Waris Ali | Computer Science | Best Researcher Award

Mr Waris Ali | Computer Science | Best Researcher Award

Student, Beijing University of Technology, China

Waris Ali is a PhD scholar in the Department of Information Technology at Beijing University of Technology, China. With extensive academic and professional experience in Computer Science, he has worked as a lecturer at multiple institutions in Pakistan, including The Islamia University of Bahawalpur, Superior Group of Colleges, and Govt. Degree College. Throughout his career, Waris has demonstrated strong interpersonal skills and cultural competence, which have helped him foster a collaborative learning environment. His work focuses on advanced technologies like distributed systems, IoT, and artificial intelligence, with a particular emphasis on content delivery networks (CDNs) and multi-CDN deployment. Waris is committed to pushing the boundaries of technology through his research, contributing valuable insights to both academia and industry.

PROFESSIONAL PROFILE

Google Scholar

EDUCATION

Waris Ali is currently pursuing a PhD in Computer Science (2022-2026) at Beijing University of Technology, China. He completed his M.Phil. in Computer Science in 2020 from The Islamia University of Bahawalpur, where he achieved an impressive CGPA of 3.74/4.0. He also holds a Bachelor of Science in Information Technology (2013-2017) from the same institution, graduating with a CGPA of 3.889/4.0. Waris completed his intermediate studies in Science (FSc Pre-Engineering) in 2013, securing 730/1100 marks from the Board of Intermediate and Secondary Education. His academic journey reflects a strong foundation in computer science and information technology, positioning him for success in his current research.

EXPERIENCE

Waris Ali has garnered substantial experience as a lecturer in Computer Science at various prestigious institutions, including The Islamia University of Bahawalpur, Superior Group of Colleges, and Govt. Degree College, Yazman. He has also worked as a web developer at Digicon Computer Center, Bahawalpur. His teaching experience spans from 2017 to 2022, during which he has consistently demonstrated excellent communication and interpersonal skills. Waris has built strong relationships with both students and faculty, creating a supportive educational environment. His ability to collaborate with students from diverse backgrounds has enriched the learning experience, especially in international settings. This experience complements his academic research and professional growth.

AWARDS AND HONORS

Waris Ali’s dedication to research and academic excellence has earned him recognition in his field. He received accolades for his contribution to the study of content delivery networks in Pakistan. His work, “Analyzing the Deployment and Performance of Multi-CDNs in Pakistan,” was published in the Pakistan Journal of Engineering and Technology. Additionally, Waris presented at notable conferences such as the 4th Asia Pacific International Conference on Emerging Engineering (APICEE), where he discussed multi-CDN deployment. He has also participated in the 2nd International Computer Science Conference, showcasing his ongoing commitment to advancing the field of Computer Science.

RESEARCH FOCUS

Waris Ali’s research interests lie in distributed systems, reliable networks, content delivery networks (CDNs), IoT applications, artificial intelligence, and data science. His work aims to analyze and improve the performance and deployment of multi-CDNs, with a focus on their application in Pakistan. His research contributes valuable insights into optimizing the efficiency of these networks, as well as exploring the potential of emerging technologies in real-world applications. With his current research as a PhD candidate at Beijing University of Technology, Waris is working to expand the boundaries of knowledge in these cutting-edge fields.

PUBLICATION TOP NOTES

  • “Analyzing the Deployment and Performance of Multi-CDNs in Pakistan” — Pakistan Journal of Engineering and Technology 📖
  • “Analyzing the Deployment and Performance of Multi-CDNs in Pakistan” — 4th Asia Pacific International Conference on Emerging Engineering (APICEE), 2021 📚
  • “The 2nd International Computer Science Conference” — International Conference on Intelligent Technologies & Applications (INTAP), 2019 💻

CONCLUSION

Waris Ali is a promising researcher and academic in the field of Computer Science, dedicated to advancing the understanding and application of emerging technologies. With a solid educational background and diverse professional experience, he continues to contribute valuable research on content delivery networks, artificial intelligence, and IoT applications. His commitment to excellence in both teaching and research underscores his role as an influential figure in the global tech community.

