Ammar Khaleel l Reinforcement Learning | Research Excellence Award

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Mr. Ammar Khaleel l Reinforcement Learning | Research Excellence Award

Széchenyi István Egyetem | Hungary

Mr. Ammar Khaleel PhD-level researcher in computer science with ongoing doctoral training, focusing on reinforcement learning–based decision making for autonomous vehicles. Experience includes designing, training, and evaluating deep reinforcement learning and control algorithms for autonomous driving, particularly lane-changing, within large-scale traffic simulations using SUMO and the TraCI Python API. Research interests span reinforcement learning, deep learning, model predictive control, intelligent transportation systems, and traffic modeling. Technical expertise covers Python, C/C++, simulation frameworks, and reproducible research workflows. Academic contributions emphasize simulation-driven experimentation and algorithmic innovation; no formal awards are listed. Overall, the work aims to advance safe, efficient, and intelligent mobility systems.

Citation Metrics (Scopus)

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Featured Publications


A Multi-Levels RNG Permutation

– Indonesian Journal of Electrical Engineering and Computer Science, 2019

A New Permutation Method for Sequence of Order 28

– Journal of Theoretical and Applied Information Technology, 2019

N/A and Signature Analysis for Malwares Detection and Removal

– Indian Journal of Science and Technology, 2019

Mohammed Almulla | Prescriptive Analytics | Research Excellence Award

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Prof. Mohammed Almulla | Prescriptive Analytics | Research Excellence Award

Kuwait University | Kuwait

Prof. Mohammed Almulla is a distinguished computer scientist with a Ph.D. from McGill University, Canada. He has served Kuwait University for over three decades, progressing from Assistant Professor to Professor, and held key administrative roles including Department Chair and Acting Vice President. His research focuses on artificial intelligence, automated theorem proving, database systems, and digital transformation in education. He contributed to ABET accreditation, ICT infrastructure, and eLearning initiatives, and actively participates in international conferences and journal reviews. Recognized for his leadership and innovation, he has received awards for informatics excellence, fostering advancements in computing education and research.

Citation Metrics (Scopus)

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Citations
613

Documents
72

h-index
14

Citations

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Top 5 Publications

Data-Driven Anesthesia: An Ensemble Model for Propofol and Remifentanil Dosage Control During Medical Surgery

International Journal of Research and Scientific Innovation, 2025
DOI: 10.51244/ijrsi.2025.121500017p
Authors: Abas Almaayofi, Farah Almulla, Mohammed A. Almulla
A Trust-Based Global Expert System for Disease Diagnosis Using Hierarchical Federated Learning

Journal of Engineering Research, 2025
DOI: 10.1016/j.jer.2025.03.001
Authors: Farah M. Almulla, Mohammed A. Almulla
A Novel CLIPS-Based Medical Expert System for Migraine Diagnosis and Treatment Recommendation

Kuwait Journal of Science, 2025
DOI: 10.1016/j.kjs.2024.100310
Author: Mohammed A. Almulla
On the Effect of Prior Knowledge in Text-Based Emotion Recognition

International Journal of Research and Scientific Innovation, 2024
DOI: 10.51244/ijrsi.2024.1108005
Author: Mohammed A. Almulla
Facial Expression Recognition Using Deep Convolution Neural Networks

IEEE Annual Congress on Artificial Intelligence of Things (AIoT), 2024
DOI: 10.1109/aiot63253.2024.00022
Author: Mohammed A. Almulla

Helmi Ayari | Data processing | Research Excellence Award

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Mr. Helmi Ayari | Data processing | Research Excellence Award

Université Ibn khaldoun | Tunisia

Helmi Ayari is a doctoral researcher in Artificial Intelligence at the École Polytechnique de Tunisie, focusing on machine learning, deep learning, and intelligent imaging systems, with a research track record that includes 3 published documents, an h-index of 1, and citations from 33 documents. He holds a Master of Research in Intelligent Systems for Imaging and Computer Vision and a fundamental Bachelor’s degree in Computer Science. His work includes contributions to medical image analysis, explainable AI, and optimization techniques, with notable publications such as a comparative study of classical versus deep learning-based computer-aided diagnosis systems published in Knowledge and Information Systems (Q2), and a study integrating genetic algorithms with ensemble learning for enhanced credit scoring presented at the International Conference on Business Information Systems (Class B). Professionally, he has served as a Maître Assistant and teaching assistant, delivering courses in machine learning, deep learning, Python, R, computer architecture, and automata theory, while supervising Master’s research, coordinating academic programs, and contributing to hackathons and university events. His research interests span AI-driven decision systems, interpretable machine learning, evolutionary optimization, and applied deep learning. Recognized for both academic and pedagogical engagement, he continues advancing impactful AI research and education.

