Mahad Rashid | Machine Learning | Best Researcher Award

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Mr Mahad Rashid | Machine Learning | Best Researcher Award

Senior Analytics Consultant at WorkSafe VIC, Australia

Mahad Rashid is an enthusiastic and skilled Analytics Consultant with a Master’s degree in Data Science from Deakin University. With over six years of experience in data analysis, machine learning, and software engineering, Mahad has a proven track record of developing data-driven solutions to enhance business operations and customer experiences. Proficient in Python, SAS, SQL, and data visualization tools like Power BI and Qlik, he has worked in diverse roles, including Senior Analytics Consultant at WorkSafe Victoria and Research Engineer at the Applied Artificial Intelligence Institute. Mahad is passionate about leveraging data to drive innovation and deliver impactful results. His expertise spans machine learning, deep learning, and statistical analysis, with a strong focus on MLOps and AI deployment. Mahad is also an effective communicator, capable of translating complex technical concepts for non-technical stakeholders.

Professional Profile

Scopus

Education 🎓

Mahad Rashid holds a Master of Data Science from Deakin University, Burwood (2019–2021), where he honed his skills in data analysis, machine learning, and AI. Prior to this, he completed his Bachelor of Software Engineering from the National University of Sciences and Technology, Pakistan (2014–2018), gaining a strong foundation in programming, software development, and data structures. Throughout his academic journey, Mahad demonstrated a keen interest in applying data science to solve real-world problems. He has also pursued additional certifications, including Getting Started with SAS Programming and Git and GitHub on Coursera (2024), showcasing his commitment to continuous learning and professional development.

Experience 💼

Mahad Rashid has a rich professional background spanning over six years. As a Senior Analytics Consultant at WorkSafe Victoria (2023–Present), he excels in data extraction, cleaning, and machine learning using Python and SQL. He also mentors junior consultants and creates insightful dashboards using Power BI. Previously, as a Research Engineer at the Applied Artificial Intelligence Institute, Deakin (2021–2023), he developed and deployed ML models, applied MLOps principles, and collaborated on AI research. Earlier, as a Software Engineer at CureMD, Pakistan (2018–2019), he designed machine learning applications and advanced data visualizations. Mahad’s expertise lies in leveraging data to drive innovation, improve decision-making, and deliver impactful solutions across industries.

Awards and Honors 🏆

While specific awards and honors are not explicitly mentioned in the provided profile, Mahad Rashid’s contributions to data science and AI research are evident through his publications and professional achievements. His work on high-voltage lithium cathode materials, published in ACS Applied Energy Materials (2024), highlights his involvement in cutting-edge research. Additionally, his role in mentoring junior consultants and leading analytics projects at WorkSafe Victoria underscores his recognition as a skilled and reliable professional. Mahad’s commitment to continuous learning, evidenced by his certifications in SAS and Git, further reflects his dedication to excellence in the field of data science.

Research Focus 🔍

Mahad Rashid’s research focuses on applying machine learning, deep learning, and AI to solve complex problems across various domains. His work includes developing and deploying ML models for classification, regression, and image detection, as well as applying MLOps principles to streamline data science workflows. He has also contributed to research on high-voltage lithium cathode materials using Bayesian optimization and first-principles studies, showcasing his interdisciplinary expertise. Mahad is passionate about leveraging data-driven approaches to improve business operations, enhance customer experiences, and drive innovation. His research interests extend to data visualization, statistical analysis, and AI-driven decision-making, with a strong emphasis on delivering practical, impactful solutions.

Publication Top Notes 📚

  1. High-Voltage, High Capacity Aluminum-Rich Lithium Cathode Materials: A Bayesian Optimization and First-Principles Study – ACS Applied Energy Materials, 2024.

Conclusion 🌟

Mahad Rashid is a highly skilled and passionate data science professional with a strong academic background and extensive industry experience. His expertise in data analysis, machine learning, and AI, combined with his ability to communicate complex ideas effectively, makes him a valuable asset to any organization. Mahad’s commitment to innovation, continuous learning, and delivering impactful results positions him as a leader in the field of data science and analytics.