Duaa Mehiar | Artificial Intelligence | Best Researcher Award

Assist. Prof. Dr Duaa Mehiar | Artificial Intelligence | Best Researcher Award

Assistant Professor, Middle East University, Jordan

Duaa Mehiar is an expert in Artificial Intelligence and Robotics, currently part of the Department of IT at Middle East University. She has a strong background in developing intelligent robotic systems, optimizing robotic swarm behaviors, and exploring AI applications in education and healthcare. Duaa is passionate about the intersection of technology and practical solutions, particularly in enhancing robot autonomy and improving human-robot interactions. She has contributed significantly to research in robotic optimization and AI systems, with numerous publications in international journals.

Professional Profile

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Scopus

Strengths for the Award

Duaa Mehiar is an accomplished researcher in the fields of Artificial Intelligence (AI) and Robotics. With a PhD in AI from the University of Malaya, her extensive academic background, demonstrated by her impactful research on optimization methods in robot swarm behaviors, makes her a prime candidate for the Best Researcher Award. Her published works in high-impact journals and international conferences, including contributions to cloud-based frameworks for social robotics and AI-based systems for education, have received recognition in academia. Duaa’s research on dynamic task distribution in drone swarms and deep fake image detection also highlights her broad expertise in both practical applications and cutting-edge AI research.

Areas for Improvement

Although Duaa has made significant strides in her research, further collaboration with interdisciplinary teams in the fields of neuroscience and psychology could enhance the human-robot interaction aspects of her work, especially with virtual agents. Expanding the scope of her research to explore more industry-based applications of her findings, particularly in education and healthcare, would also make her work more impactful. Additionally, more emphasis on real-world robotic deployments could demonstrate her research’s practical outcomes.

Education

  • Ph.D. in Artificial Intelligence – University of Malaya, 2016–2021
    Thesis: Improving Robot Darwinian Particle Swarm Optimization Using Quantum-Behaved Swarm Theory for Robot Exploration and Communication
  • MSc in Computer Science – Al Balqa Applied University, Jordan, 2007–2009
    Thesis: The Multi-Robot Cooperative System for Objects Detection
  • B.Sc. in Computer Science – Al Zaytoona University, Jordan, 1998–2002
    Graduation Project: Production System for Oriental Arabs using Oracle Language

Experience

Duaa Mehiar has a wealth of experience in the field of robotics and AI. She has trained teachers and school supervisors on integrating AI into education, including using metaverse and robots. Duaa was involved in numerous training programs with institutions like EduTech and Ishraq Institute. She has contributed to robotic research and development, from swarm optimization algorithms to practical applications like controlling robots using various protocols. Her expertise includes IoT projects and robot building using Arduino technology.

Awards and Honors

Duaa has received multiple honors for her work in robotics and AI. She was nominated as a trainer for the Ministry of Education in Dubai and Ras Al Khaima for teaching robotic theory and practice. She has also been part of the Arab Robotics Association and has served as a judge for the Arab Robotics Competition. Her research in AI and robotics has been recognized by international platforms, earning her citations and respect within the scientific community.

Research Focus

Duaa’s research primarily focuses on AI and robotics, particularly in optimization algorithms for swarm robots, human-robot interaction, and AI applications in education and healthcare. She has developed quantum-behaved swarm optimization methods for robot exploration and communication. Her interests include improving robotic autonomy, integrating robots in educational environments, and exploring AI systems in healthcare, such as asthma management and rehabilitation. She is dedicated to advancing AI technologies to benefit society.

Publication Top Notes

  • Revolutionizing Social Robotics: A Cloud-Based Framework for Enhancing the Intelligence and Autonomy of Social Robots 🤖
  • Towards Renewable Urban Landscapes: Exploring Photovoltaic Panel Integration – A Case Study 🌍
  • Chatbots in Classrooms: Tailoring Education and Boosting Engagement 🎓
  • QRDPSO: A New Optimization Method for Swarm Robot Searching and Obstacle Avoidance in Dynamic Environments 🤖
  • Customized Convolutional Neural Network for Accurate Detection of Deep Fake Images in Video Collections 🎥
  • Report on Optimization for Efficient Dynamic Task Distribution in Drone Swarms Using QRDPSO Algorithm 🚁
  • Linguistic and Gender Factors in User Engagement with Arabic LLM-Based Virtual Agents for Rehabilitation 🧑‍💻
  • Real-Time Student Attention Evaluation and Engagement Recommendation System Using AI-Based Behavior Analysis 📚
  • Personalized Alarming System for Asthma Management Based on Lung Functionality 🫁
  • Reducing Interrupts Among Robots in Quantum-Behaved Swarm Exploration with MR-LEACH 🤖
  • Improving Robot Darwinian Particle Swarm Optimization Using Quantum-Behaved Swarm Theory for Robot Exploration and Communication 🔍
  • Multi-Robot Cooperative System for Object Detection 🤖
  • QRDPSO Equation: A New Optimization Method for Swarm Robot 🏎
  • Multi-Agent Cooperative System for Object Detection 🛠
  • Multi-Robot System for Search and Rescue Operations 🚑

