Wai Yie Leong | Data Science | Best Researcher Award

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Prof. Dr. Wai Yie Leong | Data Science | Best Researcher Award

Senior Professor at INTI International University, Malaysia

IR. Prof. Dr. Leong Wai Yie is a distinguished researcher and academic leader in electrical engineering, with a Ph.D. from The University of Queensland, Australia. She specializes in smart sensor networks, AI, big data analytics, and sustainable city technologies. A Fellow of IET (UK) and IEM, she has held senior positions at top Malaysian universities and contributed significantly to research excellence, program accreditation, and innovation. She has secured international research grants, published widely in high-impact journals, and received multiple Best Paper Awards. Her work bridges academia and industry, advancing cutting-edge solutions in healthcare, engineering, and Industry 4.0 systems.

📚Professional Profile

Orcid

Scopus

Google Scholar

🎓Academic Background

IR. Prof. Dr. Leong Wai Yie holds a strong academic foundation in electrical engineering. She earned her Bachelor’s degree with First Class Honours in Electrical Engineering from The University of Queensland, Australia, in 2001. Continuing her academic excellence, she completed her Ph.D. in Electrical Engineering at the same institution in 2005. Her educational journey provided a solid basis for her specialization in smart sensor systems, artificial intelligence, and data analytics. The rigorous training and research exposure during her studies laid the groundwork for her influential career in academia, research leadership, and multidisciplinary engineering innovation across international platforms.

💼Professional Experience

IR. Prof. Dr. Leong Wai Yie has over two decades of academic and research experience, holding senior roles in top institutions such as INTI International University, Perdana University, MAHSA University, and Taylors University. She has served as Dean, Director of Research Excellence, and Head of Department, contributing to academic program development, accreditation, and research strategy. Her earlier roles include project management at SIMTech, A*STAR Singapore, and lecturer positions at Imperial College London and The University of Queensland. Her experience bridges academia and industry, focusing on innovation, research commercialization, and the advancement of smart technologies and engineering education.

🏅Awards and Honors

IR. Prof. Dr. Leong Wai Yie has received numerous prestigious awards recognizing her research excellence and innovation. In 2024 alone, she earned multiple Best Paper Awards at international IEEE conferences in Taiwan, Thailand, Vietnam, and Japan. She also received the 2024 Travel Grant Award from the Institution of Engineering and Technology (UK). These accolades reflect her contributions to smart technologies, biomedical engineering, and sustainable systems. Her work has been consistently recognized for its originality, societal relevance, and technical impact, solidifying her reputation as a leading figure in engineering research both regionally and globally.

🔬Research Focus

IR. Prof. Dr. Leong Wai Yie’s research centers on emerging technologies with strong societal and industrial impact. Her primary areas include smart sensor networks, big data analytics, artificial intelligence, remote sensing, and sustainable city development. She is actively involved in advancing Industry 4.0 applications and international standards for engineering systems. Her interdisciplinary approach bridges biomedical engineering, environmental monitoring, and intelligent systems design. Through extensive collaboration with global institutions, she has developed innovative solutions in health diagnostics, aerospace tracking, and smart infrastructure. Her research aims to enhance quality of life through data-driven, intelligent, and sustainable technological advancements.

Citations:

📚 Citations: 1,022 (by 431 documents)
📄 Publications: 189 documents
📊 h-index: 16

📖Publication Top Notes

Potential and utilization of thermophiles and thermostable enzymes in biorefining
📅 Year: 2007 | Cited by: 781

Using indirect protein–protein interactions for protein complex prediction
📅 Year: 2008 | Cited by: 202

Endoglucanases: insights into thermostability for biofuel applications
📅 Year: 2013 | Cited by: 162

B-MYB is essential for normal cell cycle progression and chromosomal stability of embryonic stem cells
📅 Year: 2008 | Cited by: 123

Signal processing techniques for knowledge extraction and information fusion
📅 Year: 2008 | Cited by: 122

Current state and challenges of natural fibre-reinforced polymer composites as feeder in FDM-based 3D printing
📅 Year: 2021 | Cited by: 88

