Yuxuan Zhao – Deep Learning – Best Researcher Award

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Yuxuan Zhao - Deep Learning - Best Researcher Award

Xi’an Jiaotong-Liverpool University - China

AUTHOR PROFILE

SCOPUS

ACADEMIC BACKGROUND

Dr. Yuxuan Zhao is an accomplished Assistant Professor at the School of AI and Advanced Computing (AIAC) at Xi’an Jiaotong-Liverpool University (XJTLU), Taicang Campus. He completed his PhD in Computer Science from the University of Liverpool in 2022 and holds an MSc in Computer Graphics, Vision and Imaging from University College London, earned in 2017. His academic journey reflects a robust foundation in advanced computing and artificial intelligence.

RESEARCH INTERESTS

Dr. Zhao’s research encompasses a broad spectrum of advanced technological fields. His primary interests include deep learning, image and video processing, computer vision, and the application of machine learning techniques. His work aims to push the boundaries of how these technologies can be utilized to solve complex real-world problems.

RESEARCH PROJECTS

Dr. Zhao is engaged in several cutting-edge research projects. His work on "Deep Learning in Video Anomaly Detection" and "Radar Signal Processing Based on Neural Network Sequence Mode" highlights his focus on innovative applications of machine learning. He is also involved in "Computer Vision-Based Traffic Accident Detection" and the governmental project "Intelligent Multimodal Data Analysis for Digital Twin Cities," reflecting his commitment to advancing technology in practical and impactful ways.

PROCEEDINGS AND PUBLICATIONS

Dr. Zhao has contributed to numerous high-profile conferences and journals. His recent papers include "Appearance-Motion United Memory Autoencoder for Video Anomaly Detection," presented at the 2023 International Conference on Cyber-Enabled Distributed Computing and Knowledge Discovery, and "YOLOv5s-Transformer: Improved YOLOv5 Network for Real-Time Detection of Cigarette Smoking," showcased at the 2023 4th International Seminar on Artificial Intelligence, Networking, and Information Technology. His research demonstrates a deep engagement with current trends and challenges in computer vision and AI.

CONFERENCE PARTICIPATION

Dr. Zhao has actively participated in the academic community by presenting at leading conferences and contributing to the advancement of knowledge in his field. His presentations at various international seminars and conferences underscore his role in shaping the future of AI and computer vision.

INNOVATIVE RESEARCH CONTRIBUTIONS

Dr. Zhao’s innovative contributions include the development of intelligent algorithms for multi-mobile robot systems and autonomous alert generation for disaster management. His early work, such as the design of algorithms for Wi-Fi access point roaming, highlights his long-standing dedication to addressing diverse technological challenges.

GOVERNMENTAL RESEARCH PROJECTS

Currently, Dr. Zhao is involved in several governmental research initiatives, including the "Suzhou Multimodal Big Data Innovation Application Lab," which aims to enhance the application of big data and AI technologies. These projects reflect his ongoing commitment to leveraging advanced technologies for societal benefit.

NOTABLE PUBLICATION

A Novel Two-Stream Structure for Video Anomaly Detection in Smart City Management

Authors: Zhao, Y., Man, K.L., Smith, J., Guan, S.-U.
Year: 2022
Journal: Journal of Supercomputing
Pages: 3940–3954

Improved Two-Stream Model for Human Action Recognition

Authors: Zhao, Y., Man, K.L., Smith, J., Siddique, K., Guan, S.-U.
Year: 2020
Journal: Eurasip Journal on Image and Video Processing
Article: 24

Erratum: RingText: Dwell-free and Hands-free Text Entry for Mobile Head-Mounted Displays Using Head Motions

Authors: Xu, W., Liang, H.-N., Zhao, Y., Yu, D., Monteiro, D.
Year: 2019
Journal: IEEE Transactions on Visualization and Computer Graphics
Volume: 25
DOI: 10.1109/TVCG.2019.2898736

DMove: Directional Motion-based Interaction for Augmented Reality Head-Mounted Displays

Authors: Xu, W., Liang, H.-N., Zhao, Y., Yu, D., Monteiro, D.
Year: 2019
Conference: Conference on Human Factors in Computing Systems - Proceedings

RingText: Dwell-free and Hands-free Text Entry for Mobile Head-Mounted Displays Using Head Motions

Authors: Xu, W., Liang, H.-N., Zhao, Y., Yu, D., Monteiro, D.
Year: 2019
Journal: IEEE Transactions on Visualization and Computer Graphics

Fangyu Wu – Artificial Intelligence – Best Researcher Award

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Fangyu Wu - Artificial Intelligence - Best Researcher Award

AUTHOR PROFILE

SCOPUS

ACADEMIC AND PROFESSIONAL BACKGROUND

Fangyu Wu is a distinguished researcher and academic in the field of computer science, specializing in deep learning, multi-modal learning, and intelligent data analysis. He is currently an Associate Professor at Xi’an Jiaotong-Liverpool University (XJTLU) in China, where he supervises PhD and Master's students focusing on innovative research topics such as multi-modal learning and deep learning for computer vision. His previous role included co-supervising PhD students at Zhejiang University, contributing to advancements in facial recognition and image-text retrieval.