 

Zihang Li – Pile foundation – Best Researcher Award

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Zihang Li - Pile foundation - Best Researcher Award

Wuhan University of Technology - China

AUTHOR PROFILE

ORCID

ZIHANG LI: MARINE GEOTECHNICAL ENGINEER 🌊

Zihang Li is a dedicated researcher in the field of marine geotechnical engineering, having recently completed his MEng degree in Civil and Hydraulic Engineering at Wuhan University of Technology in 2024. His current research focuses on the modeling and simulation of marine geotechnical systems, with particular emphasis on the calculation of pile foundation bearing capacity and saturated soil seepage. Zihang is passionate about advancing knowledge in this essential area of civil engineering, aiming to contribute innovative solutions to industry challenges.

EDUCATION JOURNEY 🎓

Zihang's academic journey began at Chongqing University of Science and Technology, where he earned his Bachelor’s Degree in Architectural Engineering in 2021. This foundation in engineering principles provided him with critical skills and knowledge that he has built upon during his master’s studies. His educational experiences have equipped him with a solid grounding in both theoretical and practical aspects of civil engineering.

RESEARCH INTERESTS 🔍

At Wuhan University of Technology, Zihang’s research interests have developed into a focused exploration of marine geotechnical engineering. He is particularly interested in the complexities of pile foundation design and the behavior of saturated soils under various conditions. His work aims to enhance the understanding of these systems, providing valuable insights for future construction and engineering projects in marine environments.

PUBLICATIONS AND CONTRIBUTIONS 📝

Zihang recently published a journal article titled "Performance Analysis of Pile Group Installation in Saturated Clay," showcasing his research findings and contributing to the body of knowledge in his field. This publication highlights his ability to conduct significant research and disseminate findings that can aid in both academic and practical applications. His work emphasizes the importance of rigorous analysis in marine geotechnical engineering.

PROFESSIONAL ASPIRATIONS 🚀

Looking ahead, Zihang is eager to further his research career and contribute to advancements in marine geotechnical engineering. He aspires to collaborate with industry professionals and researchers to develop innovative techniques that enhance the design and implementation of marine structures. His goal is to make a meaningful impact on the field through his research and practical applications.

LIFELONG LEARNER 📖

Zihang embodies the spirit of a lifelong learner, consistently seeking opportunities to expand his knowledge and skills. He recognizes the dynamic nature of engineering and the importance of staying updated with the latest advancements and technologies. This commitment to continuous improvement drives him to engage with new ideas and methodologies, ensuring that he remains at the forefront of his field.

COMMITMENT TO INNOVATION 💡

In his pursuit of excellence, Zihang is committed to finding innovative solutions to complex engineering problems. He believes that creativity and analytical thinking are essential in addressing the challenges faced in marine geotechnical engineering. By fostering an innovative mindset, Zihang aims to contribute significantly to the advancement of engineering practices and the sustainable development of marine infrastructure.

NOTABLE PUBLICATION

Title: Performance Analysis of Pile Group Installation in Saturated Clay
Authors: Wenlin Xiong, Zihang Li, Dan Hu, Fen Li
Journal: Applied Sciences
Year: 2024

Clement Asare – Data and Predictive analytics – Excellence in Research

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Clement Asare - Data and Predictive analytics - Excellence in Research

Kwame Nkrumah University of Science and Technology - Ghana

AUTHOR PROFILE

SCOPUS

CLEMENT ASARE: MACHINE LEARNING ENTHUSIAST 📊

Clement Asare is a dedicated statistical machine learning enthusiast, passionate about utilizing advanced statistical, actuarial, and machine learning techniques to tackle complex real-world challenges. With a solid foundation in actuarial science, he seeks opportunities to collaborate with academics worldwide, enhancing his skills and knowledge in statistical machine learning applications across diverse sectors.

EDUCATION BACKGROUND 🎓

Clement earned his Bachelor of Science in Actuarial Science from Kwame Nkrumah University of Science and Technology (KNUST) in Kumasi, Ghana, graduating with First-Class honors. This rigorous program equipped him with strong analytical and quantitative skills, laying the groundwork for his future endeavors in statistical and machine learning domains. His academic achievements reflect his commitment to excellence in the field.

PROFICIENCY IN PROGRAMMING 💻

Clement is proficient in several programming languages, including Python, R, and MATLAB, which he utilizes to implement machine learning algorithms and statistical analyses effectively. His programming skills enable him to develop robust models and analyze data efficiently, making him a valuable asset in research and applied settings. This technical expertise supports his goal of solving real-world problems through data-driven insights.

