Mathew Habyarimana | Artificial Intelligence | Best Academic Researcher Award

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Dr. Mathew Habyarimana | Artificial Intelligence | Best Academic Researcher Award

Research Scholar at Durban University of Technology, South Africa

Mathew Habyarimana, Ph.D., is an accomplished electrical engineer with expertise in electrical machines, power electronics, and renewable energy. He is a self-motivated researcher and educator committed to advancing knowledge and mentoring students in the field of electrical engineering. With a strong background in academia and industry, he has contributed significantly to the development of energy systems, power electronics applications, and machine optimization techniques. His career spans several years in research, lecturing, and engineering roles, with a focus on intelligent power systems and electrical energy optimization.

Profile

Scopus

Education

Dr. Habyarimana obtained his Ph.D. in Electrical Engineering from the University of KwaZulu-Natal, Durban, South Africa, in September 2022. His doctoral research, funded by the Eskom Power Plant Engineering Institute (EPPEI), focused on electrical machines and power system optimization. Prior to this, he completed his MSc. in Electrical Engineering at the same institution in 2016, specializing in power electronics. His undergraduate studies were conducted at the University of Rwanda, College of Science and Technology, where he earned a BSc. in Electrical Engineering with a focus on renewable energy. His strong educational foundation has shaped his expertise in energy conversion, machine performance improvement, and sustainable energy solutions.

Experience

Dr. Habyarimana has held various academic and research positions throughout his career. Currently, he is a Postdoctoral Research Fellow at Durban University of Technology, where he is engaged in high-impact research on electrical power systems. Previously, he served as a Postdoctoral Research Fellow at the University of Johannesburg from 2023 to 2024, authoring scientific papers and presenting his findings at international conferences.

His academic contributions also include lecturing positions at Durban University of Technology, where he taught courses such as Illumination and Digital Signal Processing in the Electrical and Electronic Engineering Department. As a Senior Lecturer, he developed curricula, designed assessment tools, and guided students through complex electrical engineering concepts.

Before transitioning into academia, Dr. Habyarimana worked as a Project Engineer at Rwanda Energy Group, contributing to rural electrification projects. Additionally, he served as a mathematics tutor and lab demonstrator at the University of KwaZulu-Natal, mentoring students in power electronics and electrical machines. His extensive experience bridges theoretical research and practical engineering applications.

Research Interests

Dr. Habyarimana’s research interests lie in electrical machines, power electronics, renewable energy, and intelligent power management systems. He is particularly focused on optimizing induction motors, mitigating in-rush currents, and integrating artificial intelligence into power systems for enhanced energy efficiency. His work aims to address challenges in energy sustainability, improve motor efficiency, and develop hybrid energy systems that balance renewable and conventional energy sources.

Awards

Dr. Habyarimana has received multiple accolades for his contributions to research and innovation. He was awarded the Best Commercialization Project by the UKZN Inqubate Intellectual Property initiative in 2014. In addition, he received a Certificate of Appreciation for judging at the Eskom Expo for Young Scientists in 2015. His academic excellence is further recognized through his University Teaching Assistant certification, highlighting his dedication to education and student mentorship.

Publications

M. Habyarimana, G. Sharma, P. N. Bokoro, and K. A. Ogudo, “Intelligent power source selection for solar energy optimization,” International Conference on Artificial Intelligence, Big Data, Computing and Data Communication Systems, 2024.

M. Habyarimana, G. Sharma, and P. N. Bokoro, “The Effect of Tuned Compensation Capacitors in the Induction Motors,” WSEAS Transactions on Power Systems, 2024.

Habyarimana, M., Dorrell, D. G., & Musumpuka, R., “Reduction of Starting Current in Large Induction Motors,” Energies, 2022.

Habyarimana, M., Musumpuka, R., & Dorrell, D. G., “Mitigating In-rush Currents for Induction Motor Loads,” IEEE Southern Power Electronics Conference, 2021.

Habyarimana, M., & Dorrell, D. G., “Methods to reduce the starting current of an induction motor,” IEEE International Conference on Power, Control, Signals and Instrumentation Engineering, 2017.

Venugopal, C., Subramaniam, P. R., & Habyarimana, M., “A Fuzzy Based Power Switching Selection for Residential Application to Beat Peak Time Power Demand,” Intelligent Decision Support Systems for Sustainable Computing, 2017.

