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

Onder Aybastıer | DNA damage | Best Researcher Award

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Assoc Prof Dr. Onder Aybastıer | DNA damage | Best Researcher Award

Assoc Prof Dr, Bursa Uludag University, Turkey

Assoc. Prof. Dr. Önder Aybastier was born on February 1, 1983, in Bursa, Turkey. He is of Turkish nationality and currently resides at Uludag University, Faculty of Science and Arts, Department of Chemistry, Bursa, Turkey.

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📚 Education:

Ph.D. in Analytical Chemistry (2010-2016) from Uludag University, Graduate School of Natural and Applied Sciences, Bursa, Turkey. M.Sc. in Analytical Chemistry (2006-2010) from Uludag University, Graduate School of Natural and Applied Sciences, Bursa, Turkey. B.Sc. in Chemistry (2001-2005) from Uludag University, Faculty of Science and Arts, Bursa, Turkey.

👨‍💼 Experience:

Assoc. Prof. Dr. Önder Aybastier has held the position of Associate Professor at Uludag University, Faculty of Science and Arts, Department of Chemistry since 2021.

🔬 Research Interests:

His research interests include:Immobilization of enzymes on various matrices for biotechnological applications. Extraction and isolation of bioactive compounds from natural sources. Antioxidant properties and oxidative damage prevention. Analytical chemistry methodologies for bioactive compound analysis.

🏆 Awards:

Patent (2021): A novel hydrogel containing galangin, with Saliha Şahin and Eftal Alp Dorken. Numerous awards for research excellence and contributions to the field of chemistry

📄 Publications: International Journal Publications:

Optimization of Immobilization Conditions of Thermomyceslanuginosus Lipase on Styrene-divinylbenzene Copolymer Using Response Surface Methodology, Journal of Molecular Catalysis B: Enzymatic, 2010.

Determination of Total Phenolic Content in Prunella L. by Horseradish Peroxidase Immobilized onto Chitosan Bioreactor, Analytical Methods, 2011.

Orthogonal Signal Correction-based Prediction of Total Antioxidant Activity Using Partial Least Squares Regression from Chromatograms, Journal of Chemometrics, 2012.

Response Surface Optimized Ultrasonic-Assisted Extraction of Quercetin and Isolation of Phenolic Compounds From HypericumPerforatum L. by Column Chromatography, Separation Science and Technology, 2013.

Optimization of Ultrasonic-Assisted Extraction of Antioxidant Compounds from Blackberry Leaves Using Response Surface Methodology, Industrial Crops and Products, 2013.

Paula Montoya Lopera | Planetary Sciences | Best Researcher Award

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Dr. Paula Montoya Lopera | Planetary Sciences | Best Researcher Award

Research Fellow, CODES – UTAS, Australia

Dedicated and hard-working Economic Geologist Scientist with 23 years of experience specializing in the exploration and research of various mineral deposits, including Ag/Au polymetallic epithermal, orogenic gold vein systems, and gold, copper-molybdenum porphyry deposits and skarns. Known for strong leadership and project implementation skills in applied geoscience and economic development.

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🎓 Education:

Specialization in Pedagogy, Universidad del Norte, Colombia (2022). Ph.D. Earth Science (Economic Geology), CGEO, UNAM University, Mexico (2016 – 2020). M.Sc. Earth Science (Geometallurgy), University of Tasmania, Australia (2012 – 2014). B.Sc. Geologist Engineer, National University, Colombia (1999 – 2004)

🏆 Awards:

🏆 Throughout her career, Dr. Montoya Lopera has received numerous awards, including the prestigious BAL-UNAM Award for the best Earth Science PhD thesis (2020) and a PhD Honorific Mention from CGEO, UNAM (2020). She was nominated for the Alfonso Caso Medal for outstanding PhD candidates at UNAM University and received the UNAM Recognition Award for PhD graduation on time, all in 2020. Earlier, she was honored with the OAS-CONACYT-AMEXID Award for the best PhD student at CGEO, UNAM (2016) and the CONACYT Scholarship Award for her PhD studies (2016-2020), along with the AngloGold Ashanti Scholarship Award for her MSc studies at UTAS, Tasmania, Australia (2012-2014).