COLLABORATIVE SPIRIT 🌍

Clement actively seeks collaborative opportunities with academic professionals and researchers around the globe. He values the exchange of ideas and knowledge that comes from working with others, believing it enhances understanding and innovation in the field of statistical machine learning. His eagerness to learn from others drives his ambition and growth as a statistician.

PASSION FOR PROBLEM-SOLVING 🔍

At the core of Clement’s pursuits is a passion for solving complex problems. He is motivated by the challenges that arise in various sectors, including finance, healthcare, and technology. By applying his expertise in statistical techniques and machine learning, he aims to develop effective solutions that can significantly impact these fields.

FUTURE ASPIRATIONS 🚀

Looking ahead, Clement is determined to expand his knowledge and skills further, aiming for a career that blends academic research with practical applications of machine learning. His goal is to contribute to innovative projects that harness the power of data for better decision-making and enhanced outcomes in society. Clement is excited about the future and the possibilities that lie ahead in his professional journey.

LIFELONG LEARNER 📖

Clement embodies the spirit of a lifelong learner, continually seeking new knowledge and experiences. He believes that staying current with the latest advancements in machine learning and statistics is crucial for personal and professional growth. His dedication to continuous improvement drives him to explore new challenges and opportunities that further his expertise in the field.

NOTABLE PULICATION

Title: Predictive Analysis on the Factors Associated with Birth Outcomes: A Machine Learning Perspective
Authors: Adebanji, A.O., Asare, C., Gyamerah, S.A.
Journal: International Journal of Medical Informatics
Year: 2024

Title: Assessing the Impact of Climate Variability on Maize Yields in the Different Regions of Ghana — A Machine Learning Perspective
Authors: Gyamerah, S.A., Asare, C., Agbi-Kaeser, H.O., Baffour-Ata, F.
Journal: PLoS ONE
Year: 2024

Title: The Impacts of Global Economic Policy Uncertainty on Green Bond Returns: A Systematic Literature Review
Authors: Gyamerah, S.A., Asare, C.
Journal: Heliyon
Year: 2024

Title: A Critical Review of the Impact of Uncertainties on Green Bonds
Authors: Gyamerah, S.A., Asare, C.
Journal: Green Finance
Year: 2024

Title: Asymmetric Impact of Heterogeneous Uncertainties on the Green Bond Market
Authors: Gyamerah, S.A., Agbi-Kaiser, H.O., Asare, C., Dzupire, N.
Journal: Discrete Dynamics in Nature and Society
Year: 2024

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

Jamin Rahman Jim – Generative AI – Young Scientist Award

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Jamin Rahman Jim - Generative AI - Young Scientist Award

Advanced Machine Intelligence Research Lab - Bangladesh

AUTHOR PROFILE

Scopus

EARLY ACADEMIC PURSUITS

Jamin Rahman Jim's academic journey commenced with a Bachelor of Science degree in Computer Science and Engineering, with a major in Information Systems, from the American International University-Bangladesh. His exceptional academic performance, evidenced by a final grade of 3.96/4.00, was complemented by a thesis focusing on assessing Personalized Federated Learning Algorithms for Pattern Recognition Tasks.

PROFESSIONAL ENDEAVORS

Jamin Rahman Jim has established himself as a dedicated researcher in the field of artificial intelligence and machine learning. His roles as a Research Assistant at Deepchain Labs and subsequently as a Researcher at the Advanced Machine Intelligence Research Lab (AMIR Lab) reflect his commitment to advancing knowledge and contributing to cutting-edge research projects.

CONTRIBUTIONS AND RESEARCH FOCUS

With a focus on artificial intelligence and machine learning, Jamin Rahman Jim has made significant contributions to the field through his publications and projects. His research spans various domains, including the trustworthy metaverse, NLP-based sentiment analysis, deep learning for medical image segmentation, and user authentication and authorization in cybersecurity. Through preprints and published articles, he continues to explore innovative approaches and address challenges in the application of machine learning techniques.

IMPACT AND INFLUENCE

Jamin Rahman Jim's research has garnered attention within the academic community and beyond, as evidenced by his publications in reputable journals and his receipt of prestigious awards and grants. His work on generative AI in medical imaging, fusion-enhanced terrain detection, and explainable AI approaches has the potential to influence the development of AI systems in various domains, including healthcare, autonomous vehicles, and cybersecurity.

