Modafar Ati | Machine Learning and AI Applications | Best Researcher Award

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Assoc. Prof. Dr. Modafar Ati | Machine Learning and AI Applications | Best Researcher Award

Abu Dhabi University | United Arab Emirates

Assoc. Prof. Dr. Modafar Ati is an accomplished academic and researcher in Computer Science and Information Technology with extensive experience in teaching, curriculum development, and leadership. He holds a BSc in Electrical & Communication Engineering and a PhD in Electrical & Computing Engineering from Newcastle upon Tyne, UK. Dr. Ati has over three decades of experience in both academia and industry, serving in senior roles including Associate Professor at Abu Dhabi University, Acting Dean at Sohar University, and Assistant Dean at multiple institutions in Oman. His professional expertise spans software development, systems integration, networking, ICT, project management, Service-Oriented Architecture (SOA), Artificial Intelligence, Big Data, Cybersecurity, and eHealth smart systems. He has published numerous research articles focusing on AI-driven Chronic Disease Management and smart healthcare systems and has led research groups in eGovernment and ICT. Dr. Ati has received multiple grants and awards, including the Chancellor Innovation Award, and serves on editorial boards and as a senior reviewer for international journals and conferences. His teaching portfolio covers programming, network security, project management, human-computer interaction, and mobile application development. Dr. Ati’s contributions to education, research, and innovation reflect a strong commitment to advancing technology-driven solutions in healthcare, smart cities, and digital systems.

Profile : Google Scholar

Featured Publications

Hussein, A. S., Omar, W. M., Li, X., & Ati, M. (2012). “Efficient chronic disease diagnosis prediction and recommendation system” in 2012 IEEE-EMBS Conference on Biomedical Engineering and Sciences, 209–214.

Mohamed, O., Kewalramani, M., Ati, M., & Al Hawat, W. (2021). “Application of ANN for prediction of chloride penetration resistance and concrete compressive strength” in Materialia, 17, 101123.

Mohamed, O. A., Ati, M., & Najm, O. F. (2017). “Predicting compressive strength of sustainable self-consolidating concrete using random forest” in Key Engineering Materials, 744, 141–145.

Hussein, A. S., Omar, W. M., Li, X., & Ati, M. (2012). “Accurate and reliable recommender system for chronic disease diagnosis” in Global Health, 3(2), 113–118.

Ati, M., Kabir, K., Abdullahi, H., & Ahmed, M. (2018). “Augmented reality enhanced computer aided learning for young children” in 2018 IEEE Symposium on Computer Applications & Industrial Electronics.

Abdelouahad Achmamad | Engineering | Best Researcher Award

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Dr. Abdelouahad Achmamad | Engineering | Best Researcher Award

Universite De Mans | France

Dr. Abde Louahad Achmamad is an embedded software engineer and researcher specializing in intelligent systems, AI algorithms, biomedical signal processing, and advanced embedded technologies for electrical, biomedical, and IoT applications. He holds a PhD in Electrical Engineering, complemented by master’s degrees in biomedical engineering and electrical/electronic engineering, supported by earlier qualifications in electromechanics and electronics. His professional experience spans biomedical R&D, embedded system design, AI-based medical diagnostics, MRI segmentation, IoT health monitoring, wearable sensor development, and security applications for STM32 microcontrollers. He has worked with leading institutions and companies across France and Morocco, including STMicroelectronics, Akkodis, Diabtech, Université de Rouen, ENSIAS, and multiple research laboratories. His scientific output includes 102 citations by 95 documents, 16 publications, and an h-index of 6, reflecting contributions in EMG-based diagnostics, phonoangiography, neuromuscular disorder detection, sensor fusion, and few-shot learning for medical imaging. He has also reviewed more than 200 scientific manuscripts for major journals from Springer, Elsevier, and MDPI, demonstrating recognized expertise in signal processing and embedded systems. His research interests include embedded AI, biomedical instrumentation, wearable sensors, IoT-based healthcare, security-focused embedded design, and intelligent diagnostic systems. Dr. Achmamad remains dedicated to advancing high-impact engineering solutions that enhance healthcare, sensing technologies, and intelligent embedded platforms.