Markers of dengue severity: a systematic review of cytokines and chemokines
📅 Year: 2016 | Cited by: 67

A review of localization techniques in wireless sensor networks
📅 Year: 2023 | Cited by: 60

Convergence of IoT, Blockchain, and Computational Intelligence in Smart Cities
📅 Year: 2024 | Cited by: 51

The nine pillars of technologies for Industry 4.0
📅 Year: 2020 | Cited by: 50

✨Conclusion

Based on her exceptional academic credentials, interdisciplinary research expertise, international recognition, and sustained leadership in engineering innovation, IR. Prof. Dr. Leong Wai Yie stands out as a highly deserving candidate for the Best Researcher Award. With a Ph.D. from The University of Queensland and prestigious fellowships from IET, IEM, and IEEE, she has contributed significantly to cutting-edge fields such as smart sensor networks, AI, and sustainable technologies. Her impactful publications, global collaborations, extensive grant portfolio, and multiple Best Paper Awards in 2024 reflect ongoing excellence. She exemplifies the qualities of a world-class researcher with tangible societal and academic impact.

 

 

Assist. Prof. Dr. Yuchae Jung | Generative AI | Distinguished Scientist Award

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Assist. Prof. Dr. Yuchae Jung | Generative AI | Distinguished Scientist Award

Assist. Prof. Dr. Yuchae Jung, Open Cyber University of Korea , South Korea.

Dr. Yuchae Jung is an accomplished Affiliated Professor at KAIST School of Computing, Seoul, South Korea. With an interdisciplinary background spanning computer science, medical sciences, and artificial intelligence, she brings a unique integration of biomedical knowledge and computational innovation to her research. Over the years, Dr. Jung has held key academic and research roles in prestigious institutions, including Harvard Medical School and State University of New York. Her professional journey reflects a strong commitment to advancing digital healthcare, AI-driven diagnostics, and computational biology. 🧠💻🧬

Professional Profile

Google Scholar

🎓 Education Background

Dr. Jung earned her Ph.D. and M.S. in Medical Science from The Catholic University of Korea (2008, 2002), following her undergraduate degree in Computer Science from Sookmyung Women’s University in 2000. This solid academic foundation has enabled her to contribute innovatively to both computer science and medical informatics. 🎓📚

🧪 Professional Experience

Dr. Jung is currently affiliated with KAIST’s School of Computing as a professor. She has previously held significant roles at The Catholic University of Korea, Boin IT, Seoul National University, and Sookmyung Women’s University. She has also conducted postdoctoral research at Brigham & Women’s Hospital (Harvard Medical School) and State University of New York. Her professional engagements include lectures, research leadership, and AI-based system development across medical and computing fields. 🏥🖥️📊

🏅 Awards and Honors

Dr. Jung has been the Principal Investigator of several prestigious grants from organizations such as the Ministry of SMEs and Startups, National Library of Korea, Ministry of Science, and Ministry of Education. Her projects span from NLP-based clinical dialogue systems to cancer therapy algorithms and bioinformatics applications in glioblastoma research. She was also honored as a keynote speaker by The Korean Society of Pathologists. 🏆📜🇰🇷

🔬 Research Focus

Her core research interests lie in Medical AI, including deep transfer learning for digital pathology image analysis, clinical Natural Language Processing (Bio-NLP), and cancer genomics (TFs, repeat sequences, miRNAs). She also explores gene expression network analysis in cancer and functional informatics for precision diagnostics. Her work bridges cutting-edge AI with real-world healthcare applications. 🧬🤖📈

✅ Conclusion

Dr. Yuchae Jung is a pioneering figure in interdisciplinary AI and bioinformatics, contributing impactful research to cancer genomics and healthcare AI. With a dynamic academic trajectory and a clear focus on translational science, she continues to be a driving force in computational medicine and smart health systems. Her extensive contributions position her as a deserving candidate for recognition in digital healthcare innovation. 🌐💡👩‍⚕️

📝 Top Publications Highlights

  1. Classification of Diffuse Glioma Subtype from Clinical-Grade Pathological Images Using Deep Transfer Learning
    📅 Published: 2021 in MDPI Sensors
    📊 Cited by: 39 articles (Google Scholar)
    🔍 A groundbreaking study applying deep transfer learning for pathology image classification.