Habyarimana, M., & Venugopal, C., “Automated hybrid solar and mains system for peak time power demand,” International Conference on the Domestic Use of Energy, 2015.

Conclusion

Dr. Mathew Habyarimana is a distinguished electrical engineer and researcher whose work significantly impacts electrical power systems and renewable energy integration. His extensive experience in academia and industry, coupled with his research contributions, underscores his commitment to innovation in energy optimization and power electronics. Through his lecturing, mentoring, and research initiatives, he continues to shape the next generation of electrical engineers while advancing knowledge in intelligent power management and sustainable energy solutions.

Nidhi Bhatia | Data-Driven Decision Making | Best Researcher Award

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Ms. Nidhi Bhatia | Data-Driven Decision Making | Best Researcher Award

Doctoral researcher at IIT DELHI, India

Nidhi Bhatia is a dedicated academician and researcher with a keen interest in marketing, sustainability, and social issues surrounding women’s health and hygiene. Her research focuses on understanding consumer behavior, social marketing strategies, and sustainability in business and education. With a strong background in teaching and research, she has contributed significantly to her field through publications, conferences, and collaborative projects. She is currently pursuing her Ph.D. in Marketing at the Department of Management Studies, IIT Delhi, under the supervision of Prof. Biswajita Parida.

Profile

Scopus

Education

Nidhi Bhatia has a strong academic foundation with diverse educational qualifications. She completed her 10th and 12th education from the CBSE board in 2001 and 2003, respectively. She earned a Bachelor of Science degree in Statistics, Mathematics, and Physics in 2006, followed by a Master of Science in Physics, Electronics, and Communication in 2008. She later pursued an MBA in Marketing and Human Resources in 2010. Her academic achievements also include qualifying for the National Eligibility Test (NET) in 2011. She enrolled in the Ph.D. program at IIT Delhi on December 28, 2019, with her research focusing on the antecedents and consequences of tabooness perception around women’s health and hygiene, with an expected submission by March 2025.

Experience

With over a decade of teaching experience, Nidhi Bhatia has served as an Assistant Professor at various institutions. She began her academic career at Radha Govind Engineering College (2010-2011) and later joined Meerut Institute of Engineering and Technology (2011-2016). From 2017 to 2019, she worked as a guest faculty member at the University of Petroleum and Energy Studies, Dehradun. Additionally, she has delivered Entrepreneurship Development Program (EDP) lectures at the National Institute for Entrepreneurship and Small Business Development (NIESBUD) in Noida and Dehradun. Her teaching expertise includes marketing, consumer behavior, and business strategy.

Research Interests

Nidhi Bhatia’s research interests span various aspects of marketing, consumer behavior, and sustainability. Her primary research focuses on social taboos related to women’s health and hygiene, aiming to understand their impact on consumer perception and marketing strategies. She is also interested in sustainable education, green business practices, and digital marketing. Through her research, she seeks to bridge the gap between societal norms and business practices, advocating for inclusive and sustainable policies in marketing and education.

Awards

Nidhi Bhatia has received several recognitions for her contributions to research and academia. She was awarded the Best Paper Award at the International Hybrid Conference on Diversity, Equity & Inclusion: Creating a Value-Based Sustainable Future at IILM Jaipur. Her work on sustainability, marketing, and women’s health has been widely recognized at various international conferences and academic forums.

Publications

Bhatia N., Parida B. (2024). “Taboo in Business and Society: Past, Present and Future.” Global Business Review (Under Review, Sage Publications).

Manchanda K., Bhatia N., Parida B. (2024). “Noteworthiness of Sustainable Education in Higher Education: A Qualitative Study.” European Journal of Education (Published, Wiley-Blackwell, Scopus Indexed, IF 4.5, Cite Score 2.8).

Bhatia N., Parida B. (2024). “Smart Cities’ Approaches to Menstrual Hygiene Management.” 8SCS-2024, IET Smart Cities Symposium, University of Bahrain (Accepted, IET Inspec, IEEE Xplore, Elsevier’s Scopus).

Bhatia N., Parida B. (2023). “Health is Wealth: Importance of Healthcare Management in Smart Cities.” 7SCS-2023, IET Smart Cities Symposium, University of Bahrain (Published, IET Digital Library, IEEE Xplore, Scopus Indexed).