Conclusion

Duaa Mehiar stands out for her contributions to the fields of AI and Robotics, with a focus on innovative solutions to enhance autonomous robotic systems and optimize AI-driven tasks. She demonstrates strong academic potential, with a portfolio of research that is not only technically sound but also socially relevant, particularly in education and healthcare. For the Best Researcher Award, her continued growth in interdisciplinary collaboration and real-world applications would solidify her place as a leading researcher in her field.

Sina Fard Moradinia | Machin Learning | Best Researcher Award

Assist. Prof. Dr Sina Fard Moradinia | Machine Learning | Best Researcher Award

Reviewer&Editor, Department of Civil Engineering, Tabriz Branch, Islamic Azad University, Tabriz, Iran

Dr. Sina Fard Moradinia is an Assistant Professor in the Department of Civil Engineering at Islamic Azad University, Tabriz Branch, Iran. He specializes in water resource management, hydrology, hydraulic engineering, computational fluid dynamics, and the application of machine learning in civil engineering. With a strong academic background and a focus on integrating advanced technologies, Dr. Fard Moradinia has contributed significantly to research in sustainable construction, water management, and infrastructure optimization. His work is recognized for its innovative approaches to environmental and structural challenges, particularly in dam construction, flood prediction, and water resource forecasting. He has authored several peer-reviewed papers and participated in numerous academic and professional conferences.

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Strengths for the Award

Dr. Sina Fard Moradinia is a highly accomplished researcher and educator in civil engineering, particularly in the areas of water resource management, hydrology, hydraulics, and computational fluid dynamics. His research contributions are diverse and impactful, addressing key challenges in dam construction, flood risk prediction, and sustainable water management. Dr. Fard Moradinia’s ability to integrate machine learning with traditional engineering models to solve complex problems stands out as a significant strength. His extensive body of work, evidenced by multiple publications in high-impact journals, reflects his proficiency in both theoretical and applied research, especially in projects that integrate Building Information Modeling (BIM), System Dynamics, and ANFIS models for project optimization.

Dr. Fard Moradinia has demonstrated leadership in his field through innovative research in human resource risk analysis in construction, water quality management, and the use of computational models to optimize construction project time and cost. His work on flood flow prediction and seepage analysis in earth dams is a testament to his ability to address real-world infrastructure challenges with advanced methodologies.

Areas for Improvements

While Dr. Fard Moradinia has a robust and impressive portfolio of research, there are a few areas where improvements or further development could enhance his profile for recognition.

  1. Broader Global Collaboration: Although his work is highly relevant within the local context of Iran, expanding his collaborative efforts with international researchers, especially in global water management issues or climate change adaptation strategies, could increase the global impact of his research.
  2. Interdisciplinary Approaches: There is an opportunity for Dr. Fard Moradinia to explore more interdisciplinary research areas, such as the integration of civil engineering with environmental science, data analytics, or sustainable urban planning. This could make his work even more relevant to the global discourse on climate change and urban sustainability.
  3. Public Engagement and Outreach: While his academic and research credentials are strong, increasing his presence in public and policy-making circles, particularly in the context of water crisis management and sustainable infrastructure, could make his work more impactful outside academia.

Education 

Dr. Sina Fard Moradinia holds a Ph.D. in Civil Engineering, focusing on hydrology and water resources management, from an esteemed institution in Iran. His academic journey includes both Bachelor’s and Master’s degrees in Civil Engineering, where he developed a solid foundation in fluid dynamics, hydrology, and structural engineering. Dr. Fard Moradinia has continually expanded his expertise through advanced research in the application of computational techniques, including machine learning algorithms for solving complex civil engineering problems. His educational background reflects a commitment to both theoretical and practical aspects of civil engineering, preparing him for an impactful academic career in the field.

