Generation of High-Resolution Hair and Fur With ConvNet Using Adaptive Strand Geometry Images
Authors: Jong-Hyun Kim; Jung Lee
Year: 2023

Conclusion

Prof. Jong-Hyun Kim is highly deserving of the Best Researcher Award for his outstanding contributions to cutting-edge research in computer graphics, AI-driven simulation, and immersive technologies, as well as his significant role in bridging academia and industry through impactful collaborative projects. His innovative work has advanced both scientific understanding and practical applications, benefiting diverse sectors and inspiring the next generation of researchers. With a proven track record of excellence, leadership, and innovation, he holds strong potential to make even greater contributions to research and society in the future.

Qi Li | Human-Computer Interaction | Women Researcher Award

Published on by Computer Vision Awards

Prof. Qi Li | Human-Computer Interaction | Women Researcher Award

Professor at Capital Normal University, China

Professor Qi Li is a renowned scholar in psychology, currently serving as a Professor and Doctoral Supervisor at the School of Psychology, Capital Normal University, and a part-time Associate Researcher at the Chinese Academy of Sciences. He is also the Director of the Institute of Basic Psychology and Deputy Director of a Scientific Research Innovation Team. With visiting experience at Stanford University, he brings a strong global perspective. Professor Li has made pioneering contributions in the fields of cognitive neuroscience and adolescent mental health, integrating traditional psychological methods with cutting-edge technologies like EEG, brain imaging, and behavioral modeling. His research has led to the creation of impactful platforms like the Mental Health Assessment and Early Warning System and the Qihuang Angel Platform, serving over 100,000 individuals nationwide. With over 110 peer-reviewed publications and leadership in 20+ national projects, Professor Qi Li exemplifies excellence in research, innovation, and societal impact.

Professional Profile 

Education🎓

Professor Qi Li holds a robust academic background in psychology and neuroscience, which laid the foundation for his influential research career. Although specific degree details are not listed in the provided profile, his academic and research affiliations with prestigious institutions such as the Chinese Academy of Sciences and Stanford University indicate a high level of scholarly achievement and global academic engagement. His continuous progression from Assistant Researcher to Associate Researcher and ultimately to Professor and Doctoral Supervisor reflects both his academic competence and research leadership. His education has empowered him to lead interdisciplinary work that combines psychology, cognitive neuroscience, and behavioral science with practical application in education and healthcare. The depth and breadth of his academic training are also evident in his ability to mentor PhD students, spearhead large-scale national projects, and develop research-backed mental health assessment tools. His educational journey reflects a strong commitment to academic excellence and innovation.

Professional Experience📝

Professor Qi Li’s professional trajectory is marked by steady advancement and impactful leadership. He began his career in 2011 as an Assistant Researcher at the Institute of Psychology, Chinese Academy of Sciences, progressing to Associate Researcher and Doctoral Supervisor by 2014. In 2021, he joined Capital Normal University as a Professor and Director of the Institute of Basic Psychology, while maintaining part-time research responsibilities at the Chinese Academy of Sciences. Additionally, he serves as Deputy Director of a major Scientific Research Innovation Team and holds numerous committee and advisory roles across educational and psychological institutions in China. His multidisciplinary leadership spans clinical, educational, and research settings. Notably, he has developed two national platforms addressing adolescent behavior and mental health, collaborated on major government-funded R&D projects, and published extensively in international journals. His dual engagement in academic research and real-world application highlights his broad professional impact.

Research Interest🔎

Professor Qi Li’s research focuses on the neural mechanisms of cognitive control and reward, especially as they relate to adolescent behavior, internet addiction, emotional regulation, and decision-making. His work examines how cognitive and affective systems interact in developing brains, using tools such as EEG, brain imaging, behavioral experiments, and data modeling. A major focus of his research is the early warning, assessment, and correction of problem behaviors in children and adolescents. He has pioneered interdisciplinary platforms that integrate psychological theory, educational practice, and digital technology to address behavioral health challenges in schools. His studies have explored social comparison, fairness decision-making, and the brain’s response to motivation and learning contexts. Additionally, he leads projects that combine neuroscience with traditional Chinese medicine in mental health interventions. His work stands at the frontier of basic and applied psychological science, aiming to translate theoretical insights into scalable and effective behavioral interventions.