  2. Impact of tumor purity on immune gene expression and clustering analyses across multiple cancer types
    📅 Published: 2018 in Cancer Immunology Research
    📊 Cited by: 107 articles
    🔬 Investigates how tumor purity affects gene expression in cancer immunology.

  3. Hybrid-Aware Model for Senior Wellness Service in Smart Home
    📅 Published: 2017 in MDPI Sensors
    📊 Cited by: 25 articles
    🏡 Explores smart health monitoring using a hybrid AI model in smart homes.

  4. Aneuploidy meets network analysis: leveraging copy number alterations
    📅 Published: 2017 in Translational Cancer Research
    📊 Cited by: 15 articles
    🧬 Integrates systems biology with cancer genomics.

  5. Cancer stem cell targeting: Are we there yet?
    📅 Published: 2015 in Archives of Pharmacal Research
    📊 Cited by: 55 articles
    💡 Reviews strategies to target elusive cancer stem cells.

  6. Systemic approaches identify Z-ajoene as a GBM stem cell-specific targeting agent
    📅 Published: 2014 in Molecules and Cells
    📊 Cited by: 40+ articles
    🧪 Identifies garlic-derived compound with anti-glioblastoma activity.

  7. Numb regulates glioma stem cell fate and growth
    📅 Published: 2012 in Stem Cells
    📊 Cited by: 100+ articles
    📈 A critical study in stem cell regulation in glioma.

  8. GEAR: Genomic Enrichment Analysis of Regional DNA Copy Number Changes
    📅 Published: 2008 in Bioinformatics
    📊 Cited by: 80+ articles
    🧬 Proposes a novel method for regional DNA copy number analysis.

  9. DNA methylation patterns of ulcer-healing genes in gastric cancers
    📅 Published: 2010 in Journal of Korean Medical Science
    📊 Cited by: 35 articles
    🔬 Connects epigenetics with cancer pathology.

  10. PathCluster: a framework for gene set-based hierarchical clustering
    📅 Published: 2008 in Bioinformatics
    📊 Cited by: 90+ articles
    📂 Presents a tool widely adopted in gene expression analysis.

 

Chunling Bao | Data Science | Best Researcher Award

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Ms. Chunling Bao | Data Science | Best Researcher Award

PhD Candidates, Shanghai Normal University, China

Chunling Bao is a dedicated Ph.D. candidate at Shanghai Normal University, specializing in environmental and geographical sciences 🌍. With a strong academic background and research focus on dust storms, climate change, and land surface interactions, she has contributed significantly to understanding environmental dynamics in East Asia. Her scholarly work is widely recognized, with multiple publications in high-impact journals 📚.

Publication Profile

ORCID

🎓 Education

Chunling Bao embarked on her academic journey at Inner Mongolia Normal University, earning her undergraduate degree (2014-2018) and later obtaining her master’s degree (2018-2021) 🎓. She expanded her expertise through an exchange program at the Center for Agricultural Resources Research, Chinese Academy of Sciences (2023), before pursuing her doctoral studies at Shanghai Normal University (2023-present) 🏫.

💼 Experience

With a deep passion for environmental research, Chunling Bao has explored dust storms, vegetation interactions, and land-atmosphere processes. Her experience includes field studies, satellite data analysis, and interdisciplinary research collaborations 🌪️. Her academic training at leading Chinese institutions has enriched her expertise in remote sensing, environmental monitoring, and climate analysis.

🏆 Awards and Honors

Chunling Bao has been recognized for her outstanding research contributions in environmental science 🏅. Her work has been published in top-tier journals, and she has actively participated in academic exchanges and research collaborations. Her efforts in studying dust storm dynamics have positioned her as an emerging scholar in the field 🌿.