HONORS AND AWARDS

Dr. Wu's achievements have been recognized through several prestigious awards. He was named a Suzhou Youth Innovation Leading Talent in 2023 and won first prize at the 7th China Innovation Challenge for his project on intelligent tracking systems using infrared thermal imaging. Additionally, he received the Lotfi Zadeh Best Paper Award at ICMLC&ICWAPR 2017 and has been honored with the Outstanding Graduates award from Xi’an Jiaotong-Liverpool University and National Encouragement Scholarships from China.

RESEARCH PROJECTS

Fangyu Wu leads several high-impact research projects. These include “Intelligent Multimodal Data Analysis for Digital Twin Cities” under the Gusu Innovation and Entrepreneurship Leading Talents Programme, and “Relational Modeling and Reasoning for Reliable Cross-Modal Retrieval” funded by the Zhejiang Natural Science Foundation. His projects also cover advanced topics such as distributed AI platforms for Metaverse scenarios and optimization software for injection molding processes.

PUBLICATIONS

Dr. Wu has an extensive list of publications in top-tier conferences and journals. Notable works include papers on fine-grained image-text matching, relation-aware prototype networks, and pose-robust face recognition. His research has been featured at prestigious conferences such as CVPR, ECCV, and ICPR, showcasing his contributions to advancements in deep learning and computer vision.

CONFERENCE ORGANIZATION

In addition to his research, Fangyu Wu plays a vital role in organizing academic conferences. He served as the Publication Chair for the IEEE 17th International Conference on Computer Science & Education (ICCSE 2022) and as General Co-Chair for the 5th International Symposium on Emerging Technologies for Education (SETE 2020). His involvement ensures the smooth execution of these events and contributes to the dissemination of cutting-edge research.

STUDENT SUPERVISION

Fangyu Wu is actively engaged in supervising students at both the PhD and Master’s levels. He currently supervises a PhD student at XJTLU focusing on multi-modal learning and has previously co-supervised a PhD student at Zhejiang University on deep learning for computer vision. His mentorship extends to six Master’s students at XJTLU and three at Zhejiang University, covering areas such as facial recognition and image-text retrieval.

COMPETITIONS AND RECOGNITION

Dr. Wu has achieved notable success in various competitions. His project on human motion recognition based on deep neural networks won third prize at the China First Smart Manufacturing and Big Data Innovation Competition. Additionally, his participation in competitions has been marked by significant awards, including the first prize in the China Innovation Challenge for his intelligent tracking system.

NOTABLE PUBLICATION

  • Fine-grained Image-text Matching by Cross-modal Hard Aligning Network
    • Authors: Pan, Z., Wu, F., Zhang, B.
    • Year: 2023
    • Conference: IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR)
    • Pages: 19275–19284
  • Knowledge-embedded Prompt Learning for Zero-shot Social Media Text Classification
    • Authors: Li, J., Chen, Q., Wang, W., Wu, F.
    • Year: 2023
    • Conference: IEEE International Conference on Smart Computing (SMARTCOMP)
    • Pages: 222–224
  • Kernel Triplet Loss for Image-Text Retrieval
    • Authors: Pan, Z., Wu, F., Zhang, B.
    • Year: 2022
    • Conference: Computer Animation and Virtual Worlds
    • Article: e2093
  • FaceCaps for Facial Expression Recognition
    • Authors: Wu, F., Pang, C., Zhang, B.
    • Year: 2021
    • Conference: Computer Animation and Virtual Worlds
    • Article: e2021

BASEM A. ALKHALEEL – Machine learning – Best Paper Award

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BASEM A. ALKHALEEL - Machine learning - Best Paper Award

King Saud University - Saudi Arabia

PROFESSIONAL SUMMARY

Basem A. Alkhaleel is a dedicated Assistant Professor in Industrial Engineering with a distinguished record of academic excellence and practical expertise in process reengineering and business continuity. Combining his extensive background in teaching, research, project management, and consulting, he brings a unique perspective to both academia and industry. With skills in leading cross-functional teams, analyzing complex systems, and implementing innovative solutions, he excels in driving process optimization, operational efficiency, and organizational resilience.

