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

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)

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)

Micheal Sakr – Structural Health Monitoring – Best Researcher Award

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Micheal Sakr - Structural Health Monitoring - Best Researcher Award

Western University of Ontario - Canada

AUTHOR PROFILE

Scopus

EARLY ACADEMIC PURSUITS

Micheal Sakr commenced his academic journey with a Bachelor of Science in Civil Engineering from the University of Balamand, Lebanon, where he achieved outstanding academic performance, earning a cumulative average of 90.06% and graduating with distinction. He further enriched his academic background with graduate coursework in Structural Engineering at the University of Western Ontario, Canada, where he is currently pursuing a Ph.D. under the supervision of Dr. Ayan Sadhu. His research focus revolves around Digital Twins for Structural Health Monitoring, showcasing his commitment to advancing the field of structural engineering.

PROFESSIONAL ENDEAVORS

Throughout his academic career, Micheal has demonstrated versatility and excellence, serving as a Teaching Assistant at Western University, where he contributed to courses such as Engineering Statics, Advanced Structural Dynamics, and Professional Communication for Engineers. Additionally, his experience as an AutoCAD Drafter equipped him with practical skills in handling structural detailing and drawings for civil engineering projects.

CONTRIBUTIONS AND RESEARCH FOCUS

Micheal's research interests center on Structural Health Monitoring, a field critical for ensuring the safety and integrity of civil infrastructure. His work involves utilizing specialized equipment for structural testing, such as displacement sensors, accelerometers, and acoustic emission sensors, to assess the strength and response of various structural elements. By actively participating in research projects and mentoring initiatives, Micheal demonstrates his dedication to advancing knowledge and addressing real-world engineering challenges.

IMPACT AND INFLUENCE

Micheal's contributions to the field of Structural Health Monitoring have the potential to make a significant impact on civil engineering practices, particularly in ensuring the safety and resilience of infrastructure systems. His involvement in community aid groups and volunteer activities further underscores his commitment to making a positive difference in society.

ACADEMIC CITES

Micheal's academic achievements, including his outstanding performance in coursework and research, have positioned him as a promising scholar in the field of structural engineering. His contributions to research projects and mentorship activities reflect his dedication to academic excellence and professional development.

LEGACY AND FUTURE CONTRIBUTIONS

As Micheal continues to pursue his Ph.D. and engage in research endeavors, he is poised to leave a lasting legacy in the field of Structural Health Monitoring. His passion for innovation, coupled with his strong academic foundation and practical skills, sets the stage for future contributions that will advance the safety, sustainability, and resilience of civil infrastructure worldwide.

NOTABLE PUBLICATION

Visualization of structural health monitoring information using Internet-of-Things integrated with building information modeling.  2023 (4)