Award and Honor🏆

Although specific individual awards are not directly listed in the provided profile, Professor Qi Li’s nationally funded research projects, editorial roles, software copyrights, and leadership in high-impact platforms are indicative of substantial recognition and honor in his field. His appointment as a Visiting Scientist at Stanford University, Editorial Board Member of Frontiers, and reviewer for top-tier journals such as Neuroimage and Cerebral Cortex reflect his respected standing in the international academic community. Additionally, he holds key positions in national academic committees, such as Vice Chairman of the Traditional Chinese Medicine Nursing Committee and Expert Steering Committee for Psychological Correction in Drug Rehabilitation. The wide adoption of his mental health assessment platform in over 50 institutions nationwide showcases the trust and acknowledgment his work has earned. His sustained research funding from the National Natural Science Foundation of China and other prestigious bodies further attests to his excellence and credibility.

Research Skill🔬

Professor Qi Li possesses a comprehensive and multidisciplinary research skill set that bridges psychology, cognitive neuroscience, education, and digital health. He is adept in questionnaire design, behavioral experiment protocols, electroencephalography (EEG), functional brain imaging, and computational data modeling. These skills have enabled him to explore the intricacies of cognitive control, reward processing, emotion regulation, and adolescent behavioral patterns. His ability to analyze complex brain-behavior relationships has been instrumental in developing real-time, technology-driven assessment and correction systems. He also excels in platform development, evidenced by the large-scale deployment of his behavioral intervention platforms in schools and healthcare systems. His proficiency in software development is supported by multiple software copyrights for psychological assessment and intervention tools. Furthermore, his leadership in interdisciplinary projects highlights strong skills in project management, team coordination, and inter-institutional collaboration. Altogether, Professor Li’s technical and analytical expertise underscores his capability as a top-tier researcher in psychology and behavioral science.

Conclusion💡

Professor Qi Li is highly suitable and deserving of the Best Researcher Award. His track record exemplifies academic excellence, innovation in psychological assessment and intervention, real-world impact, and national-level leadership in both research and education. While opportunities for enhanced globalization and commercialization exist, his contribution to mental health, cognitive neuroscience, and student behavioral development is both timely and transformative.

Publications Top Noted✍

  1. Title: Core Symptoms and Symptom Relationships of Problematic Internet Use in Children and Adolescents: A Network Analysis
    Authors: Qi Li, Hui Zhou, Guangteng Meng, Jing Xiao, Kesong Hu, Ping Wei, Jinpeng Wang, Mei Du, Xun Liu
    Year: 2025
    Citation (DOI): https://doi.org/10.1007/s11469-025-01455-9

  2. Title: Patients with Methamphetamine Use Disorder Show Highly Utilized Proactive Inhibitory Control and Intact Reactive Inhibitory Control with Long-Term Abstinence
    Authors: Weine Dai, Hui Zhou, Arne Møller, Ping Wei, Kesong Hu, Kezhuang Feng, Jie Han, Qi Li, Xun Liu
    Year: 2022
    Citation (DOI): https://doi.org/10.3390/brainsci12080974

  3. Title: The Roles of Risk Perception, Negative Emotions and Perceived Efficacy in the Association Between COVID-19 Infection Cues and Preventive Behaviors: A Moderated Mediation Model (Preprint)
    Authors: Guangteng Meng, Xiaoyan Yuan, Ya Zheng, Kesong Hu, Qi Li, Bibing Dai, Xun Liu
    Year: 2021
    Citation (DOI): https://doi.org/10.2196/preprints.32930

  4. Title: Enhanced Neural Responses in Specific Phases of Reward Processing in Individuals with Internet Gaming Disorder
    Authors: Lingxiao Wang, Guochun Yang, Ya Zheng, Zhenghan Li, Yue Qi, Qi Li, Xun Liu
    Year: 2021
    Citation (DOI): https://doi.org/10.1556/2006.2021.00003

  5. Title: The Impact of Intolerance of Uncertainty on Negative Emotions in COVID-19: Mediation by Pandemic-Focused Time and Moderation by Perceived Efficacy
    Authors: Weine Dai, Guangteng Meng, Ya Zheng, Qi Li, Bibing Dai, Xun Liu
    Year: 2021
    Citation (DOI): https://doi.org/10.3390/ijerph18084189

  6. Title: The Effects of COVID-19 Infection Cues on Preventive Behaviors: Development of a Moderated Mediation Model (Preprint)
    Authors: Guangteng Meng, Xiaoyan Yuan, Qi Li, Bibing Dai, Xun Liu
    Year: 2021
    Citation (DOI): https://doi.org/10.2196/preprints.28986

  7. Title: Dysfunctional Cognitive Control and Reward Processing in Adolescents with Internet Gaming Disorder
    Authors: Qi Li, Yong Wang, Zhong Yang, Weine Dai, Ya Zheng, Yuwei Sun, Xun Liu
    Year: 2020
    Citation (DOI): https://doi.org/10.1111/psyp.13469