Profile : Scopus

Featured Publications

Computer-Aided Diagnosis Systems: A Comparative Study of Classical Machine Learning Versus Deep Learning-Based Approaches. Knowledge and Information Systems, published May 23, 2023. https://doi.org/10.1007/s10115-023-01894-7

Integrating Genetic Algorithms and Ensemble Learning for Improved and Transparent Credit Scoring. International Conference on Business Information Systems, June 25, 2025. (Class B)

Umme Habiba | Machine Learning and AI Applications | Research Excellence Award

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Mrs. Umme Habiba | Machine Learning and AI Applications | Research Excellence Award

North Dakota State University(NDSU) | United States

Umme Habiba is a dedicated researcher and educator in computer science whose work centers on machine learning, deep learning, transformer-based architectures, explainable AI, and swarm intelligence, particularly within medical data analysis. She is pursuing her Ph.D. and M.Sc. in Computer Science at North Dakota State University, where she has gained extensive teaching experience as an instructor of record and graduate teaching assistant across several undergraduate courses. Her research contributions span clinical text mining, medical risk prediction, brain–computer interface modeling, IoT security, and usability analysis of mHealth applications, with publications in reputable international journals. She has also collaborated on projects involving mobile sensor–based spatial analysis, voice-controlled IoT automation systems, and hybrid ML models for network intrusion detection. Her academic journey began with a bachelor’s degree in Computer Science and Engineering, where she developed a strong foundation in data-driven system design and intelligent applications. She has received consistently high teaching evaluations and has demonstrated a commitment to interdisciplinary research and student learning. Her long-term goal is to contribute impactful solutions at the intersection of artificial intelligence and healthcare while advancing as both a researcher and an educator.

Profile : Orcid

Featured Publication

PSO-optimized TabTransformer architecture with feature engineering for enhanced cervical cancer risk prediction, 2026

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.

Osama Sawalha | Healthcare Data Analysis | Best Researcher Award

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Dr. Osama Sawalha | Healthcare Data Analysis | Best Researcher Award

Universidad de Granada | Spain

Dr. Osama Sawalha is a dedicated researcher and registered nurse with a PhD in Public Health and Clinical Medicine from the University of Granada, Spain. His academic background also includes a Master’s degree in Health Care for the Promotion of Personal Autonomy and End-of-Life Care Processes and a Bachelor’s degree in Nursing. With extensive clinical experience across Spain and Palestine, Dr. Sawalha has worked in diverse healthcare environments, including hospitals, Alzheimer’s care facilities, and emergency medical services. His research focuses on psychological well-being, particularly depression, anxiety, and stress among patients undergoing coronary artery bypass grafting (CABG) and their caregivers. He has authored and co-authored several peer-reviewed publications in high-impact journals, addressing mental health outcomes, cardiac recovery, and family functioning in chronic illness contexts. Dr. Sawalha has presented his work at international conferences and participated in numerous professional development programs on research methodologies, scientific writing, and biomedicine. His work aims to improve the integration of psychological care within clinical and community health systems. Through his dedication to patient-centered research and compassionate nursing practice, Dr. Sawalha continues to contribute meaningfully to advancing public health and evidence-based care.

Profile : Orcid

Featured Publications

Sawalha, O., Ariza-Vega, P., Alhalaiqa, F., Pérez-Rodríguez, S., & Romero-Ayuso, D. (2024). Psychological discomfort in patients undergoing coronary artery bypass graft (CABG) in West Bank: A cohort study. Journal of Clinical Medicine, 13(7), 2027.

Sawalha, O., Ariza-Vega, P., Alhalaiqa, F., Dabbour, R., & Romero-Ayuso, D. (2025). Comparison of pre- and post-surgery cardiac depression and perceived stress levels in heart patients undergoing different types of surgery. Geriatric Nursing.

Pérez-Rodríguez, S., Sawalha, O., & Romero-Ayuso, D. (2025). ECogFun-Virtual Reality program for improving planning and organization skills in daily life in children and adolescents with ADHD: A study protocol for a randomized controlled trial. Research in Developmental Disabilities.