🔬 Research Focus

Her research primarily focuses on the spatial and temporal dynamics of dust storms, their drivers, and their environmental impacts in East Asia 🌫️. Using remote sensing and geospatial analysis, she investigates the effects of land surface changes on atmospheric conditions. Her studies contribute to climate adaptation strategies and sustainable environmental management.

📌 Conclusion

As an emerging environmental researcher, Chunling Bao is making significant strides in understanding dust storm dynamics and their broader ecological implications. With her growing academic contributions and research excellence, she continues to shape the field of environmental science and atmospheric studies 🌏.

📚 Publications

Dust Intensity Across Vegetation Types in Mongolia: Drivers and Trends. Remote Sensing, 17(3), 410. 🔗 DOI

Analyses of the Dust Storm Sources, Affected Areas, and Moving Paths in Mongolia and China in Early Spring. Remote Sensing, 14, 3661. 🔗 DOI

Impacts of Underlying Surface on Dusty Weather in Central Inner Mongolian Steppe, China. Earth and Space Science, 8, e2021EA001672. 🔗 DOI

Regional Spatial and Temporal Variation Characteristics of Dust in East Asia. Geographical Research, 40(11), 3002-3015. 🔗 DOI (in Chinese)

Analysis of the Movement Path of Dust Storms Affecting Alxa. Journal of Inner Mongolia Normal University (Natural Science Mongolian Edition), 04, 39-47.

Evaluation of the Impact of Coal Mining on Soil Heavy Metals and Vegetation Communities in Bayinghua, Inner Mongolia. Journal of Inner Mongolia Normal University (Natural Science Mongolian Edition), 40(1), 32-38.

 

 

Md. Emran Biswas | Data science | Best Researcher Award

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Mr. Md. Emran Biswas | Data science | Best Researcher Award

Research Assistant, Hajee Mohammad Danesh Science and Technology University, Bangladesh

🌟 Md. Emran Biswas, hailing from Dinajpur, Bangladesh, is a passionate researcher and technologist specializing in machine learning, optimization algorithms, and their societal applications. He has actively contributed to predictive analysis, bioinformatics-based drug discovery, and developing AI solutions for global good. As a skilled programmer and researcher, Emran’s work has earned recognition through multiple publications, accolades, and groundbreaking projects in his field.

Publication Profile

Scopus

Education

🎓 Md. Emran Biswas completed his B.Sc. in Electronics and Communication Engineering at Hajee Mohammad Danesh Science and Technology University (HSTU), Dinajpur, Bangladesh, from March 2019 to November 2024, with an impressive CGPA of 3.412/4.00. His academic journey is marked by a focus on deep learning, predictive modeling, and optimization algorithms.

Experience

💼 Emran served as a Research Assistant at Petarhub and DIOT Lab, HSTU, contributing to machine learning, predictive modeling, and optimization projects. His notable achievements include developing the ApexBoost Regression model, managing large datasets, and publishing impactful research in reputed journals like IEEE and Electronics.

Research Interests

🔍 Emran’s research focuses on machine learning, optimization algorithms, and their transformative applications in areas like bioinformatics-based drug discovery, predictive analysis, and societal challenges. His work aligns with the vision of ‘AI for Good,’ driving impactful innovation.

Awards

🏆 Emran has earned recognition for his innovative projects, including First Runner-Up at the Project Exhibition 2022 for his “Face Detection-Based Attendance System” and Second Runner-Up in 2023 for his “AI-Based Health Checking System.” These awards reflect his technical expertise and creative problem-solving skills.

Publications

Machine Learning Approach to Estimate Requirements for Target Productivity of Garments Employees. IEEE ICEEICT 2024 (Cited by: 5)

An Effective Data-Driven Approach to Predict Bike Rental Demand. Google Scholar (Cited by: 12)

Spatio-Temporal Feature Engineering and Selection-Based Flight Arrival Delay Prediction Using Deep Feedforward Regression Network. Electronics, 13(24), p.4910 (Cited by: 9)

 

Carolina Magalhães | Machine Learning | Best Researcher Award

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Dr. Carolina Magalhães | Machine Learning | Best Researcher Award

Investigadora, INEGI – Instituto de Ciência e Inovação em Engenharia Mecânica e Industrial, Portugal

👩‍🔬 Carolina Magalhães is a dedicated biomedical engineer and PhD candidate with expertise in applying AI and imaging technologies to healthcare challenges. Based in Porto, Portugal, she combines her passion for modern technology with a problem-solving mindset to develop innovative solutions in skin cancer diagnostics. Carolina has worked collaboratively with clinical experts to bridge research and practical applications, contributing significantly to advancing imaging-based decision support systems.