 

Assoc Prof Dr. Chor-Kheng Lim | Human-Computer Interaction | Best Researcher Award

Published on by Computer Vision Awards

Assoc Prof Dr. Chor-Kheng Lim | Human-Computer Interaction | Best Researcher Award

Chor-Kheng Lim at YuanZe University, Taiwan

👨‍🎓 Profiles

Scopus

Orcid

Google Scholar

Publications

Research on Indoor Spatial Behavior Perception IoT Smart System for Solitary Elderly at Home

  • Authors: Chor-Kheng Lim
  • Journal: Designs
  • Year: 2022

A framework of CAD/CAM design and construction process for freeform architecture: a case study

  • Authors: Chor-Kheng Lim
  • Journal: International Journal of Architectural Computing
  • Year: 2010

New tectonics: a preliminary framework involving classic and digital thinking

  • Authors: Yu-Tung Liu, Chor-Kheng Lim
  • Journal: Design studies
  • Year: 2006

Comparisons of practice progress of digital design and fabrication in free-form architecture

  • Authors: Zi-Ru Chen, Chor-Kheng Lim, Wei-Yen Shao
  • Journal: Journal of industrial and production engineering
  • Year: 2015

From concept to realization

  • Authors: Chor-Kheng Lim
  • Journal: Proceedings of Association for Computer Aided Design in Architecture
  • Year: 2006

Ms. Bdour Hamad Alwugaysi | Human-Computer Interaction | Best Researcher Award

Published on by Computer Vision Awards

Ms. Bdour Hamad Alwugaysi | Human-Computer Interaction | Best Researcher Award

Bdour Hamad Alwugaysi at King’s College London, United Kingdom

👨‍🎓 Profiles

Scopus

Orcid

Google Scholar

Publications

The impact of social media use on mental health and family functioning within web-based communities in Saudi Arabia: Ethnographic correlational study

  • Authors: Bdour Alwuqaysi, Alfie Abdul-Rahman, Rita Borgo
  • Journal: JMIR Formative Research
  • Year: 2024

Correlational Data Visualizations with Colored Bar Charts

  • Authors: Bdour Alwuqaysi, Alfie Abdul-Rahman, Rita Borgo
  • Year: 2024

Visualizing Content-based Categorization of Social Media Platforms: A Study of UK Users

  • Authors: Bdour Alwuqaysi, Alfie Abdul-Rahman, Rita Borgo
  • Year: 2024

Visualizing The Effect Of Frequency And Nature Of Social Media Platforms Usage On Mental Health And Family Functioning From An Ethnographic Point Of View

  • Authors: Bdour Hamad Alwuqaysi.
  • Year: 2024

An Ethnographic Study: on the Impact of Social Media Usage on Mental Health and Family Functioning on Saudi Arabia Online Communities

  • Authors: Bdour Alwuqaysi
  • Journal: JMIR Formative Research
  • Year: 2023

Dr. Dang Anh Tuan | Human-Computer Interaction | Best Researcher Award

Published on by Computer Vision Awards

Dr. Dang Anh Tuan | Human-Computer Interaction | Best Researcher Award

Doctorate at University of Medicine and Pharmacy at Ho Chi Minh City, Vietnam

👨‍🎓 Profiles

Orcid

Google Scholar

Publications

Real earnings management trends in the context of the COVID-19 pandemic: The case of non-financial listed companies in Vietnam

  • Authors: Dang Anh Tuan, Nguyen Ngoc Khanh Dung, Bui Thi Thu Thao
  • Year: 2023

Model for Forecasting Tax Compliance Behaviors for Small and Medium Enterprises Owners Based on Owning Tax Knowledge

  • Authors: Nguyen Ngoc Khanh Dung, Dang Anh Tuan, Bui Thi Thu Thao
  • Journal: Journal of Law and Sustainable Development
  • Year: 2023

Financial distress prediction of listed companies–empirical evidence on the Vietnamese stock market

  • Authors: Tran Quoc Thinh, Dang Anh Tuan, Nguyen Thanh Huy, Tran Ngoc Anh Thu
  • Journal: Innovations
  • Year: 2021

Development of Audit Risk Model Applied in Public Investment Project Audit: The State Audit in Vietnam

  • Authors: Dang Anh Tuan, Nguyen Ngoc Khanh Dung.
  • Journal: Social Space
  • Year: 2023

TESTING THE INFLuENCE OF FACTORS ON THE TIMELINESS OF FINANCIAL REPORTING–EMPIRICAL EVIDENCE OF VIETNAMESE LISTED ENTERPRISES