Experience 

Dr. Sina Fard Moradinia has accumulated a wealth of experience in both academic and research settings. As an Assistant Professor at Islamic Azad University in Tabriz, he teaches and mentors students in civil engineering, with an emphasis on hydrology, water resource management, and advanced computational methods. In addition to his teaching role, he is actively involved in high-impact research projects, collaborating with professionals in the fields of water resources, infrastructure, and construction management. His research spans areas such as flood prediction, water quality management, construction project optimization, and the use of artificial intelligence for infrastructure analysis. Dr. Fard Moradinia has also applied his expertise in industry-focused projects, working with governmental and private organizations to enhance the design and management of civil infrastructure, particularly in dam construction, flood mitigation, and reservoir management.

Awards and Honors

Dr. Sina Fard Moradinia’s research has garnered recognition from various academic and professional institutions. His publications have received multiple citations, attesting to the impact of his work in civil engineering, hydrology, and water resource management. He has been honored with awards for his contributions to research and education, including recognition for excellence in the application of machine learning techniques to civil engineering problems. Dr. Fard Moradinia has been invited to speak at international conferences and serve on editorial boards for leading journals in his field. Additionally, his role as a reviewer for numerous scholarly publications further solidifies his standing as a respected figure in his domain. His collaborative efforts with industry partners have also resulted in several successful projects aimed at improving infrastructure sustainability and management in Iran.

Research Focus

Dr. Sina Fard Moradinia’s research focuses on applying advanced computational techniques to solve pressing issues in civil engineering, particularly in the areas of water resources management, hydrology, and hydraulic engineering. His work explores innovative solutions for flood prediction, aquifer management, and sustainable water usage, with a strong emphasis on integrating machine learning and artificial intelligence. Dr. Fard Moradinia also investigates the optimization of construction projects, particularly in the context of dam and reservoir management, where he applies Building Information Modeling (BIM) and system dynamics to improve project efficiency and reduce risks. Another key area of his research is the analysis of environmental factors influencing civil infrastructure, such as the impact of sludge discharge in wastewater systems. Through his work, he aims to advance both the scientific understanding of hydrological systems and the practical tools available for managing water resources and infrastructure projects.

Publication Top Notes

  • “Toward Nearly Zero Energy Building Designs: A Comparative Study of Various Techniques” 🌱🏢
  • “Time and Cost Management of Dam Construction Projects Based on BIM” 💼🏞️
  • “The Role of BIM in Reducing the Number of Project Dispute Resolution Sessions” ⚙️💬
  • “Wavelet-ANN Hybrid Model Evaluation in Seepage Prediction in Nonhomogeneous Earth Dams” 🌊🧠
  • “Optimization of Quantitative and Qualitative Indicators of Construction Projects” ⚙️📊
  • “An Approach for Flood Flow Prediction Using New Hybrids of ANFIS” 🌧️🔮
  • “Forecasting the Level of Aquifers in the Ajab Shir Plain with Different Management Scenarios” 💧🔍
  • “Development of an ANFIS Model for Human Resource Risk Analysis in Construction” 🏗️🧑‍💼
  • “Using Umbrella Arch Method in Design of Tunnel Lining” 🏞️⚒️
  • “Evaluation of Water Diversion Tunnel Lining Using Numerical Model” 🔢🌍
  • “Analysis and Investigation of Hydrological Drought Indicators in Mahenshan” 🌵💧
  • “A Novel Approach to Flood Risk Zonation: Integrating Deep Learning Models with APG” 💻🌊
  • “The Prediction of Precipitation Changes in the Aji-Chay Watershed Using CMIP6 Models” 🌧️📈
  • “Applying Project Knowledge Management to Enhance Time and Cost Efficiency in Water Reservoir Projects” 🕒💡
  • “Developing a System Dynamics Model to Study Human Resource Motivation and Time Productivity” 🕹️💼
  • “Investigating Strategies for Implementing Knowledge Management in Dam Construction Projects” 🏗️📚
  • “Simulation of Delay Factors in Dam Construction Projects with System Dynamics” ⏳🏞️
  • “Mathematical Equations for Grouting Pressure and Intensity in Joint Rocks” 🏔️🛠️
  • “Investigation of Excavation Behavior in Soil Nailing for Construction” 🏗️🌍
  • “Study of the Effects of Sludge Discharge from Water Treatment Plants” ♻️💧

Conclusion

Dr. Sina Fard Moradinia’s exceptional contributions to civil engineering, particularly in water resource management, hydrology, and construction project optimization, make him a strong candidate for the Best Researcher Award. His work, combining cutting-edge computational techniques and practical engineering solutions, addresses some of the most pressing challenges in sustainable development and infrastructure resilience. His innovative approaches in dam construction, flood prediction, and water quality management not only benefit academia but also have significant implications for real-world applications. With his continued focus on advancing research methodologies and expanding his influence both nationally and internationally, Dr. Fard Moradinia has the potential to be a leading figure in shaping the future of civil engineering and environmental management.