Profiles : Scopus | Orcid | Google Scholar

Featured Publications

Achmamad, A., & Jbari, A. (2020). A comparative study of wavelet families for electromyography signal classification based on discrete wavelet transform. Bulletin of Electrical Engineering and Informatics.

Achmamad, A., Belkhou, A., & Jbari, A. (2020). Fast automatic detection of amyotrophic lateral sclerosis disease based on Euclidean distance metric. In 2020 International Conference on Electrical and Information Technologies .

Belkhou, A., Achmamad, A., & Jbari, A. (2019). Classification and diagnosis of myopathy EMG signals using the continuous wavelet transform. In 2019 Scientific Meeting on Electrical-Electronics and Biomedical Engineering and Computer Science .

Belkhou, A., Achmamad, A., & Jbari, A. (2019). Myopathy detection and classification based on the continuous wavelet transform. Journal of Communications Software and Systems.

Abdelouahad, A., Belkhou, A., Jbari, A., & Bellarbi, L. (2018). Time and frequency parameters of sEMG signal–force relationship. In 2018 International Conference on Optimization and Applications .

Decheng Li | Engineering | Best Researcher Award

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Mr. Decheng Li | Engineering | Best Researcher Award

Lanzhou University of Technology | China

Dr. Decheng Li is a dedicated scholar and researcher at the School of Automation and Electrical Engineering, Lanzhou University of Technology, China. He obtained his academic training in electrical engineering and automation, focusing on intelligent control systems, robotics, and power electronics. With extensive teaching and research experience, Dr. Li has contributed significantly to the advancement of automation technologies and intelligent systems applications in industrial environments. His research interests encompass intelligent control theory, optimization algorithms, renewable energy integration, and advanced signal processing techniques for control systems. Dr. Li has authored and co-authored numerous papers in leading international journals and conferences, reflecting his commitment to academic excellence and technological innovation. He has been involved in several national and provincial research projects, fostering collaboration between academia and industry. In recognition of his contributions, Dr. Li has received multiple academic awards and honors for his outstanding research and teaching performance. He continues to mentor graduate students and promote interdisciplinary research to solve real-world engineering challenges. Dr. Li remains committed to advancing automation and intelligent systems for sustainable industrial development and the future of smart technologies.

Profile: Orcid

Featured Publication

Liu, J., Li, D., & Chen, H. (2025). “Robust hybrid decentralized controller design for Voice Coil Actuator-Fast Steering Mirror system in high-precision optical measurements.

Mittar Pal | Engineering | Women Researcher Award

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Dr. Mittar Pal | Engineering | Women Researcher Award

Deenbandhu Chhotu Ram University of Science and Technology | India

Dr. Mittar Pal is an experienced academic and researcher in Electronics & Communication Engineering with over twelve years of teaching and research experience, specializing in renewable energy systems and AI‑based engineering applications. He holds a B.Tech in ECE (2003), M.Tech in Nanoscience & Technology (2013) and completed his Pre‑PhD in ECE (2019) from renowned Indian institutions, and recently earned his PhD on barrier identification and prioritisation for solar photovoltaic system deployment in dairy farming in India (2023). His work on techno‑economic analysis of photovoltaic systems in dairy farming and optimization of utility‑integrated solar PV systems has appeared in SCI and Scopus‑indexed outlets, and he has supervised numerous B.Tech and M.Tech projects while contributing to NBA documentation and curriculum development. He is UGC‑NET qualified for Electronic Science (Assistant Professor). His research interests span signal & system theory, digital electronics, power electronics, renewable solar energy modelling (using MATLAB, HOMER Pro, SAM, RETScreen), AI/ML, generative AI, IoT and pattern recognition. With a growing scholarly profile (h‑index ~ 5 and citation count ~5 as per publicly listed profiles), he continues to publish, present at international conferences, and drive innovation in teaching and research. His dedication to transforming traditional dairy farming through solar PV integration underscores his commitment to sustainability and engineering education.