  • Authors: Tran Quoc Thinh, Dang Anh Tuan, Luu Chi Danh
  • Journal: Innovations
  • Year: 2022

Mr. Md Abrar Jahin | Human Computer Interaction | Best Researcher Award

Published on by Computer Vision Awards

Mr. Md Abrar Jahin, Human Computer Interaction, Best Researcher Award

Md Abrar Jahin at Okinawa Institute of Science and Technology Graduate University, Bangladesh

Profiles

Scopus

Orcid

Google Scholar

Research Gate

Linked In

🎓 Education:

Mr. Md Abrar Jahin pursued his B.Sc. in Industrial & Production Engineering at Khulna University of Engineering & Technology (KUET), Bangladesh, from January 2019 to March 2024. He graduated with a remarkable CGPA of 3.83/4.00, ranking in the top 5% of his class. Abrar was honored with the Dean’s Award for three consecutive years (2018-2019, 2019-2020, 2020-2021) for his exceptional academic performance. His thesis, titled “Supply Chain Backorder Prediction Using Interpretable Hybrid Quantum–Classical Neural Network,” reflects his deep engagement with cutting-edge research in his field.

🔬 Research Interests:

Mr. Abrar’s research interests span several advanced areas, including Machine Learning & Deep Learning, Natural Language Processing (NLP), eXplainable AI (XAI), Quantum Computing and Comparative Genomics. His work in these areas includes developing innovative models like Kolmogorov-Arnold Networks (KAN) and Physics-Informed Neural Networks (PINN), and applying them to practical problems in supply chain management, logistics, and demand forecasting.

🔍 Research Experience:

Visiting Researcher at the Physics and Biology Unit, Okinawa Institute of Science and Technology (OIST), Japan, since March 2024. Abrar is working under the supervision of Prof. Jonathan Miller on the project “Evolution of Strongly Conserved Sequence.”

Visiting Research Student at OIST from February 2023 to February 2024, contributing to research on conserved sequences and genomic alignments.

Researcher at the Advanced Machine Intelligence Research Lab (AMIRL), American International University-Bangladesh (AIUB), since March 2023, focusing on NLP and deep learning.

Research Lead at Research Camp 02, Scholarship School BD, Bangladesh, where he led a team on an AI project for COVID-19 detection from May 2022 to March 2023.

Research Intern at OIST, Japan, from October 2021 to March 2022, where he conducted research on sequence length distributions and optimized genomic data analysis workflows.

Research Intern at UiT – The Arctic University of Norway in May 2021, working on machine learning models for road state identification.

🏆 Honors and Awards:

Mr. Abrar has received numerous accolades, including being a Global Champion in the Smart Roads Hackathon 2021, Top 6 in Entrepret Season-2: Crafting Visions 2021, and a Global Nominee in the NASA Space Apps Challenge 2023. He has also been awarded the Dean’s Award at KUET three times and recognized as a Junior Research Fellow by SPARRSO in 2022.

👩‍🏫 Professional Skills:

Mr. Abrar is proficient in multiple programming languages and tools such as Python, C/C++, R, SQL, and SAS. He is skilled in Machine Learning, Data Analysis, and High-Performance Computing, and familiar with Quantum Machine Learning and XAI.

📖 Publications:

Big Data—Supply Chain Management Framework for Forecasting: Data Preprocessing and Machine Learning Techniques
  • Authors: Md Abrar Jahin, Md Sakib Hossain Shovon, Jungpil Shin, Istiyaque Ahmed Ridoy, MF Mridha
  • Journal: Archives of Computational Methods in Engineering
  • Year: 2024
A Natural Language Processing-Based Classification and Mode-Based Ranking of Musculoskeletal Disorder Risk Factors
  • Authors: Md Abrar Jahin, Subrata Talapatra
  • Journal: Decision Analytics Journal
  • Year: 2024
Analysis of Internet of things implementation barriers in the cold supply chain: An integrated ISM-MICMAC and DEMATEL approach
  • Authors: Kazrin Ahmad, Md Saiful Islam, Md Abrar Jahin, Muhammad Firoz Mridha
  • Journal: PloS one
  • Year: 2024
Optimizing Container Loading and Unloading through Dual-Cycling and Dockyard Rehandle Reduction Using a Hybrid Genetic Algorithm
  • Authors: Md Mahfuzur Rahman, Md Abrar Jahin, Md Saiful Islam, MF Mridha
  • Journal: arXiv preprint arXiv:2406.08534
  • Year: 2024
MCDFN: Supply Chain Demand Forecasting via an Explainable Multi-Channel Data Fusion Network Model
  • Authors: Md Abrar Jahin, Asef Shahriar, Md Al Amin
  • Journal: arXiv preprint arXiv:2405.15598
  • Year: 2024

Human-Computer Interaction

Published on by Computer Vision Awards

Introduction of Human-Computer Interaction

Introduction: Human-Computer Interaction (HCI) research is a multidisciplinary field that focuses on understanding and improving the interaction between humans and technology. It explores how users interact with digital systems, interfaces, and devices, aiming to enhance user experiences, usability, and accessibility. HCI research plays a pivotal role in shaping the design of user-friendly and intuitive technology interfaces.