ACADEMIC CITES

Jamin Rahman Jim's publications in journals such as IEEE Access, Natural Language Processing Journal, and Computers and Electrical Engineering have been cited by fellow researchers, indicating the relevance and impact of his work. His research on generative AI in medical imaging, personalized federated learning algorithms, and lightweight human activity recognition frameworks has contributed to advancing knowledge in the field of artificial intelligence.

LEGACY AND FUTURE CONTRIBUTIONS

As Jamin Rahman Jim continues his academic and professional journey, his legacy lies in his dedication to advancing the field of artificial intelligence and machine learning. Through his ongoing research projects, publications, and collaborations, he aims to address critical challenges and contribute to the development of innovative AI solutions. His focus on generative AI in medical imaging underscores his commitment to leveraging AI for improved healthcare outcomes and societal impact.

NOTABLE PUBLICATION

Machine learning and deep learning for user authentication and authorization in cybersecurity: A state-of-the-art review 2024

Generative Adversarial Networks (GANs) in Medical Imaging: Advancements, Applications and Challenges 2024

Toward Trustworthy Metaverse: Advancements and Challenges 2023 (4)

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

Samir Khatir – AI for fast prediction – Best Researcher Award

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Samir Khatir - AI for fast prediction - Best Researcher Award

Ho Chi Minh City Open university - Belgium

AUTHOR PROFILE

Google Scholar
Scopus

EARLY ACADEMIC PURSUITS

Dr. Samir Khatir embarked on his academic journey by earning a PhD in Mechanical Engineering from Boumerdes University, Algeria, in collaboration with Centre Val de Loire, France, focusing on damage detection using optimization techniques. He later pursued a second PhD in Civil Engineering at Ghent University, Belgium, specializing in artificial intelligence for fast crack identification in steel plate structures. His academic pursuits reflect a strong foundation in engineering and a commitment to advancing knowledge in his field.

PROFESSIONAL ENDEAVORS

Dr. Samir Khatir has held various prestigious positions, including Technical Manager at Btecch in Brussels, Belgium, and part-time distinguished researcher at CEATS Centre, Ho Chi Minh City Open University, Vietnam. Additionally, he serves as an editor-in-chief and member of the editorial board for several scientific journals, contributing to the dissemination of knowledge in his field. His extensive experience spans research, academia, and industry, showcasing his versatility and expertise.

CONTRIBUTIONS AND RESEARCH FOCUS

Dr. Samir Khatir's research focuses on a wide range of topics, including characterization of metals and composite materials, design optimization, damage identification, static and dynamic tests, machine learning, and tribological analysis in metal contact. He has made significant contributions to projects addressing modal updating and structural health monitoring in metal bridges, fast crack identification using machine learning in steel plates, and impact identification in composite materials. His research underscores his dedication to advancing engineering solutions through innovative methodologies.

IMPACT AND INFLUENCE

Dr. Samir Khatir's work has had a profound impact on the field of engineering, particularly in the areas of structural health monitoring, damage identification, and optimization techniques. His collaborations with prestigious institutions and his role as a visiting researcher and research member highlight his influence and recognition within the global research community. His contributions have contributed to advancements in the understanding and application of artificial intelligence for predictive analysis in engineering structures.

ACADEMIC CITES

Dr. Samir Khatir's research has been widely cited and recognized in the academic community, with numerous publications and collaborations with renowned institutions. His work has been instrumental in shaping the discourse and driving innovation in engineering research, particularly in the application of machine learning techniques for fast prediction and damage identification in structural materials.

LEGACY AND FUTURE CONTRIBUTIONS

As Dr. Samir Khatir continues to excel in his career, his legacy in the field of engineering is poised to grow. His future contributions are expected to further enhance our understanding of structural behavior and advance predictive modeling techniques using artificial intelligence. Through his dedication to research and innovation, he will continue to shape the future of engineering and inspire the next generation of researchers and practitioners.

NOTABLE PUBLICATION

An efficient approach for damage identification based on improved machine learning using PSO-SVM  2022 (82)

YUKI Algorithm and POD-RBF for Elastostatic and dynamic crack identification 2021 (80)