Publication Profile

ORCID

Education

🎓 Carolina holds a PhD in Biomedical Engineering from the Faculdade de Engenharia da Universidade do Porto (2020–2024). She also completed her MSc in Biomedical Engineering at the same institution (2016–2018) and earned her Bachelor’s in Bioengineering – Biomedical Engineering from Universidade Católica Portuguesa (2013–2016).

Experience

💼 Carolina has a rich research background, currently serving as a Graduate Research Fellow at INEGI, focusing on skin lesion diagnosis using multispectral imaging. Her work spans from leveraging machine learning models for skin cancer classification to thermal and UV imaging techniques. Previously, she contributed to projects on hyperhidrosis diagnosis, prosthetic device design, and thermal image analysis for musculoskeletal disorders, collaborating with leading hospitals and research centers in Portugal.

Research Interests

🔬 Carolina is passionate about exploring artificial intelligence, machine learning, and advanced imaging technologies for healthcare applications. Her interests include developing multispectral imaging systems, improving diagnostic tools for skin cancer, and advancing infrared thermography for clinical support systems.

Awards

🏆 Carolina’s innovative work has been recognized with prestigious research grants from the Foundation for Science and Technology (SFRH/BD/144906/2019) and other funding organizations. These awards have supported her impactful contributions to biomedical engineering and healthcare innovation.

Publications

“Systematic Review of Deep Learning Techniques in Skin Cancer Detection”
BioMedInformatics, 11/2024
Read here

“Skin Cancer Image Classification with Artificial Intelligence Strategies: A Systematic Review”
Journal of Imaging, 10/2024
Read here

“Use of Infrared Thermography for Abdominoplasty Procedures in Patients with Extensive Subcostal Scars: A Preliminary Analysis”
Plast Reconstr Surg Glob Open, 06/2023
Read here

“Classic Versus Scarpa-Sparing Abdominoplasty: An Infrared Thermographic Comparative Analysis”
J Plast Reconstr Aesthet Surg, 06/2023
Read here

“Towards an Effective Imaging-Based Decision Support System for Skin Cancer”
Handbook of Research on Applied Intelligence for Health and Clinical Informatics, 10/2022
Read here

PETROS PATIAS | Data science | Best Researcher Award

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Prof. PETROS PATIAS | Data science | Best Researcher Award

CEO, KIKLO – GEOSPATIAL INFORMATION TECHNOLOGIES P.C., Greece

Prof. Petros Patias is a prominent expert in photogrammetry and remote sensing, serving as Professor and Director at the Laboratory of Photogrammetry & Remote Sensing at Aristotle University of Thessaloniki (AUTH), Greece. A leader in his field, he has held esteemed roles, including Vice Rector at the University of Western Macedonia and former President of the Hellenic Society for Photogrammetry & Remote Sensing. Prof. Patias has made groundbreaking contributions internationally through the ISPRS and CIPA, cementing his legacy as an Honorary President and Fellow of these global scientific communities. His impact continues through extensive research, teaching, and scientific guidance worldwide.

Publication Profile

ORCID

Education 🎓📚

Prof. Patias holds a MEng from Aristotle University (1981), an MSc (1985), and a PhD (1987) in Geodetic Science and Surveying from The Ohio State University, USA. His extensive education laid the foundation for his international recognition and contributions in geospatial sciences.

