Akmal Jahan Mohamed Abdul Cader | Artificial Intelligence | Best Researcher Award

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Akmal Jahan Mohamed Abdul Cader | Artificial Intelligence | Best Researcher Award

Dr. Akmal Jahan Mohamed Abdul Cader, South Eastern University, Sri Lanka.

Dr. Akmal Jahan Mohamed Abdul Cader is a distinguished academic and researcher currently serving as a Senior Lecturer in Computer Science at the South Eastern University of Sri Lanka. With extensive experience in higher education, he is a Visiting Research Fellow at QUT, Australia. His research interests include artificial intelligence, data science, and document image analysis. Dr. Cader has published numerous high-impact articles and is actively involved in academic development and curriculum design. He is committed to advancing education and research in the field of computer science. 📚💻🌍

Publication Profiles 

Googlescholar

Education and Experience

  • Visiting Research Fellow – QUT Momentum Visiting Fellow, QUT, Australia (2021 – Present) 🎓
  • Senior Lecturer (Computer Science) – South Eastern University of Sri Lanka (2020 – Present) 🏫
  • Sessional Academic – School of Electrical Engineering & Computer Science, QUT (2016 – 2019) 📖
  • Lecturer (Computer Science) – South Eastern University of Sri Lanka (2012 – 2015) 🧑‍🏫
  • Assistant Lecturer – South Eastern University of Sri Lanka (2010 – 2012) 🔍
  • Demonstrator in Computer Science – South Eastern University of Sri Lanka (2009 – 2010) 👨‍🔬

Suitability For The Award

Dr. Mac Akmal Jahan Mohamed Abdul Cader, Senior Lecturer in Computer Science at the South Eastern University of Sri Lanka, is a highly accomplished academic and researcher, making him an exemplary candidate for the Best Researcher Award. With a career spanning over a decade, Dr. Cader has consistently demonstrated leadership in research, teaching, and academic development, particularly in the fields of artificial intelligence, computer science, and digital technologies. His research contributions, coupled with his active involvement in academic service, professional organizations, and international collaborations, solidify his standing as a leading figure in his domain.

Professional Development

Dr. Cader has participated in several professional development programs focused on effective communication, teaching and learning, and project-based learning. He has completed various certifications at QUT, enhancing his skills in pedagogy and curriculum development. His commitment to continuous improvement in education is evident in his active engagement in workshops and training sessions aimed at promoting best practices in teaching. As a Fellow of the Higher Education Academy, he champions high standards in academic instruction and student engagement. 🏅📈📚

Research Focus

Dr. Cader’s research primarily focuses on artificial intelligence, data science, and document image analysis. He explores the synthesis and application of synthetic metals, aiming to develop innovative solutions in electronics and energy storage. His work on TCNQ chemistry has significant implications for biotechnology and medicine, including the construction of electrochemical sensors and drug delivery systems. By synthesizing novel compounds, he contributes to advancements in both theoretical and practical aspects of computer science and materials research. 🔬⚙️🌐

Awards and Honors

  • Senate Honours Award for High Impact Publications – SEUSL (2022 & 2023) 🏆
  • Queensland University of Technology Postgraduate Award (QUTPRA) (2015) 📜
  • Faculty Write Up (FWU) Scholarship – QUT, Australia (2019) 📚
  • Effective Communication in Teaching and Learning – QUT, Australia (2019) 🗣️
  • Foundation of Teaching and Learning – QUT (2018) 🎓

Publication Top Notes 

  • Locating tables in scanned documents for reconstructing and republishing | Cited by: 46 | Year: 2014 📄🔍
  • Plagiarism Detection on Electronic Text based Assignments using Vector Space Model (ICIAfS14) | Cited by: 37 | Year: 2014 📊✏️
  • AntiPlag: Plagiarism Detection on Electronic Submissions of Text Based Assignments | Cited by: 34 | Year: 2014 📄🛡️
  • Plagiarism detection tools and techniques: A comprehensive survey | Cited by: 23 | Year: 2021 🔎📚
  • Fingerprint Systems: Sensors, Image Acquisition, Interoperability and Challenges | Cited by: 11 | Year: 2023 🖐️📷
  • Contactless finger recognition using invariants from higher order spectra of ridge orientation profiles | Cited by: 10 | Year: 2018 ✋📏
  • Accelerating text-based plagiarism detection using GPUs | Cited by: 10 | Year: 2015 ⚡💻
  • Contactless multiple finger segments based identity verification using information fusion from higher order spectral invariants | Cited by: 9 | Year: 2018 🖐️🔗

Prof. Hsin-Yuan Chen | AI Awards | Outstanding Scientist Award

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Prof. Hsin-Yuan Chen | AI Awards | Outstanding Scientist Award

Prof. Hsin-Yuan Chen, Zhejiang University, China

H.Y. J. Chen is an accomplished researcher with expertise spanning multiple fields including bioengineering, materials science, and guidance system technologies. Holding a Web of Science ResearcherID (JSL-7102-2023) , Chen has an impressive H-index of 58, with over 11,000 citations accumulated from works published between January 2000 and March 2024. Some of Chen’s notable contributions include studies on biochar anodes for lithium-ion batteries, computational fluid dynamics (CFD) analysis of cormorant takeoff mechanisms, and innovations in van der Waals semiconductor photodetectors. Chen’s interdisciplinary work also extends into preprints and collaboration on machine learning applications in conformal field theories.

Professional Profile:

Scopus

Suitability Summary for Research for Outstanding Scientist Award

Researcher: H.Y. J. Chen

Summary:

H.Y. J. Chen stands out as a highly suitable candidate for the Research for Outstanding Scientist Award due to his exceptional contributions and interdisciplinary expertise across multiple scientific domains. Chen’s research spans bioengineering, materials science, and guidance system technologies, showcasing a profound impact on these fields.