Talita Ferreira | Data Regulation | Best Researcher Award

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Ms. Talita Ferreira | Data Regulation | Best Researcher Award

University of Salamanca | Spain

Talita Ferreira is an experienced pharmacist and regulatory affairs specialist with over 20 years of expertise in the pharmaceutical industry, leading strategic projects across Latin America, the USA, and Africa. She holds a Master’s degree in Entrepreneurship from the University of São Paulo and is pursuing a PhD in Business Economy at Universidad de Salamanca, with a research focus on healthcare management, organizational strategies, decision-making processes, and knowledge management. Talita has served as CEO and founder of multiple companies, including Avanti Farmacêutica, Pharma Avanti, and Legis Consulting, providing regulatory, quality, and strategic support to pharmaceutical organizations. She has collaborated with global institutions such as the World Health Organization and the International Pharmaceutical Federation, supporting vaccine manufacturing expansion, regulatory compliance, and biowaiver alignment initiatives. Her professional experience spans regulatory submissions, due diligence, GMP inspections, and regulatory intelligence, contributing to product launches, portfolio expansion, and process improvements. Talita combines her industry expertise with academic experience as an assistant professor and facilitator of business simulation games in undergraduate and postgraduate programs. Known for her effective communication, leadership, and problem-solving skills, she is committed to fostering innovation, compliance, and sustainable growth within the pharmaceutical and healthcare sectors.

Profiles: Orcid | Google Scholar

Featured Publications

da Silva Ferreira, T., Pauletti, G. M., Fernandes, E. A. F., Campos, A. F., Aceituno, A., … (2024). “Knowledge-based: facilitating access to medicines in Latin America.”

de Oliveira, L. G., de Souza Marcelino, V., & da Silva Rangel, F. C. (2018). “Perception of chemicals graduates about the adoção of teaching methodologies in a virtual learning.

Ferreira, T. S. (2019). “Technical alignment of collaborators through the management of knowledge.” University of São Paulo.

Ferreira, T. S., Pauletti, G. M., & Vázquez-Suárez, L. (2025). “How the Stakeholders’ Perception Contributes to the Pharmaceutical Strategies: A Regional Case Study in Latin America.

Ferreira, T. S., Pauletti, G. M., Fernandes, E. A., Campos, A. F., Aceituno, A., … (2023). “Knowledge-Based: Strategic Access to Medicines in Latin America.

Amon Exavery | Statistical Analysis | Transcontinental Excellence in Research Data Analysis Award

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Dr. Amon Exavery | Statistical Analysis | Transcontinental Excellence in Research Data Analysis Award

University of Dodoma | Tanzania

Dr. Amon Exavery is a distinguished statistician and public health researcher with over 15 years of experience in research, evaluation, and learning. He holds a Ph.D. in Statistics from the University of Dodoma, a Master’s degree in Epidemiology from the University of the Witwatersrand, and a Bachelor’s degree in Statistics from the University of Dar es Salaam. Dr. Exavery has led numerous large-scale health and social service research projects, including impactful programs on Orphans and Vulnerable Children (OVC), HIV/AIDS, malaria, WASH, nutrition, reproductive, maternal, and child health, adolescent sexual and reproductive health, and sustainable livelihoods. As a Senior Research and Learning Advisor at Pact Tanzania, he has spearheaded multiple secondary data analyses, impact evaluations, and evidence-based program improvements. Previously, he served as a Statistician and Research Scientist at Ifakara Health Institute and Monitoring & Evaluation Officer at Jhpiego, where he applied advanced statistical modeling, multilevel analysis, and predictive analytics to inform policy and practice. A prolific author, Dr. Exavery has published over 40 peer-reviewed articles, presented at international conferences, and contributed to global public health knowledge. Recognized for his strategic leadership, mentorship, and innovative research approaches, he continues to drive evidence-based interventions and strengthen research capacity across Tanzania and the wider region.

Profile : Orcid

Featured Publications

Exavery, A., Kirigiti, P. J., Balan, R. T., & Charles, J. (2026). “Enhancing Longitudinal Impact Evaluation of Non-Experimental Interventions: A Comparative Analysis of Generalized Estimating Equations and Multilevel Models Based on Empirical Evaluation of Temporal Change in Food Security Following an Economic Empowerment Intervention.” Evaluation and Program Planning.

Exavery, A., Kirigiti, P. J., Balan, R. T., & Charles, J. (2025). “Determinants of Participation in WORTH Yetu Economic Empowerment Intervention among Caregivers of Orphaned and Vulnerable Children in Tanzania: A Longitudinal Multivariable Logistic Regression Analysis.” Social Sciences & Humanities Open.

Exavery, A., Kirigiti, P. J., Balan, R. T., & Charles, J. (2024). “Longitudinal Evaluation of the Influence of WORTH Yetu on Household Economic Status Based on the Count of Non-Asset Resources for Orphaned and Vulnerable Children’s Well-Being in Tanzania.” Child Indicators Research.

Exavery, A., Katbi, M., Kirigiti, P. J., Balan, R. T., & Charles, J. (2024). “Multivariate Mixed-Effects Ordinal Logistic Regression Models with Difference-in-Differences Estimator of the Impact of WORTH Yetu on Household Hunger and Socioeconomic Status among OVC Caregivers in Tanzania.” PLOS ONE.