Bhatia N., Manchanda K., Parida B. (2023). “Menstruation Effect on Well-Being: Exploring the Mediating Role of Physical Pain and Psychological Anguish.” ICISAS, Curtin University, Dubai (Published, Springer).

Bhatia N., Parida B. (2023). “Unleashing Societal Norms Around Women’s Health and Hygiene with Social Marketing Strategies.” ANZMAC 2023, New Zealand (Published, Conference Proceedings).

Bhatia N., Parida B. (2023). “Social Marketing Strategies Employed by NGOs to Bring Menstrual Health Awareness.” World Social Marketing Conference, Cali, Colombia (Published, Conference Proceedings).

Conclusion

Nidhi Bhatia is a passionate researcher and educator whose work focuses on marketing, consumer behavior, and social issues related to women’s health and sustainability. Through her research, she seeks to drive positive change in society by addressing taboos and encouraging sustainable business practices. With her extensive teaching experience and numerous publications, she continues to contribute significantly to the academic community. Her dedication to education and research underscores her commitment to fostering meaningful engagement and understanding in her field.

Faye Taxman | Data-Driven Decision Making | Best Researcher Award

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Prof. Faye Taxman | Data-Driven Decision Making | Best Researcher Award

University Professor at George Mason University, United States

Dr. Faye S. Taxman is a distinguished University Professor at George Mason University, where she serves as the Director of the Center for Advancing Correctional Excellence! (ACE!). Her work has had a profound impact on criminal justice policy, implementation science, and evidence-based practices in correctional settings. With decades of experience in criminology, she has contributed significantly to improving interventions for justice-involved populations, particularly in the areas of rehabilitation, health services, and community corrections. A widely cited scholar, Dr. Taxman has received numerous accolades for her groundbreaking research and dedication to the field.

Profile

Orcid

Education

Dr. Taxman earned her Ph.D. in Criminal Justice from Rutgers University in 1982, following an M.A. in the same field in 1981. Prior to that, she completed her undergraduate studies in Political Science and Criminal Justice at the University of Tulsa, where she graduated with honors in 1977. Her academic training laid a strong foundation for her career in research, policy development, and the advancement of evidence-based practices in criminology and public policy.

Professional Experience

Dr. Taxman has held numerous academic and research positions throughout her career. Since 2020, she has been a University Professor at George Mason University’s Scholar School of Policy and Government. She has also served as Director of the Center for Advancing Correctional Excellence! (ACE!) since 2009. Her academic affiliations extend to institutions such as Griffith University, Howard University School of Medicine, and Florida State University. Before joining George Mason University, she held key positions at the University of Maryland, Virginia Commonwealth University, and the Institute for Law and Justice, among others. Her career has been marked by extensive involvement in research projects aimed at improving correctional systems, public safety outcomes, and evidence-based policy applications.

Research Interests

Dr. Taxman’s research focuses on criminal justice policy, correctional rehabilitation, implementation science, and behavioral health interventions for justice-involved individuals. She has been instrumental in developing and evaluating strategies to enhance community corrections, improve substance use disorder treatments, and implement evidence-based practices in justice systems. Her work has emphasized the integration of public health and justice systems, aiming to improve rehabilitation outcomes and reduce recidivism. Her recent projects include studies on supervision conditions, digital interventions for justice-involved individuals, and the development of translational research strategies for policy implementation.

Awards and Recognitions

Dr. Taxman has received numerous prestigious awards for her contributions to criminology and public policy. In 2023, she was honored with the Vollmer Award from the American Society of Criminology for her outstanding scholarship. She has also been recognized with the Scholar School Award for Outstanding Scholarship, the Society for Implementation Research Collaboration Mission Award, and the Joan McCord Award for experimental criminology. Additionally, she was named a Fellow of the American Society of Criminology and the Academy of Experimental Criminology. Her lifetime achievements in sentencing and corrections research have been recognized by the Division of Sentencing and Corrections of the American Society of Criminology. Her scholarship continues to shape the field and influence justice reform initiatives.

Selected Publications

Taxman, F. S., & Pattavina, A. (2021). “Simulation Modeling for Criminal Justice.” Criminology & Public Policy. Cited by 85 articles.

Taxman, F. S., Henderson, C. E., & Young, D. (2019). “Behavioral Health Services and Probation: Evidence-Based Practices.” Journal of Offender Rehabilitation. Cited by 120 articles.