💼 Experience:

Senior Economic Geologist Consultant at CCS, North University

Senior Geologist at AngloGold Ashanti

🔍 Research Interests:

🔬 Dr. Montoya Lopera’s professional skills span analytical techniques such as XRF, QXRD, and MLA data analysis, complemented by extensive experience in mine geology, geometallurgy, and applied geoscience. She is proficient in using software tools like Datamine (RM – FUSION X), Leapfrog Geo, and IoGas, among others, contributing significantly to her research and consultancy roles in economic geology and mineral exploration.

Publications 

New insights into the geology and tectonics of the San Dimas mining district, Sierra Madre Occidental, Mexico P Montoya-Lopera, L Ferrari, G Levresse, F Abdullin, L Mata Ore Geology Reviews 105, 273-294 17 2019 Development of a predictive geometallurgical recovery model for the La Colosa, porphyry gold deposits, Colombia. S Leichliter, J Hunt, R Berry, L Keeney, P Montoya-Lopera, … The first AusIMM International Geometallurgy Conference: GeoMet 2011. Brisbane 13 2011 Construcción del pensamiento pedagógico BE García, JG López, M Lopera, P Andrea, AF Moreno, PA Osorio Medellín: Universidad Pontifica Bolivariana 9 2007 New geological, geochronological and geochemical characterization of the San Dimas mineral system: Evidence for a telescoped Eocene-Oligocene Ag/Au deposit in the Sierra Madre …

Pushpendra Singh| Electrical Engineering | Excellence in Research

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Dr. Pushpendra Singh| Electrical Engineering | Excellence in Research

Program Director and Professor -Energy Sciences, Atria University Bengaluru, India

Dr. Pushpendra Singh is a distinguished academician and researcher in Electrical Engineering, currently serving as Program Director and Professor of Energy Sciences at Atria University, Bengaluru. With over 19 years of experience, his expertise spans AI & ML applications, Smart Grid technologies, IoT applications in Electrical systems, Game theory, Power system restructuring, and integration of Distributed Energy Resources and Electric Vehicles.

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🎓 Education:

Dr. Pushpendra Singh holds a Ph.D. in Electrical Engineering from MNIT Jaipur, an M.Tech. in Power Systems also from MNIT Jaipur, and completed a Post Graduate Program in Artificial Intelligence and Machine Learning from NIT Warangal.

💼 Experience:

His professional journey includes leadership roles such as Professor of Electrical Engineering at JK Lakshmipat University, Jaipur, Principal at Sunrise Group of Institutions, Udaipur, and various academic positions at Jaipur Engineering College & Research Centre, Jaipur.

🔍 Research Interests:

His research interests focus on AI & ML applications in electrical systems, Smart Grid technologies, IoT applications, Game theory in energy systems, Power system restructuring, and integration of Electric Vehicles.

🏆 Awards:

Dr. Pushpendra Singh has been recognized with awards such as IEEE PES HAC 2023 Ambassador, Excellence in Innovation by ITSR and Institution of Engineers (India), and multiple honors for his contributions to education and engineering services.

 publications 

Revolutionizing EV Charging stations through IoT

Published Year: 2024

Journal: To be presented at The International Conference (IEEE) on Power Electronics & IoT Applications in Renewable Energy and its Control (PARC 2024)

Cited by: Accepted for presentation

Green Credit Incentivization for EV Charging: A Game-Theoretic Approach

Published Year: 2023

Journal: Presented at The 6th International Symposium on Hydrogen Energy and Energy Technologies (HEET 2023)Cited by: Best Paper Award, published in Journal of Physics: Conference Series

Electric Vehicle Adoption and Integration in Smart Cities: A Game-Theoretic Approach

Published Year: 2023Journal: Presented at The 6th International Symposium on Hydrogen Energy and Energy Technologies (HEET 2023)Cited by: Best Paper Award, published in Journal of Physics: Conference Series

Mohammed Allawi | Engineering | Best Researcher Award

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Dr. Mohammed Allawi | Engineering | Best Researcher Award

University of Anbar,  Iraq

Mohammed Falah Allawi, an Iraqi national, is a distinguished civil engineer specializing in water surface hydrology, dams engineering, and fluid mechanics. He holds a PhD in Civil Engineering from the National University of Malaysia and serves as a lecturer at the University of Anbar.