Bin Yang – AI for Everything – Best Researcher Award

Bin Yang - AI for Everything - Best Researcher Award

Chongqing University of Posts and Telecommunications - China

AUTHOR PROFILE

SCOPUS

ORCID

🧑‍🏫 ACADEMIC BACKGROUND AND RESEARCH PASSION

Dr. Bin Yang, also known as Sean Bin Yang, is an Assistant Professor at Chongqing University of Posts and Telecommunications. With a deep passion for leveraging big data and artificial intelligence (AI) to address urban challenges, he has been making significant contributions to the field. He is also a member of the Chongqing Key Laboratory of Image Cognition, working closely with Prof. Xinbo Gao.

🎓 EDUCATION AND GLOBAL COLLABORATIONS

Dr. Yang obtained his Ph.D. in Computer Science from Aalborg University in 2022, under the guidance of Prof. Bin Yang and Associate Prof. Jilin Hu. During his doctoral studies, he collaborated with renowned researchers at the Center for Data-Intensive Systems (Daisy) and the Machine Learning Group. He also spent time at the Mila-Quebec AI Institute in Canada, working with Associate Prof. Jian Tang.

📚 PROLIFIC PUBLICATION RECORD

Dr. Yang has authored more than 20 peer-reviewed publications in prestigious international journals and conferences, including KDD, ICML, and TKDE. His work, such as the development of lightweight path representation models, has gathered over 452 citations, with an h-index of 13. His innovative research in data mining, machine learning, and AI continues to push the boundaries of knowledge in these fields.

💡 INNOVATIVE PATENTS AND TECHNOLOGY APPLICATIONS

Dr. Yang's commitment to practical applications of his research is demonstrated by his filing of over 10 patents in China. These patents reflect his dedication to advancing technology through innovation, particularly in the fields of AI-driven solutions for urban and transportation challenges.

🎓 SUPERVISION AND MENTORSHIP

As a dedicated mentor, Dr. Yang has supervised numerous student research projects, including those on construction waste management through AI techniques. His guidance has led to the publication of impactful research articles, helping his students make meaningful contributions to the field of artificial intelligence and urban problem-solving.

🔬 RESEARCH IN AI AND URBAN CHALLENGES

Dr. Yang's research focuses on using AI to tackle complex urban issues, such as waste management, transportation optimization, and infrastructure development. His work in path representation learning, unsupervised learning, and predictive autoscaling has significantly contributed to the advancement of smart city technologies.

🏅 CONFERENCE AND JOURNAL INVOLVEMENT

Dr. Yang is an active member of the research community, serving as a Program Committee member for top conferences like ICML, KDD, and IJCAI. His expertise is frequently sought as a reviewer for leading journals such as IEEE Transactions on Knowledge and Data Engineering and IEEE Transactions on Intelligent Transportation Systems, highlighting his influence in the AI and big data research domains.

NOTABLE PUBLICATION

Title:Extended-state-observer-based double-loop integral sliding-mode control of electronic throttle valve
Authors: Y. Li, B. Yang, T. Zheng, Y. Li, M. Cui, S. Peeta
Journal: IEEE Transactions on Intelligent Transportation Systems
Year: 2015

Title: Unsupervised path representation learning with curriculum negative sampling
Authors: S.B. Yang, C. Guo, J. Hu, J. Tang, B. Yang
Journal: arXiv preprint arXiv:2106.09373

Title: Context-aware path ranking in road networks
Authors: S.B. Yang, C. Guo, B. Yang
Journal: IEEE Transactions on Knowledge and Data Engineering
Year: 2020

Title: Luenberger-sliding mode observer based fuzzy double loop integral sliding mode controller for electronic throttle valve
Authors: B. Yang, M. Liu, H. Kim, X. Cui
Journal: Journal of Process Control
Year: 2018