Taxman, F. S., Caudy, M. S., & Rhodes, A. (2018). “Translational Criminology: Applying Research to Justice Practices.” Justice Quarterly. Cited by 97 articles.

Taxman, F. S., & Perdoni, M. (2017). “The Role of Implementation Science in Correctional Settings.” Journal of Criminal Justice Education. Cited by 75 articles.

Taxman, F. S., & Bouffard, J. (2016). “Community Corrections and Risk-Needs Assessment Tools.” Criminal Justice and Behavior. Cited by 140 articles.

Taxman, F. S., & Belenko, S. (2015). “Substance Abuse Treatment in the Criminal Justice System: Implementation and Impact.” Health & Justice. Cited by 130 articles.

Taxman, F. S. (2014). “The Role of Supervision in Reducing Recidivism: Lessons from Evidence-Based Practices.” Corrections Today. Cited by 110 articles.

Conclusion

Dr. Faye S. Taxman is a leading figure in criminology, recognized for her extensive research and commitment to improving the criminal justice system through evidence-based interventions. Her work has influenced policy decisions, program implementations, and research methodologies in the field of criminal justice. Through her leadership, scholarship, and dedication to mentorship, she continues to shape the future of criminal justice and public policy research. Her contributions have left an enduring impact on the advancement of effective correctional practices and justice system improvements.

Ali Mehrizi | Machine Learning | Best Paper Award

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Dr. Ali Mehrizi | Machine Learning | Best Paper Award

Lecturer at Ferdowsi University of Mashhad, Iran.

Ali Mehrizi is a distinguished researcher and lecturer in Artificial Intelligence (AI) and Machine Learning at Ferdowsi University of Mashhad (FUM), Iran. With a wealth of experience exceeding a decade, his expertise spans adaptive probabilistic models, distributed learning, multi-target tracking, time series forecasting, and Gaussian Mixture Probability Hypothesis Density (GMPHD) methods. Dr. Mehrizi has published multiple impactful articles in renowned journals such as Expert Systems with Applications and Fuzzy Sets and Systems. He is deeply committed to advancing the understanding and application of AI techniques and has successfully mentored numerous students in areas ranging from Data Mining to Advanced Operating Systems.

Profile

Google Scholar

Education

Dr. Mehrizi educational background is rooted in Artificial Intelligence. He is currently pursuing a Ph.D. in AI at Ferdowsi University of Mashhad (2017–2024), under the supervision of Professor H. Sadoghi Yazdi. His dissertation focuses on financial time series forecasting using experience-based adaptive learning, a project that has already produced several publications in top-tier journals. Previously, he earned an M.Sc. in AI from Azad University of Mashhad (2011–2013), where he worked on adaptive semi-supervised learning, optimizing self-organizing map models. His early academic journey began with a B.Sc. in Computer Engineering from the University of Birjand, later transferring to Azad University of Mashhad.

Experience

Dr. Mehrizi professional career spans various roles, beginning in 2001 when he became the IT & Network Manager at the Faculty of Engineering. In this capacity, he significantly improved the system performance and network management. Since 2011, he has been involved in research in AI and Machine Learning, contributing to the development of machine learning models and publishing his findings in high-impact journals. He has also served as a lecturer since 2013, teaching a variety of undergraduate and graduate courses, including Data Mining, Operating Systems, and Advanced Operating Systems. As a researcher, he has mentored students in their theses, particularly in machine learning and pattern recognition, fostering the next generation of AI experts.

Research Interests

Dr. Mehrizi  research interests are broad, focusing on several key areas within the domain of AI. His work on distributed adaptive learning, particularly through Diffusion LMS and Diffusion RLS, aims to optimize decentralized data processing for dynamic systems. In addition, he has contributed to probabilistic and hypothesis-based learning, exploring the use of Gaussian Mixture Probability Hypothesis Density (GMPHD) models for uncertainty-based learning and tracking. His research also delves into time series analysis and forecasting, with a particular focus on financial markets. Dr. Mehrizi’s interest in multi-target tracking extends to real-time tracking algorithms, emphasizing performance in noisy and incomplete data environments. He is also committed to semi-supervised learning, exploring hybrid methods that bridge supervised and unsupervised learning approaches in scenarios with limited labeled data.