Profile: Scopus 

Featured Publications

Mittarpal. (2018). “Modeling and Simulation of Solar Photovoltaic Module using Matlab-Simulink.” International Journal for Research in Engineering Application & Management .

Mittarpal. (2018). “Modeling Design and Simulation of Photovoltaic Module with Tags Using Simulink.” International Journal of Advance & Innovative Research.

Mittarpal, & Asha. (2018). “Simulation and Modeling of Photovoltaic Module Using Simscape.” National Conference on Advances in Power, Control & Communication Systems .

Mittarpal, Naresh Kumar, & Priyanka Anand, Sunita. (2017). “Realization of Flip Flops Using LabVIEW and MATLAB.”

Mittarpal, Naresh Kumar, & Sunita Rani. (2017). “Realisation of Digital Circuits Systems Using Embedded Function on MATLAB.” International Journal of Engineering and Technology.

Chulhwan Bang | Machine Learning and AI Applications | Best Researcher Award

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Dr. Chulhwan Bang | Machine Learning and AI Applications | Best Researcher Award

Georgia Southern University | United States

Dr. Chulhwan C. Bang is an Assistant Professor of Business Analytics and Information Systems at Georgia Southern University. He earned his Ph.D. in Business Management, specializing in Management Science and Systems with a minor in Communication, from the University at Buffalo, SUNY. With over a decade of academic and professional experience, Dr. Bang has taught a wide range of courses in business programming, information systems, and data analytics, integrating tools such as Python, SAP, Power BI, and Tableau. His research interests include big data analytics, cryptocurrency forecasting, social media analysis, deep learning, and sports analytics. He has published in top-tier journals such as Information Systems Frontiers and International Journal of Information Management and actively collaborates with students on applied data-driven projects. Prior to academia, he worked in the IT industry as a system architect and software developer, contributing to large-scale ERP and BI projects in Korea and the U.S. Dr. Bang has received multiple honors, including the Outstanding Research Award and finalist recognition for accelerator research grants. His work bridges theory and practice, fostering innovation in analytics education and advancing interdisciplinary research in business intelligence and emerging technologies.

Profile : Orcid

Featured Publications

Lee, Y. S., & Bang, C. C. (2022). Framework for the Classification of Imbalanced Structured Data Using Under-sampling and Convolutional Neural Network. Information Systems Frontiers.

Bang, C. C., Lee, J., & Rao, H. R. (2021). The Egyptian protest movement in the twittersphere: An investigation of dual sentiment pathways of communication. International Journal of Information Management.

Bang, C. C. (2020). Predicting Loyalty of Korean Mobile Applications: A Dual-Factor Approach. International Journal of Information and Communication Technology for Digital Convergence (IJICTDC).

Yu, J., Bang, C. C., & Oh, D.-Y. (2020). The Effect of Noncognitive Factors on Information Disclosure on Social Network Websites: Role of Habit and Affect. Southern Business & Economic Journal.

Kwon, K. H., Bang, C. C., Egnoto, M., & Rao, H. R. (2016). Social media rumors as improvised public opinion: semantic network analyses of Twitter discourses during Korean saber rattling 2013. Asian Journal of Communication.

Arun Gupta |  Fluid Mechanics | Best Researcher Award

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Dr. Arun Gupta |  Fluid Mechanics | Best Researcher Award