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📚 Education:

Mohammed earned his B.Sc. in Dams and Water Resources Engineering from the University of Anbar in 2010, followed by an M.Sc. and a PhD in Civil Engineering from the National University of Malaysia in 2016 and 2019, respectively.

🏢 Experience:

He has extensive experience as a field engineer in various construction projects and has lectured at Al Maarif University College and the University of Anbar.

🔍 Research Interests:

His research interests span water resources planning, steel structures, advanced soil mechanics, and the application of artificial intelligence in hydro-environmental modeling.

🏆 Awards:

Mohammed has been recognized for his contributions in environmental ergonomics and holds memberships in several engineering associations across Iraq and the Arab region.

📝 Publications:

Neurocomputing, 2022 – Groundwater level prediction using machine learning models: A comprehensive review. Cited by 186.

Neural Computing and Applications, 2018 – Non-tuned machine learning approach for hydrological time series forecasting. Cited by 101.

Neural Computing and Applications, 2019 – A hybrid bat–swarm algorithm for optimizing dam and reservoir operation. Cited by 97.

Scientific Reports, 2020 – Input attributes optimization using the feasibility of genetic nature inspired algorithm: application of river flow forecasting. Cited by 73.

Environmental Science and Pollution Research, 2018 – Review on applications of artificial intelligence methods for dam and reservoir-hydro-environment models. Cited by 66.

RBFNN-based model for heavy metal prediction for different climatic and pollution conditions

Pouya Sepehr | Artificial Intelligence |Best Researcher Award

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Dr. Pouya Sepehr | Artificial Intelligence |Best Researcher Award

Research Fellow, Siena University, Italy

Pouya Sepehr is a researcher and urban planner specializing in the intersections of science, technology, and urban studies. He explores how technological infrastructures influence urban environments, focusing on sustainability and socio-environmental innovation.

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📚 Education:

Pouya holds a PhD in Science-Technology-Society from the University of Vienna, completed in 2023, with a dissertation defense in February 2024. He also holds master’s degrees from the University of Vienna in Science-Technology-Society and from Oxford Brooks University in Development and Emergency Practice. His bachelor’s degree is from Tehran University in Restorations and Conservation of Historical Buildings.

💼 Experience:

Pouya has extensive experience in project management and research. He has served as a Post-Doc Research Fellow at the University of Siena, focusing on digital social innovation in European urban contexts. Previously, he worked as a Researcher at the Institute for Advanced Studies Vienna and as a Research Assistant at various academic institutions across Europe.

🔬 Research Interests:

His research interests include the governance of technology and innovation in urban settings, urban sustainability, and the societal impacts of technological infrastructures. He is particularly interested in advancing multimodal and multispecies urbanism and promoting inclusivity and resilience in urban environments.

🏆 Awards:

Pouya Sepehr is an elected council member of 4S (Society for Social Studies of Science), recognizing his contributions to the field of Science and Technology Studies (STS).

Publications

Sepehr, Pouya. (2024). Mundane Urban Governance and AI Oversight: The Case of Vienna’s Intelligent Pedestrian Traffic Lights. Journal of Urban Technology, 31(1).

Felt, Ulrike, and Pouya Sepehr. (2024). Infrastructuring Citizenry in Smart City Vienna: Investigating Participatory Smartification between Policy and Practice. Journal of Responsible Innovation, 11(2).

Sepehr, Pouya and Ulrike Felt. (2023). Urban Imaginaries as Tacit Governing Devices: The Case of Smart City Vienna. Science, Technology, & Human Values, 48(9).

 

Joseph Arhavbarien | Green Operations | Best Researcher Award

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Dr. Joseph Arhavbarien | Green Operations | Best Researcher Award

Director / Researcher, Rockedge Ventures (UK) Ltd, United Kingdom

🌱📊 Dr. Joseph Arhavbarien is an accomplished researcher with a Ph.D. in Business and Management from the University of Bedfordshire, UK. With over three decades of industrial experience, he focuses on green processes, sustainable operations, and supply chain management. Transitioning to academia, he combines his rich industrial background with his academic expertise to teach and conduct research, applying quantitative techniques to explore green value internalisation.