Exavery, A., Alam, K., Charles, J., Barankena, A., Bajaria, S., Minja, E., Mulikuza, J., Mbwambo, T., Ally, A., Mseya, R., et al. (2022). “Impact of Household Economic Strengthening Intervention on Food Security among Caregivers of Orphans and Vulnerable Children in Tanzania.” PLOS ONE.

Mohammad Zeyauddin | Qualitative Research | Best Researcher Award

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Assist. Prof. Dr. Mohammad Zeyauddin | Qualitative Research | Best Researcher Award

Jubail Industrial College | Saudi Arabia

Dr. Mohammad Zeyauddin is an accomplished Assistant Professor in the Department of General Studies, Mathematics Section, at Jubail Industrial College, Saudi Arabia. With over fourteen years of teaching experience at undergraduate and postgraduate levels, he has contributed significantly to curriculum development, academic mentorship, and student engagement. Dr. Zeyauddin holds a Ph.D. in Applied Mathematics from Banaras Hindu University, India, with research focused on spatially homogeneous and anisotropic Bianchi Type V cosmological models in general relativity and scalar-tensor theories of gravitation. He also completed a Post-Doctoral Fellowship at the Joint Institute for Nuclear Research, Dubna, Russia, specializing in relativistic cosmology. His teaching repertoire spans Linear Algebra, Differential and Integral Calculus, Differential Equations, Complex and Functional Analysis, Tensor Analysis, Probability and Statistics, and Computational Mathematics. He has published over 30 international research papers and serves as a reviewer for the American Mathematical Society. His research interests include non-linear differential equations, general relativity, cosmology, and scalar-tensor theories of gravitation. Recognized for academic excellence, he has received UGC Junior and Senior Research Fellowships, postdoctoral fellowships, and appreciation for curriculum contributions. Dr. Zeyauddin continues to inspire students and peers through innovative teaching, research, and contributions to mathematical sciences.

Profile : Orcid

Featured Publications

Dayanandan, B., Pradhan, A., Zeyauddin, M., & Banerjee, A. (2025). Quark stars with strongly interacting quark matter in energy-momentum squared gravity. International Journal of Geometric Methods in Modern Physics.

Pradhan, A., Zeyauddin, M., Dixit, A., & Krishnannair, S. (2025). Dust-fluid accelerating flat cosmological models in f(R,T,Lm)-gravity with observational constraints. International Journal of Geometric Methods in Modern Physics.

Pradhan, A., Zeyauddin, M., Dixit, A., & Ghaderi, K. (2025). Phantom dark energy behavior in Weyl type f(Q,T) gravity models with observational constraints. Universe, 11(8).

Pradhan, A., Dayanandan, B., Zeyauddin, M., & Banerjee, A. (2025). On the possible existence of wormholes in Rastall–Rainbow gravity. International Journal of Modern Physics A.

Pradhan, A., Dixit, A., Zeyauddin, M., & Krishnannair, S. (2024). A flat FLRW dark energy model in f(Q,C)-gravity theory with observational constraints. International Journal of Geometric Methods in Modern Physics.

Basharat Ali | Cybersecurity Data Analysis | Best Researcher Award

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Dr. Basharat Ali | Cybersecurity Data Analysis | Best Researcher Award

Nanjing University | China

Dr. Basharat Ali is a dedicated researcher and PhD scholar in Computer Science at Nanjing University, China, with a strong academic foundation in Software Engineering from Northeastern University, China, and the University of Swat, Pakistan. His professional journey includes roles as a Software Developer at Neusoft (China) and RaidIT Solution (Pakistan), where he gained hands-on expertise in programming, system architecture, and cross-border e-commerce platforms. His research focuses on network security, blockchain development, IoT infrastructure protection, and the integration of deep learning techniques for cyber defense. Dr. Ali has published influential works such as “An Efficient E-Voting Algorithm and DApp Using Blockchain Technology” and “Towards a Secure Infrastructure for the IoT’s Using Deep Learning.” His scholarly contributions have achieved an h-index of 4, with 79 citations and 2 indexed documents, reflecting the growing impact of his work in secure digital ecosystems. He has also been recognized for his innovation and technical creativity in decentralized systems and smart contract applications. Combining academic research with practical software engineering and design expertise, Dr. Ali aims to advance global cybersecurity through intelligent, transparent, and scalable blockchain-based systems that shape the next generation of secure digital environments.

Profiles : Orcid | Google Scholar

Featured Publications

Ali, B., & Chen, G. (2025). Next-generation AI for advanced threat detection and security enhancement in DNS over HTTPS. Journal of Network and Computer Applications.

Ali, B. (2022). An Efficient E-Voting Algorithm and DApp Using Blockchain Technology.

Ali, B. (2021). Towards a Secure Infrastructure for the IoT’s Using Deep Learning. Multidisciplinary International Journal of Research and Development.