Subtopics in Human-Computer Interaction:

  1. User Interface Design: Research in this area centers on designing user interfaces that are intuitive, visually appealing, and efficient. It involves studying user behaviors and preferences to create interfaces that meet user needs.
  2. Usability Testing and Evaluation: HCI researchers conduct usability tests to assess the effectiveness and efficiency of interfaces. They gather user feedback to identify and address usability issues, ensuring products are user-centric.
  3. Accessibility and Inclusive Design: Ensuring technology is accessible to individuals with disabilities is a critical focus. Research in this subfield involves designing interfaces and technologies that accommodate diverse user needs.
  4. Augmented and Virtual Reality Interaction: With the rise of AR and VR technologies, HCI research explores how users interact with virtual environments and objects, aiming to create immersive and user-friendly experiences.
  5. Natural Language Processing (NLP) and Conversational Interfaces: HCI researchers work on developing natural language interfaces, chatbots, and voice assistants to facilitate human-computer communication through speech and text.
  6. Gesture and Touch Interaction: Studying how users interact with touchscreens and gesture-based interfaces, such as those found in smartphones and tablets, and developing intuitive gesture-based control systems.
  7. Mobile and Wearable Device Interaction: HCI in the context of mobile devices and wearables focuses on designing interfaces that are effective on smaller screens and exploring novel interaction methods like touch, swipe, and voice commands.
  8. Human-AI Collaboration: As AI becomes more integrated into daily life, HCI research investigates how humans and AI systems can work together seamlessly and effectively, with applications in healthcare, education, and more.
  9. Privacy and Security in HCI: Ensuring the privacy and security of user data is paramount. Researchers explore ways to design interfaces that protect user information while maintaining usability.
  10. Emotion and Affective Computing: Understanding and measuring user emotions and affective states during interactions with technology is vital for tailoring interfaces and services to user needs and preferences.

HCI research continues to evolve in response to advancements in technology and the changing ways humans interact with digital systems. These subtopics highlight the critical areas of study within HCI that contribute to enhancing user experiences and shaping the future of human-computer interaction.

Object Detection and Recognition
Introduction Object Detection and Recognition: Object Detection and Recognition is a vibrant and evolving field of computer vision and artificial intelligence, dedicated to the automated identification and localization of objects
Image Processing and Enhancement
Introduction Image Processing and Enhancement: Image Processing and Enhancement is a pivotal domain within the realm of computer vision and digital imaging. This field is dedicated to the development of
Computer Vision for Robotics and Autonomous Systems
Introduction of Computer Vision for Robotics and Autonomous Introduction: Computer Vision for Robotics and Autonomous Systems is a multidisciplinary field at the intersection of computer vision, robotics, and artificial intelligence.
3D Computer Vision
Introduction of 3D Computer Vision 3D Computer Vision is a dynamic and interdisciplinary field that aims to enable machines to perceive and understand the three-dimensional structure of the world from
Medical Image Analysis
Introduction of Medical Image Analysis Medical Image Analysis is a critical and rapidly evolving field that harnesses the power of computer vision and machine learning to extract valuable insights from
Video Analysis
Introduction of Video Analysis Video Analysis and Understanding is a dynamic and interdisciplinary field that aims to develop algorithms and techniques for extracting meaningful information from video data. It plays
Deep Learning for Computer Vision
Introduction of Deep Learning for Computer Vision Deep Learning for Computer Vision is at the forefront of modern artificial intelligence, revolutionizing the way machines perceive and interpret visual information. It
Applications of Computer Vision
Introduction of Applications of Computer Vision Applications of Computer Vision represent a diverse and ever-expanding landscape of practical uses for visual data analysis and interpretation. Computer vision technology has transitioned
Human-Computer Interaction
Introduction of Human-Computer Interaction Introduction: Human-Computer Interaction (HCI) research is a multidisciplinary field that focuses on understanding and improving the interaction between humans and technology. It explores how users interact
Biometrics and Security
Introduction of Biometrics and Security Biometrics and Security research is dedicated to the development of cutting-edge technologies that leverage unique physiological or behavioral characteristics of individuals for identity verification and