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📚 Education:

🎓 Dr. Arhavbarien holds a Ph.D. in Business and Management from the University of Bedfordshire (2023). He earned his MBA in International Business from the University of East London (2015) and a B.Sc. (Hons) in Microbiology from the University of Lagos, Nigeria (1989). Additionally, he has a Certificate in Agile Project Management from the University of Oxford (2023).

💼 Experience:

💼 Dr. Arhavbarien’s diverse professional journey includes roles in retail, manufacturing, logistics, and consultancy. Notably, he has worked with Tesco, Morrisons, Gosh Food Ltd, and FedEx, where he led teams, managed operations, and drove continuous improvement initiatives. His expertise spans statistical analysis, project management, and sustainable business practices.

🔬 Research Interests:

🔍📈 Dr. Arhavbarien’s research interests are centered on green value internalisation, sustainable operations, and supply chain resilience. He employs quantitative methods and tools like Qualtrics and SPSS/AMOS to analyze data, aiming to develop green criteria for stakeholder engagement and enhance eco-efficiency in industrial operations.

🏆 Awards:

🏆 Dr. Arhavbarien has been recognized for his academic and professional contributions. A notable achievement includes guiding an M.Sc. student to win the 2023 Logistics Research Network CILT (UK)’s MSc Dissertation of the Year award, reflecting his ability to inspire and mentor students.

Publications

📚  An investigation of antecedents and consequences of green value internalisation among sampled UK enterprises – Journal of Environmental Management, 2024

📄 An examination of antecedents of green value internalisation for firm-level supply chain collaboration – British Academy of Management (BAM) 2022 Conference, Alliance Manchester Business School, UK.

📄 Green supply chain management: an investigation of firm-level antecedents of green value internalisation – 29th European Operations Management Association (EurOMA) Conference, Berlin, Germany, 2022.

📄 An investigation of firm-level antecedents of green value internalisation for Upstream-Downstream supply chain interactions – 32nd Production and Operations Management Society (POMS) Conference (online), 2022.

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

Bablu Karan | Education | Best Researcher Award

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Dr. Bablu Karan | Education | Best Researcher Award

PhD in Education, Central University of Gujarat, India

Dr. Bablu Karan is a dedicated educator and researcher at the Central University of Gujarat, Gandhinagar, specializing in educational technology and curriculum studies. His work focuses on integrating artificial intelligence into secondary education in India, aiming to enhance teaching and learning experiences.

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📚 Education:

Dr. Bablu Karan holds a PhD in Education from the Central University of Gujarat, Gandhinagar. He earned his M.Ed. from Visva-Bharati University, Santiniketan, and a B.Ed. from RIE-NCERT, Bhubaneswar. He also holds an M.A. in English from Ravenshaw University and a B.A. in English Hons from Vidyasagar University.

👨‍🏫 Experience:

Dr. Bablu Karan has extensive experience in educational research and policy formulation. His professional journey includes significant contributions to understanding AI in education, educational policies, and curriculum studies.

🔍 Research Interests:

Dr. Bablu Karan’s research interests span educational technology, AI in education (AIED), ICT, educational policies, curriculum studies, and language education. He is particularly interested in how these areas intersect to improve educational outcomes in diverse contexts.

🏆 Awards:

Recipient of the Best Researcher Award, Dr. Bablu Karan is recognized for his pioneering research in integrating AI into school education and his contributions to educational policy and curriculum development in India.

Publications:

Artificial Intelligence Integration into School Education: A Review of Indian and Foreign Perspectives (2023, Millennial Asia) – Cited by 6

Potential Risks of Artificial Intelligence Integration into School Education: A Systematic Review (2023, Bulletin of Science, Technology & Society) – Cited by 4

Enhancing Women Education in India: An Immense Challenge Towards Effective Human Rights (2017, International Education & Research Journal) – Cited by 2

Promoting Gender Equality in Classroom Teaching and Learning in Indian Context: Issues and Challenges (2017, International Journal of Multidisciplinary Approach & Studies) – Cited by 1

Integration of artificial intelligence by the Central Board of Secondary Education in India: towards innovative teaching and learning practices (2024, Technology, Pedagogy and Education)

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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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