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

Tom Jackson – Engineering Applications of AI Intelligence – Best Researcher Award

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Tom Jackson - Engineering Applications of AI Intelligence - Best Researcher Award

Loughborough University - United Kingdom

AUTHOR PROFILE

SCOPUS

EARLY CAREER AND ACADEMIC JOURNEY

My career began in 1998 with the founding of an internet company during my PhD in Computer Science. After successfully selling the company in 2001, I transitioned to academia. Since 2013, I have held the position of Professor at Loughborough Business School, where I focus on securing substantial funding for innovative research aimed at shaping future business trends.

RESEARCH AND INNOVATION LEADERSHIP

I am renowned for my expertise in developing pioneering technologies that influence business strategies. Notable innovations include EMOTIVE, a system analyzing social media to predict events, and the Data Carbon Scorecard, assessing AI's impact on CO2 emissions, recognized by the World Economic Forum as pivotal in Digital Decarbonisation.

EDUCATION AND QUALIFICATIONS

I earned my Ph.D. in "The Cost Effectiveness of Electronic Communication" and a BSc (Hons) in Computer Science, both from Loughborough University. As a Fellow of the British Computer Society (FBCS) since 2012, I continue to advance the field through cutting-edge research and strategic leadership.

PROFESSIONAL ENGAGEMENTS AND APPOINTMENTS

My roles extend beyond academia to influencing policy and standards development. I serve as an Independent Scientific Adviser for the Alan Turing Institute, advising on AI technologies and environmental impacts. Additionally, I lead the Technical Working Group for Ethics in the National Digital Twin Programme, setting national standards for ethical digital practices.

RESEARCH FUNDING AND ACHIEVEMENTS

Throughout my career, I have secured significant research funding, notably contributing to a 234% increase in research funding through strategic reorganization. My leadership has been pivotal in establishing and directing numerous EU/UK-funded projects, such as STRESSCAPES and TOXI-Motive, which have advanced understanding in data mining and crisis management.

ACADEMIC LEADERSHIP AND INSTITUTIONAL CONTRIBUTIONS

As Associate Dean Research at Loughborough Business School, I transformed the research environment, enhancing research income and global collaborations. I also directed the Centre for Information Management, elevating its global ranking and impact through pioneering research initiatives.

KEYNOTES AND MEDIA ENGAGEMENT

A sought-after keynote speaker, I have addressed international audiences on topics ranging from digital decarbonisation to AI ethics. My engagements include notable events such as the World Government Summit and collaborations with leading global organizations like AWS and OECD, advocating for sustainable technological advancements.

NOTABLE PUBLICATION

An overview of the test methodology used in current cycling helmet standards and literature

Chemical, biological, radiological and nuclear event detection and classification using ontology interrogation and social media data

Getting on top of work-email: A systematic review of 25 years of research to understand effective work-email activity

Keeping a lower profile: how firms can reduce their digital carbon footprints