University Institute of Engineering And Technology | India

Dr. Arun Kumar Gupta is an accomplished academician and researcher in the field of Chemical Engineering with over twenty-three years of teaching and research experience. He is currently serving as an Associate Professor at the University Institute of Engineering and Technology, Chhatrapati Shahu Ji Maharaj University, Kanpur. Dr. Gupta holds a B.Tech in Chemical Engineering from UIET, CSJMU, an M.Tech, and a Ph.D. in Chemical Engineering from IIT Kanpur. His research interests encompass process modeling and simulation, sustainable chemical processes, environmental engineering, smart farming systems, and the application of IoT and machine learning in chemical engineering. With 27 publications, 14 edited chapters, 3 books, and 1 completed project under the CV Raman Scheme, he has made significant scholarly contributions. He has organized and participated in numerous workshops, conferences, and faculty development programs and has been recognized with several honors, including the “Excellence in Academics Award” at the INDO–THAI International Excellence Awards 2024 and a Gold Medal in the NPTEL ASPEN course. Dr. Gupta’s innovative work has also led to two patents in smart irrigation and sustainable reactor design. Dedicated to advancing engineering education and research, he continues to inspire students and contribute to technological innovation.

Profiles : Orcid | Google Scholar

Featured Publications

Chandra, A.K., Khan, W., Gupta, A.K., Patel, P.B., & Niranjan, R.S. (2025). “E‐Waste: A Leading Hazardous Waste.” In Global Waste Management (pp. 29–61).

Lal, A., Gupta, A.K., Kumar, A., & Indu, N.K.Y. (2010). “Manufacture and study of physico-chemical properties of Karanja bio-diesel.” In Proceedings on Renewable Energy and Sustainable Biofuels (Vol. 4).

Gupta, G.D., & Arun Kumar, G. (2022). “Enhancement in activity and reusability of dry Amberlyst-15 catalyst by thermal treatment for production of biodiesel from Karanja oil.” In Asian Journal of Chemistry, 35(1), 62–68.

Gupta, A.K., & Deo, G. (2018). “A single-step process to convert Karanja oil to fatty acid methyl esters using Amberlyst-15 as a catalyst.” In Chemical and Biochemical Engineering Quarterly, 32(1), 1–10.

Chiu, K., Gupta, A., Afxentiou, T., Ashraf, A., Kanani, R., Rajaguru, K., Bhatt, N., et al. (2025). “Impact of multiprofessional radiotherapy peer review on multidisciplinary team meeting staging in head and neck cancer.” In Clinical Oncology, 38, Article 103696.

Gupta, A.K. (2023). “Various methods for enhancement in heterogeneous catalyzed biodiesel production reaction rate.” In Journal of the Indian Chemical Society, 100(100970), 4.

Eman Ayman Nada |  Public Health Analytics | Best Researcher Award

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Dr. Eman Ayman Nada |  Public Health Analytics | Best Researcher Award

Mnistry of Health, Damietta | Egypt

Dr. Eman Ayman Nada is a pharmacist-researcher who earned her Bachelor’s degree in Pharmaceutical Sciences at the Tanta University (2017–2022), graduating with a “Very Good” grade. She currently serves as a hospital pharmacist at Kafr Saad Central Hospital in Damietta, Egypt, and as a researcher with the Medical Research Group of Egypt (MRGE) in Arlington, USA. In her research role she has led systematic reviews and meta-analyses (including as first or corresponding author), performing data analysis with RevMan and SPSS. Her education and internships have included clinical research training (via Negida Academy) and GCP certification (viaMedical Agency for Research and Statistics in London). Her research interests span clinical pharmacy, systematic reviews and meta-analysis, pharmacoepidemiology, drug safety and pharmacovigilance, and the intersection of data-analysis / machine-learning with public-health outcomes. She has also served in student-research leadership roles, coordinating training for hundreds of students in scientific research methodology. Looking ahead, she aims to further publish high-impact evidence-based medicine studies, mentor emerging researchers, and contribute to improved pharmaceutical care through rigorous clinical research.

Profiles : Orcid | Scopus

Featured Publications

1️⃣ Nada, E. A., Abu Kaddorah, M. E., El Jamal, M., Hamad, A., & Mansour, F. R. (2025). Eggshell waste as a sustainable resource for nanoparticle preparation; synthesis, characterization and applications. Environmental Nanotechnology, Monitoring & Management.