🎓Education:

H.Y. J. Chen is an accomplished researcher with expertise in bioengineering, materials science, and guidance system technologies. Chen earned both his Master’s and Bachelor’s degrees, as well as a Ph.D., from National Cheng Kung University, Taiwan.

Publication Top Notes:

  • Protective Effects of an Oligo-Fucoidan-Based Formula Against Osteoarthritis Development via iNOS and COX-2 Suppression Following Monosodium Iodoacetate Injection
    • Citations: 0
  • Hinokitiol Inhibits Breast Cancer Cells In Vitro Stemness-Progression and Self-Renewal with Apoptosis and Autophagy Modulation via the CD44/Nanog/SOX2/Oct4 Pathway
    • Citations: 1
  • Alleviating 3-MCPD-Induced Male Reproductive Toxicity: Mechanistic Insights and Resveratrol Intervention
    • Citations: 1
  • Hinokitiol as a Modulator of TLR4 Signaling and Apoptotic Pathways in Atopic Dermatitis
    • Citations: 1
  • Integrating Explainable Artificial Intelligence and Blockchain to Smart Agriculture: Research Prospects for Decision Making and Improved Security
    • Citations: 7

 

 

Ms. Hind MEZIANE | Artificial Intelligence | Best Scholar Award

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Ms. Hind MEZIANE | Artificial Intelligence | Best Scholar Award 

Ms. Hind MEZIANE, ACSA Lab, Faculty of Sciences, University Mohammed First, Oujda, Morocco

Hind Meziane is a dedicated researcher and Ph.D. candidate in Computer Science at the ACSA Laboratory, Department of Mathematics, Faculty of Sciences, Mohammed Premier University, Oujda, Morocco. Her academic journey began with a Baccalaureate in Science (Science Mathematics Option B) from Mehdi Ben Berka High School in Oujda in 2012. She then pursued higher education at Mohammed Premier University, obtaining a DEUG in Mathematics and Computer Science (2012-2014), a LICENSE in Mathematics and Computer Science (2014-2016), and a Specialized Master’s in Computer Engineering with Honors (2017-2019).

Professional Profile:

Summary of Suitability for Best Scholar Award

Hind Meziane is a highly accomplished researcher whose work primarily focuses on the security of Internet of Things (IoT) systems. She is currently pursuing a Ph.D. in Computer Science at Mohammed Premier University and has an impressive academic background, including a specialized master’s degree in Computer Engineering and a bachelor’s degree in Mathematics and Computer Science. Her research contributions are well-documented through various publications in reputable international journals and conference proceedings.

🎓 Education:

  • 2019-Present: Doctorate (PhD) in Computer Science at Mohammed Premier University, Faculty of Sciences, Oujda.
  • 2017-2019: Specialized Master in Computer Engineering, with Honors, at Mohammed Premier University, Faculty of Sciences, Oujda.
  • 2014-2016: LICENSE in Mathematics and Computer Science from Mohammed Premier University, Faculty of Sciences, Oujda.
  • 2012-2014: DEUG in Mathematics and Computer Science from Mohammed Premier University, Faculty of Sciences, Oujda.
  • 2011-2012: Baccalaureate in Science, Mathematics Option B from Mehdi Ben Berka High School, Oujda.

Publication top Notes:

A survey on performance evaluation of artificial intelligence algorithms for improving IoT security systems

A Comparative Study for Modeling IoT Security Systems

Modeling IoT based Forest Fire Detection System with IoTsec

A Study of Modelling IoT Security Systems with Unified Modelling Language (UML)

Classifying security attacks in iot using ctm method

Internet of Things: Classification of attacks using CTM method

Dr. Xianchao Zhu | Reinforcement Learning | Best Researcher Award

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Dr. Xianchao Zhu | Reinforcement Learning | Best Researcher Award 

Dr. Xianchao Zhu, School of Artificial Intelligence and Big Data/Henan University of Technology, China

Dr. Xianchao Zhu is a Lecturer at the School of Artificial Intelligence and Big Data at Henan University of Technology, a position he has held since 2022. He completed his Ph.D. in Physics at the Institute of Fundamental and Frontier Sciences, University of Electronic Science and Technology of China, where his research focused on “Abstraction-based Reinforcement Learning Algorithms and its Quantization.” Prior to his doctoral studies, Dr. Zhu earned a Master of Science in Computer Architecture from the School of Computer, Central China Normal University, with a thesis on “Research on Dimensionality Reduction Visualization Method of High-Dimensional Biological Data Based on Gradient Descent and Adaptive Learning.” His academic interests span artificial intelligence, reinforcement learning, and high-dimensional data analysis.

Professional Profile:

 

ORCID

Education

  • Ph.D. in Physics
    Institute of Fundamental and Frontier Sciences, University of Electronic Science and Technology of China
    2018 – 2022
    Thesis Title: Abstraction-based Reinforcement Learning Algorithms and its Quantization.
  • M.Sc. in Computer Architecture
    School of Computer, Central China Normal University
    2015 – 2018
    Thesis Title: Research on Dimensionality Reduction Visualization Method of High-Dimensional Biological Data Based on Gradient Descent and Adaptive Learning.

Employment History

  • Lecturer
    School of Artificial Intelligence and Big Data, Henan University of Technology
    2022 – Present

Publication top Notes:

Salience Interest Option: Temporal abstraction with salience interest functions

Generalization Enhancement of Visual Reinforcement Learning through Internal States

Efficient relation extraction via quantum reinforcement learning

MDMD options discovery for accelerating exploration in sparse-reward domains