EDUCATION

Basem A. Alkhaleel holds a Ph.D. in Industrial Engineering from the University of Arkansas (2021), an MSc in Industrial and Systems Engineering from Texas A&M University (2015), and a BSc in Industrial Engineering from King Saud University (2012).

ACADEMIC AND RESEARCH EXPERIENCE

As an Assistant Professor at King Saud University since September 2021, Basem A. Alkhaleel has been involved in directing the counseling unit for undergraduate engineering students, participating in various departmental committees, and supervising numerous undergraduate student graduation projects. His research focuses on machine learning applications in critical infrastructure resilience, reliability engineering, and business continuity.

PROFESSIONAL EXPERIENCE

In addition to his academic roles, Basem A. Alkhaleel is a Management Consultant at ES Consulting in Riyadh, Saudi Arabia, where he develops and implements process improvement strategies and business continuity plans. He has also served as a Project Manager at the Arkansas Department of Transportation, leading the development and implementation of a decision support system for multi-modal transportation operations.

PROJECT MANAGEMENT AND CONSULTING

Basem A. Alkhaleel has managed several high-profile projects, including process documentation and modeling for the Ministry of Municipal and Rural Affairs and Housing and the Advanced Electronics Company. His work involves process modeling, documentation, digitalization, and KPI alignment to improve operational and strategic efficiencies.

RESEARCH AND INNOVATION

During his Ph.D. research at the University of Arkansas, Basem A. Alkhaleel developed resilience-based restoration models for disrupted critical infrastructures and combined risk mitigation with resilience restoration and simulation modeling. His MSc research at Texas A&M University focused on data-driven approaches to improve decision-making processes in engineering projects.

TEACHING AND MENTORING

With a strong commitment to education, Basem A. Alkhaleel has lectured on various industrial engineering subjects, including manufacturing processes and reliability engineering, at King Saud University. His teaching philosophy emphasizes innovative strategies to enhance student performance and academic success.

STRATEGIC PLANNING AND DEVELOPMENT

Earlier in his career, Basem A. Alkhaleel worked as a Strategic Planner at Ma’aden Company, developing long-term strategic plans and applying business development tools to identify areas of improvement. His strategic insights and communication skills have been instrumental in achieving organizational objectives and driving continuous improvement initiatives.

NOTABLE PUBLICATIONS

Risk and resilience-based optimal post-disruption restoration for critical infrastructures under uncertainty 2022 (44)

Hybrid simulation to support interdependence modeling of a multimodal transportation network 2021 (19)

Machine learning applications in the resilience of interdependent critical infrastructure systems—A systematic literature review 2023 (8)

Model and solution method for mean-risk cost-based post-disruption restoration of interdependent critical infrastructure networks 2022 (10)

Pramod Patil – Deep Learning and Smart Grid – Best Researcher Award

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Pramod Patil - Deep Learning and Smart Grid - Best Researcher Award

Dr.D.Y.Patil Institute of Technology - India

AUTHOR PROFILE

Google Scholar

ACADEMIC EXCELLENCE AND PROFESSIONAL JOURNEY 🎓

Pramod Patil's academic odyssey commenced with a Bachelor's degree in Computer Science and Engineering from S.G.G.S. College of Engineering and Technology, Nanded, followed by a Master's and Ph.D. in Computer Engineering from Govt. College of Engineering, Pune. Since November 2001, he has been an integral part of Dr.D.Y.Patil Institute of Technology, Pune, where he has held various academic positions, culminating in his current role as Professor.

EXEMPLARY ADMINISTRATIVE ROLES AND LEADERSHIP 🏢

Throughout his tenure, Patil has demonstrated exemplary leadership and administrative acumen. From serving as Dean and Principal to holding pivotal roles such as Vice Principal and Head of Department, his leadership has been instrumental in shaping the academic and administrative landscape of his institution.

COMMITMENT TO ACADEMIC ACCREDITATION AND ASSESSMENT 📚

Patil's commitment to academic quality and accreditation is evidenced through his involvement in various accreditation processes at both the institute and university levels. His expertise in accreditation, coupled with his roles as a member of inquiry committees and subject expert, underscores his dedication to upholding academic standards and fostering institutional growth.

PROFESSIONAL ENGAGEMENT AND MEMBERSHIPS 🔬

As a lifelong learner and academic stalwart, Patil is actively engaged in professional societies such as the Indian Society for Technical Education (ISTE), Computer Society of India (CSI), and Association of Computing Machinery (ACM). His membership and contributions to these esteemed organizations reflect his commitment to advancing the field of computer engineering.