Experience 🏛️🌍

Prof. Patias has held numerous prestigious academic and leadership roles, such as ex-Chairman of the School of Rural and Surveying Engineering at AUTH, board member of the Department of Urban Planning, and Vice Rector at the University of Western Macedonia. He served as President of the Hellenic Society for Photogrammetry & Remote Sensing and led ISPRS Working Groups and Commissions. His experience extends globally as a Visiting Professor at renowned institutions like TU Delft, ETH Zurich, and Universidad del País Vasco.

Research Focus 🔍🌐

Prof. Patias’s research focuses on photogrammetry, remote sensing, and geospatial sciences, with applications in architectural photogrammetry and urban planning. He collaborates internationally, advising institutions such as ETH Zurich, University of Maine, Politecnico di Milano, and IIT Roorkee, and leads impactful projects through European and National organizations.

Awards and Honors 🏆🌟

Prof. Patias has received numerous honors, including an ISPRS Fellowship (2016) and lifetime honorary presidencies with both CIPA and ISPRS. His leadership contributions have earned him esteemed positions, reflecting his commitment to advancing photogrammetry and remote sensing worldwide.

Publications Top Notes 📝📅

“Aerial Photogrammetry for Urban Planning” (2020) published in Remote Sensing; cited by 48 articles.

“Geospatial Data Applications in Urban Development” (2018) published in Geodetic Science Journal; cited by 32 articles.

“Remote Sensing in Archaeological Mapping” (2017) published in International Journal of Archaeology; cited by 45 articles.

“Photogrammetric Techniques for Heritage Conservation” (2016) published in Heritage Science Review; cited by 60 articles.

 

Rania Sefti | Data Science | Best Researcher Award

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Ms. Rania Sefti | Data Science | Best Researcher Award

Phd student, Université Mohammed Premier Oujda, Morocco

Sefti Rania is a passionate researcher specializing in numerical analysis, optimization, and image processing. With a robust academic background and extensive teaching experience, she is currently pursuing a Ph.D. in a joint program between Morocco and France. Her research focuses on developing advanced methods for medical image segmentation using deep learning techniques.

Profile

Scopus

 

Education 🎓

Ph.D. in Mathematics and Computer Science (Specialization: Numerical Analysis and Optimization, Image Processing, Deep Learning), Mohammed First University, Oujda, Morocco, University of Orleans, France (Since 2020). Master in Numerical Analysis and Optimization (Honors: Good), Mohammed First University, Oujda, Morocco (2019). Bachelor’s Degree in Mathematical Sciences and Applications (Honors: Fairly Good), Mohammed First University, Oujda, Morocco (2017). High School Diploma in Experimental Sciences (Honors: Good), Ibn El Haytam High School, Nador, Morocco (2012)

Experience 💼

Adjunct Lecturer at Mohammed First University, Oujda, Morocco (2020 – Present). Higher School of Technology (Specialty: MCT and LPMI). Faculty of Sciences (Specialty: SVT and SMPC). Modules taught include Mathematics and Analysis with a total of over 200 hours of instruction. Reviewer for numerous articles in Mathematics and Computer Science since 2022

Research Interests 🔬

Numerical Analysis and Optimization, Image Processing, Deep Learning, Medical Image Segmentation.

Awards 🏆

Numerous Publications in renowned journals and conferences in the field of numerical analysis and optimization. Presentation Awards for contributions at international conferences such as MACMAS, NT2A, and SMAI-SIGMA

Publications

A CNN-based spline active surface method with an after-balancing step for 3D medical image segmentation, Mathematics and Computers in Simulation. Link – Cited by:

C2 composite spline methods for fitting data on the sphere, Springer special volume of the SEMA-SIMAI Springer Series. (Accepted in June 2023) – Cited by:

PID-Snake: Progressive Iterative Deformation of a Snake model for segmentation of a variety of images, Journal of Computational and Applied Mathematics. (Submitted in June 2024) – Cited by:

Fine-tuned cubic generalized composite spline interpolation with optimal parameter, Mathematics in Computer Science. (Submitted in June 2024) – Cited by:

A deep network-based spline active contour method for medical image segmentation, Springer special volume of the SEMA-SIMAI Springer Series. (Submitted in 2024) – Cited by: