Narmilan Amarasingam | Artificial Intelligence | Best Researcher Award

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Mr. Narmilan Amarasingam | Artificial Intelligence | Best Researcher Award

PhD student, Queensland University of Technology, Australia

Researcher specializing in drone-based remote sensing solutions for environmental and surveillance needs, focusing on precision agriculture and biosecurity. Expertise includes UAV remote sensing, artificial intelligence, and multispectral/hyperspectral image processing. Currently pursuing a PhD in Precision Agriculture at Queensland University of Technology.

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🎓 Education

PhD: Precision Agriculture, Queensland University of Technology (2021 – Present). MSc: Agricultural Engineering, Eastern University, Sri Lanka (2016 – 2018). BSc: Agriculture, Agricultural Engineering, Eastern University, Sri Lanka (2010 – 2015). BIT: Software Engineering, University of Colombo School of Computing, Sri Lanka (2011 – 2015)

🔍 Experience

Research Assistant at Charles Sturt University and Sunshine Coast Council on projects integrating AI and drone technology for environmental monitoring and invasive species detection.

🏆 Awards

QUT/Accelerate Higher Education Development Expansion and Development (AHEAD) World Bank Project Scholarship. Vice Chancellor’s Award for Early Career Researcher, Faculty of Technology, 2022.

🌍 Research Interests

Precision Agriculture, UAV-based Remote Sensing, Multispectral Image Processing, AI, Biosystems Engineering, Environmental Management.

📚 Publications

Co-authored numerous peer-reviewed articles in Q1 and non-Q1 ranking journals on topics related to UAV-based remote sensing and AI applications in agriculture and environmental management.

A review of UAV platforms, sensors, and applications for monitoring of sugarcane crops
Predicting canopy chlorophyll content in sugarcane crops using machine learning algorithms and spectral vegetation indices derived from UAV multispectral imageryDetection of white leaf disease in sugarcane using machine learning techniques over UAV multispectral images
Detection of White Leaf Disease in Sugarcane Crops Using UAV-Derived RGB Imagery with Existing Deep Learning Models
N Amarasingam, F Gonzalez, ASA Salgadoe, J Sandino, K Powell
E-agricultural concepts for improving productivity: A review

Ali Raza | artificial intelligence | Best Researcher Award

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Mr. Ali Raza | artificial intelligence | Best Researcher Award

Lecturer, The University of Lahore, Pakistan

Ali Raza is a dedicated research scholar specializing in data science, known for his expertise in machine learning and deep learning applications. With a strong academic background and extensive professional experience in software development, he has contributed significantly to research in artificial intelligence and health informatics.

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📚 Education:

Ali completed his Bachelor of Science in Computer Science at KFUEIT after graduating from Iqra Degree College with a degree in Pre-Engineering. He further pursued his passion for computer science by earning a Master’s degree in Computer Science from KFUEIT, where his research focused on novel approaches in deep learning for image detection.

💼 Experience:

Ali’s professional journey includes roles as a Research Assistant at KFUEIT, where he published research articles on artificial intelligence. He has also worked as a Desktop App Developer at DexDevs Company and as a Full Stack Python Developer at BuiltinSoft Company, gaining expertise in business application development and machine learning frameworks.

🔬 Research Interests:

Ali’s research interests revolve around data science, particularly in machine learning model optimization, health informatics, and artificial intelligence applications in diverse domains such as pregnancy health analysis and network security.

🏆 Awards:

Ali has contributed significantly to research, evident from his publications and contributions as a peer reviewer for IEEE Access and PLOS ONE, highlighting his recognition in the academic community.

📄 Publications:

Ensemble learning-based feature engineering to analyze maternal health during pregnancy and health risk prediction, Plos one, 2022 (cited 46 times)

A novel deep learning approach for deepfake image detection, Applied Sciences, 2022 (cited 58 times)

Predicting employee attrition using machine learning approaches, Applied Sciences, 2022 (cited 44 times)

A novel methodology for human kinematics motion detection based on smartphones sensor data using artificial intelligence, Technologies, 2023 (cited 23 times)

Novel class probability features for optimizing network attack detection with machine learning, IEEE Access, 2023

JAINUL FATHIMA | Artificial Intelligence | Best Researcher Award

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Dr. JAINUL FATHIMA | Artificial Intelligence | Best Researcher Award

Associate Professor, Francis Xavier Engineering College, India

📘 Dr. A. Jainul Fathima, B.Tech., M.E., Ph.D., is an innovative professor with a strong passion for fostering academic development and success for every student. With 12 years of combined experience in teaching, research, and industry, she excels in implementing technology-based curriculum delivery and assessment tools.

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Scopus

Education🎓

Dr. Fathima holds a Ph.D. in Computational Drug Discovery from Kalasalingam Academy of Research and Education, where her interdisciplinary research focused on developing anti-viral drugs for dengue targets using AI techniques. She earned her M.E. in Computer Science and Engineering from Anna University with an 83% aggregate and a B.Tech. in Information Technology from Anna University with a 75% aggregate.

Experience 🛠️

👩‍🏫 With 12 years of total experience, Dr. Fathima has 6 years of teaching experience, currently serving as an Assistant Professor at Francis Xavier Engineering College. She has previously worked at K.L.N. College of Information Technology, Sethu Institute of Technology, and Kalasalingam University. Her research experience includes 3 years as a UGC Research Fellow and 2 years of teaching and instructing in Qatar. She also has 1 year of industrial experience as a Research Assistant in Computer-Aided Drug Design.

Research Interests 🔍

🔬 Dr. Fathima’s research interests are in the areas of computational drug discovery, machine learning, artificial intelligence, and bioinformatics. Her work focuses on applying advanced computational techniques to predict protein interactions and develop therapeutic solutions for diseases like dengue and Alzheimer’s.

Awards 🏆

🏆 Dr. Fathima has received several accolades, including the “Research Associate Award” from the Anti-viral Research Society in 2022, “Best Paper Award” at INCODS ’17 and NCAC ’09, and the “Outstanding Student Award” from Mepco Schlenk Engineering College.

Publications 📚

A comprehensive review on heart disease prognostication using different artificial intelligence algorithms, Computer Methods in Biomechanics and Biomedical Engineering, February 2024. Cited by 1.5

Alzheimer’s Patients Detection using Support Vector Machine (SVM) with Quantitative Analysis, Neuroscience Informatics, 2021. Cited by 0.5

IoT-Based Intelligent System for Garbage Level Monitoring in Smart Cities, International Conference on IoT, Communication and Automation Technology, 2023. Scopus Indexed

Intelligent Deep Learning Framework for Breast Cancer Prediction using Feature Ensemble Learning, IEEE Global Conference for Advancement in Technology, 2023. Scopus Indexed

Compressing Biosignal for diagnosing chronic diseases, Journal of Physics: Conference Series, 2021. Scopus Indexed