RECOGNITION AND AWARDS 🏆

Patil's contributions to academia have garnered widespread recognition and acclaim. From receiving Best Paper Awards to being appointed as Dean of the Faculty of Science and Technology at Savitribai Phule Pune University, his accolades underscore his scholarly prowess and leadership excellence.

INSPIRING FUTURE GENERATIONS AND MENTORSHIP 🌱

As a mentor and guide, Patil has played a pivotal role in shaping the careers of numerous students and researchers. His dedication to nurturing talent and fostering academic excellence has left an indelible mark on the academic community, inspiring generations of scholars to pursue their academic and professional aspirations.

INNOVATIVE RESEARCH ENDEAVORS AND CONTRIBUTIONS 🚀

Patil's research endeavors have spanned diverse domains such as machine learning, data security, blockchain, and smart grid technology. His prolific publication record, patent contributions, and research projects highlight his commitment to advancing knowledge and addressing real-world challenges through innovative research methodologies.

NOTABLE PUBLICATION

Skewed Evolving Data Streams Classification with Actionable Knowledge Extraction using Data Approximation and Adaptive Classification Framework 2023 (7)

Context-aware clustering and the optimized whale optimization algorithm: An effective predictive model for the smart grid 2023 (9)

Blockchain-based security services for fog computing 2021 (16)

EFFECT OF EARLY FUNCTIONAL MOBILITY ON FUNCTIONAL INDEPENDENCE IN INCOMPLETE PARAPLEGIC INDIVIDUALS. 2022 (3)

Dajian Zhong – Scene Text Recognition – Best Researcher Award

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Dajian Zhong - Scene Text Recognition - Best Researcher Award

Shanghai Maritime University - China

AUTHOR PROFILE

Scopus

EARLY ACADEMIC PURSUITS

Dr. Dajian Zhong's academic journey commenced with a strong foundation in Computer Science and Technology, beginning with a Bachelor's degree from Suzhou University of Science and Technology. He furthered his studies with a Master's degree from East China University of Science and Technology, specializing in Computer Science and Technology. Dr. Zhong's academic pursuits culminated in a Ph.D. in Computer Application Technology from East China Normal University. Throughout his educational journey, he exhibited a keen interest in advancing the field of computer vision, particularly in the domain of scene text recognition.

PROFESSIONAL ENDEAVORS

Dr. Zhong currently serves as a Lecturer in the College of Information Engineering at Shanghai Maritime University, where he imparts knowledge and expertise to aspiring students. His professional career is characterized by a commitment to excellence in research and education, with a focus on computer vision, text detection, and recognition. Through his role as a lecturer, Dr. Zhong continues to inspire and mentor the next generation of computer scientists and engineers.

CONTRIBUTIONS AND RESEARCH FOCUS

Dr. Zhong's research is centered around the advancement of scene text recognition, a critical area within computer vision. His work explores novel algorithms and techniques to improve the accuracy and efficiency of text detection and recognition in complex scenes. By leveraging approaches such as semantic GANs, attention networks, and transformer networks, Dr. Zhong aims to address the challenges associated with arbitrarily oriented and shaped text in real-world environments. His contributions have been published in reputable journals and presented at international conferences, demonstrating his expertise and impact in the field.

IMPACT AND INFLUENCE

Dr. Zhong's research has made a significant impact on the field of scene text recognition, garnering recognition from peers and researchers worldwide. His innovative algorithms and methodologies have advanced the state-of-the-art in text detection and recognition, facilitating applications in various domains, including document analysis, image understanding, and augmented reality. Through his collaborative efforts and interdisciplinary approach, Dr. Zhong continues to shape the future of computer vision and inspire advancements in intelligent systems and technologies.

ACADEMIC CITES

Dr. Zhong's publications have received significant citations from researchers and practitioners in the field of computer vision, attesting to the relevance and impact of his work. His research findings have been instrumental in advancing the understanding and capabilities of scene text recognition systems, contributing to the development of more accurate and robust algorithms for real-world applications. Dr. Zhong's influence extends beyond academia, as his work continues to shape the landscape of computer vision research and technology.

LEGACY AND FUTURE CONTRIBUTIONS

As Dr. Zhong continues to pursue his research endeavors, his focus remains on pushing the boundaries of scene text recognition and computer vision. Through ongoing collaborations, mentorship, and knowledge dissemination, he seeks to further advance the field and foster innovations that benefit society at large. Dr. Zhong's legacy lies in his dedication to excellence, his passion for advancing knowledge, and his commitment to addressing real-world challenges through cutting-edge research in scene text recognition.

NOTABLE PUBLICATION

LRATNet: Local-Relationship-Aware Transformer Network for Table Structure Recognition 2024

NDOrder: Exploring a novel decoding order for scene text recognition 2024