Title: An extended continuum model incorporating the electronic throttle dynamics for traffic flow
Authors: Y. Li, H. Yang, B. Yang, T. Zheng, C. Zhang
Journal: Nonlinear Dynamics
Year: 2018

Jia Song – Intelligence theory and applications – Best Researcher Award

Jia Song - Intelligence theory and applications - Best Researcher Award

School of Astronautics, Beihang University - China

AUTHOR PROFILE

SCOPUS

🎓 ACADEMIC BACKGROUND AND EXPERTISE

Jia Song earned her B.S. degree in Electrical Engineering and Automation, and Intelligent Systems from Harbin Engineering University in 2005, followed by a Ph.D. in Control Theory and Control Engineering from the same institution in 2009. Her profound expertise in these fields laid the foundation for her future endeavors in advanced control systems and intelligent decision-making.

🏛️ PROFESSOR AND DOCTORAL SUPERVISOR

Currently a Professor and doctoral supervisor at the School of Astronautics, Beihang University, Jia Song plays a crucial role in shaping the next generation of engineers and researchers. Her work focuses on advanced flight control systems and collaborative decision-making, where she mentors doctoral students, guiding them through complex research challenges.

🚀 RESEARCH IN ADVANCED FLIGHT CONTROL

Jia Song's research is centered on the development of advanced flight control systems, particularly in high-stakes scenarios involving high dynamic vehicles. Her studies address critical issues such as control precision and margin adequacy in environments with multiple constraints, such as no-fly zones and high-velocity interceptors, making significant strides in the field of aerospace engineering.

🎯 INNOVATIVE PENETRATION GAME STRATEGY

One of her notable contributions is the investigation of penetration game strategies for high dynamic vehicles. Her innovative approach involves an enhanced artificial potential field method that improves lateral penetration guidance strategies, effectively balancing obstacle avoidance and target reachability. This research not only advances theoretical understanding but also offers practical solutions for real-world applications.

🔧 APPLICATION OF ARTIFICIAL INTELLIGENCE AND PREDICTIVE MODELS

Jia Song integrates advanced artificial intelligence techniques, such as the Kalman filter and Transformer network, into her research. These tools are used to denoise detection information and predict multi-step state outcomes, significantly increasing the success rate of high dynamic vehicles in confronting high-velocity interceptors. Her work exemplifies the fusion of AI with traditional engineering to solve complex problems.

📊 NUMERICAL SIMULATIONS AND VALIDATION

Her research is rigorously validated through numerical simulations, which demonstrate the effectiveness and performance of the proposed penetration game guidance strategies. These simulations confirm the practicality and reliability of her methods, ensuring that they can be applied to real-world scenarios with confidence.

🏆 CONTRIBUTIONS TO AEROSPACE ENGINEERING

Jia Song’s contributions to aerospace engineering, particularly in the areas of flight control and collaborative decision-making, are highly regarded in the academic and professional communities. Her innovative research and commitment to excellence continue to push the boundaries of what is possible in the field of astronautics, making her a leading figure in her domain.

NOTABLE PUBLICATION

ADRC-Based Compound Control Strategy for Spacecraft Multi-Body Separation
Authors: Hu, Y., Wu, M., Zhao, K., Song, J., He, B.
Year: 2023
Journal: Aerospace Science and Technology

Survey on Mission Planning of Multiple Unmanned Aerial Vehicles
Authors: Song, J., Zhao, K., Liu, Y.
Year: 2023
Journal: Aerospace

Time-Cooperative Trajectory Optimization Method for Hypersonic Vehicle Based on Improved Grey Wolf Artificial Potential Field Method
Authors: Teng, B., Xu, X., Song, J.
Year: 2023
Conference: 2023 China Automation Congress (CAC 2023)

Fault Location and Separation Method of Distributed Inertial Measurement Units Based on IAC
Authors: Song, J., Shang, W., Wu, B., Ai, S.
Year: 2023
Conference: 2023 10th International Conference on Dependable Systems and Their Applications (DSA 2023)

Real-Time Trajectory Planning for Hypersonic Vehicle with Dynamic No-Fly Zone Constraints
Authors: Xiaowei, X., Jia, S., Kai, Z., Xindi, T., Yanxue, Z.
Year: 2023
Book Series: Lecture Notes in Electrical Engineering (LNEE)

Fangyu Wu – Artificial Intelligence – Best Researcher Award

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