2️⃣ Varghese, C., Peters, L., Gaborit, L., Xu, W., Kalyanasundaram, K., Basam, A., Park, M., Wells, C., McLean, K. A., Schamberg, G., et al. (2025). Predicting opioid consumption after surgical discharge: a multinational derivation and validation study using a foundation model. npj Digital Medicine.

3️⃣ Zaazouee, M. S., Nada, E. A., Al-kafarna, M., Shaheen, A., Ramu, S. K., Hafez, A. H., Matar, S. G., Assar, A., Elshennawy, M., Abu El-Enien, H., et al. (2025). A multinational cross-sectional study on the prevalence and predictors of long COVID across 33 countries. Scientific Reports.

4️⃣ Abdelghany, A., Qutob, I. A., Abdel Azim, A., Assem, M., Gad, M., Shawkat, A., Gamal, A., & Nada, E. A. (2025). Perioperative and oncological outcomes of laparoscopic versus open pancreaticoduodenectomy: A meta-analysis of randomized controlled trials. Annals of Oncology.

5️⃣ Chukr, M., Mohamady, A. O., Abdallh, F., Farrag, D. A., Nada, E. A., Qutob, I. A., & Elsayed, M. M. (2025). Knowledge, Attitudes, and Practices of Blood Donation Among Medical Students: A Systematic Review Across Nine Countries. Preprint.

 

Somnath Nandi | Data-informed Decision Making | Best Researcher Award

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Mr. Somnath Nandi | Data-informed Decision Making | Best Researcher Award

Jadavpur University | India

Mr. Somnath Nandi is a PhD Research Scholar at the Additive Manufacturing Research Group (AMRG), CSIR-Central Mechanical Engineering Research Institute (CMERI), India, affiliated with the Academy of Scientific and Innovative Research (AcSIR). His research focuses on functionally graded material (FGM) development, mechanical and tribological characterization, and process optimization in Wire Arc Additive Manufacturing (WAAM). He has contributed to several funded projects, including the design of SS-Ni transition metals-based electrodes for green hydrogen generation, bimetallic structure development for Tata Steel, and remanufacturing of railway brake shoes. Mr. Nandi holds an M.E. in Production Management from Jadavpur University and a B.Tech in Mechanical Engineering from the Government College of Engineering and Textile Technology, Berhampore. His published works in reputed SCI-indexed journals such as Progress in Additive Manufacturing, Materials Letters, and Journal of Materials Engineering and Performance highlight his expertise in optimization, digital twins, and sustainable manufacturing. His research interests span metal additive manufacturing, tribology, hybrid manufacturing, and digital monitoring systems. A GATE-qualified engineer (2021, 2022), he is an active member of professional societies including IIM and IAENG. Mr. Nandi has authored 10+ scientific documents, achieving an h-index of 3 with over 45 citations, reflecting his growing impact in the field of advanced manufacturing.

Profiles : Orcid | Google Scholar

Featured Publications

Biswas, S., Nandi, S., Hussain, M. S., Mandal, A., & Mukherjee, M. (2025). “Influence of heat input on the interfacial characteristics of SS316L–In718 bi-metallic deposition for wire arc additive manufacturing.” Materials Letters.

Nandi, S., Biswas, S., & Mukherjee, M. (2025). “Optimization of Wire Arc Additive Manufacturing Parameters for Steel–Aluminum Bimetallic Interface: A Comparative Study of Metaheuristic and Machine Learning Approaches.” Journal of Materials Engineering and Performance, 35(6).

Ahammed, A. A. C. P., Nandi, S., Paul, A. R., Sreejith, B., MJ, J., & Mukherjee, M. (2025). “On the Characteristic Evaluation of Bimetallic Interface of Carbon Steel (EN31) and Aluminium (AA4043) for Wire Arc Additive Manufacturing.” Metals and Materials International, 1–18.

Pendokhare, D., Nandi, S., & Chakraborty, S. (2025). “A comparative analysis on parametric optimization of abrasive water jet machining processes using foraging behavior-based metaheuristic algorithms.” OPSEARCH, 1–42.

Hamed Etezadi | Quantitative Research | Best Researcher Award

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Mr. Hamed Etezadi | Quantitative Research | Best Researcher Award

McGill University | Canada

Dr. Hamed Etezadi is a research-focused scholar in Bioresource Engineering with a Ph.D. from McGill University, Canada, where his thesis focused on developing decision support infrastructure for sustainable crop production under the supervision of Prof. Viacheslav Adamchuk. He holds an M.S. in Biosystems and Agricultural Engineering from the University of Tehran, Iran, and a B.E. in Agricultural Engineering from Urmia University, Iran. With over 15 years of academic and professional experience, Dr. Etezadi has contributed significantly to precision agriculture, data-driven modeling, remote sensing, machine learning, and autonomous agricultural systems. He has published 6 peer-reviewed journal articles, including Q1 and Q2 journals, and presented at leading conferences such as ASABE and IEEE/CS Robotics and Mechatronics, His research explores soil variability, aerial pollination systems, and predictive modeling for sustainable agriculture. He has received multiple honors, including the FRQNT Scholarship, Grad Excellence Award, and global recognition on Kaggle Notebooks. Dr. Etezadi combines academic teaching, research leadership, and industry experience, including directing growth and innovation in agri-tech platforms, fostering data-driven decision-making, and advancing sustainable farming technologies globally.

Profile : Orcid 

Featured Publications

Etezadi, H., Adamchuk, V., Bouroubi, Y., Leduc, M., Gasser, M.-O., & Titley-Peloquin, D. (2025). “Quantifying intra-field soil variability using categorical data: A case study of predicting soil organic matter using soil survey maps.”

Etezadi, H., & Eshkabilov, S. (2024). “A comprehensive overview of control algorithms, sensors, actuators, and communication tools of autonomous all-terrain vehicles in agriculture.”

Mazinani, M., Zarafshan, P., Dehghani, M., Vahdati, K., & Etezadi, H. (2023). “Design and analysis of an aerial pollination system for walnut trees.”

Zarafshan, P., Etezadi, H., Javadi, S., Roozbahani, A., Hashemy, S. M., & Zarafshan, P. (2023). “Comparison of machine learning models for predicting groundwater level, case study: Najafabad region.”

Salari, K., Zarafshan, P., Khashehchi, M., Chegini, G., Etezadi, H., Karami, H., Szulżyk-Cieplak, J., & Łagód, G. (2022). “Knowledge and technology used in capacitive deionization of water.”

Viken Kortian | Big Data Analytics | Best Researcher Award

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Assoc. Prof. Dr. Viken Kortian | Big Data Analytics | Best Researcher Award

Macquarie University | Australia

Assoc. Prof. Dr. Viken Kortian is an accomplished academic and researcher specializing in operations management, innovation, and entrepreneurship, with extensive expertise in business process management, strategy, and big data analytics. He holds a PhD in Management from Macquarie Graduate School of Management, where his doctoral research focused on organizational agility and firm performance in Australian SMEs. His academic foundation also includes a Master of Arts, an MBA, and a Bachelor of Chemical Engineering with honors. Dr. Kortian has built a distinguished career in higher education, currently serving as Associate Professor at Macquarie University’s School of Engineering, where he played a pivotal role in designing and leading the Master of Engineering Management program, one of the university’s largest postgraduate offerings. He has also contributed to Kaplan Business School, Macquarie Graduate School of Management, and the Australian Graduate School of Management through innovative course development in data analytics, quality management, and business excellence. His research interests span business excellence, operations management, artificial intelligence, and machine learning, with several conference presentations, publications, and a US patent to his credit. Recognized with multiple Vice Chancellor’s Awards for Teaching Excellence and other honors, Dr. Kortian is a dedicated educator, researcher, and thought leader shaping engineering management education in Australia.

Profile : Orcid 

Featured Publication

“Challenges and Issues in Implementing & Operationalising Big Data Analytics Capabilities in a major Australian Railway Organisation: A Case Study”