Awards

Dr. Mehrizi contributions to the fields of AI and machine learning have earned him recognition in various academic and professional circles. He has been nominated for multiple awards for his research, particularly in adaptive learning and time series forecasting. His work is highly regarded in the academic community, and he continues to push the boundaries of AI research, especially in the areas of distributed learning and multi-target tracking.

Publications

Dr. Mehrizi has authored several articles in well-respected journals in AI and machine learning. His key publications include:

Mehrizi, A., & Yazdi, H. S. (2019). “Adaptive probabilistic methods for long-term financial time series forecasting.” Expert Systems with Applications.

Mehrizi, A., & Yazdi, H. S. (2020). “Semi-supervised learning using GSOM for adaptive classification.” Fuzzy Sets and Systems.

Mehrizi, A. (2022). “Distributed adaptive learning for dynamic systems using Diffusion LMS and RLS.” Emerging Markets Finance and Trade.

Mehrizi, A., & Yazdi, H. S. (2021). “Gaussian Mixture Probability Hypothesis Density for multi-target tracking.” Journal of Machine Learning Research.

These publications have been cited extensively by various researchers in the fields of machine learning, AI, and financial forecasting, underscoring Dr. Mehrizi’s significant impact on the academic community.

Conclusion

Dr. Ali Mehrizi is a leading researcher and educator in the field of Artificial Intelligence and Machine Learning, with a deep commitment to advancing these fields through his innovative research. His extensive academic background and his practical experience in both teaching and real-world applications have made him an invaluable asset to Ferdowsi University of Mashhad. With a strong focus on adaptive learning, probabilistic models, and time series forecasting, Dr. Mehrizi continues to contribute to the evolution of AI. His work not only shapes academic research but also provides vital insights into practical AI solutions for industries like finance and engineering. As a mentor and educator, he remains dedicated to shaping the future of AI professionals and researchers.

Busuyi Akeredolu | Machine Learning | Best Researcher Award

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Busuyi Akeredolu | Machine Learning | Best Researcher Award

Lecturer at Lagos State University of Education, Nigeria

Busuyi E. Akeredolu is an accomplished Earth Scientist and Geospatial Data Analyst with over ten years of experience. His expertise spans mineral exploration, environmental assessments, electrification planning, and groundwater investigation. Akeredolu’s experience encompasses both office and field operations, where he has been instrumental in satellite image analysis, geophysical data processing, and spatial decision support. His professional background also includes providing technical support for various multidisciplinary projects, blending his scientific skills with real-world applications in resource management and environmental sustainability.

Profile

Orcid

Education

Akeredolu’s academic journey is marked by a solid foundation in geophysics. He is currently pursuing a Ph.D. in Exploration Geophysics at the Federal University of Technology, Akure (FUTA), expected in 2024. He holds an M.Tech. in Exploration Geophysics, also from FUTA (2017), and a B.Sc. in Applied Geophysics from Obafemi Awolowo University (OAU), Ile-Ife (2012). Additionally, he has enhanced his technical skills through certifications such as a Post Graduate Diploma in Project Management and a Certificate in Remote Sensing and GIS, further expanding his interdisciplinary knowledge and capabilities.

Experience

Akeredolu has accumulated extensive professional experience in the geophysical field, including his current role as a Field Geophysicist at Mukolak Geoconsult Nigeria Ltd. Since June 2023, he has conducted magnetic and resistivity data acquisition, processing, and interpretation for mineral exploration projects, contributing to mapping and identifying mineralized zones. His previous roles include serving as a Project Planning Specialist at Protergia Energy Nigeria Ltd. (2022-2023), where he supported off-grid mini-grid electrification projects. Earlier, Akeredolu worked as a Technical Assistant at Bluesquare Belgium (2019-2020), aiding in data management and training for health sector projects. His experience in environmental and geospatial analysis has also been instrumental in environmental assessments and community consultations at Sahel Consult, Nigeria.

Research Interest

Akeredolu’s research interests focus on geophysical methods for groundwater exploration and environmental impact assessments. His work includes applying geophysical data to understand groundwater systems, vulnerability, and aquifer characteristics, as well as studying the impact of environmental factors on mineralization and resource potential. Akeredolu has also delved into the integration of geophysical data with remote sensing techniques to enhance the prediction and management of groundwater resources, particularly in mining areas. His current research aims to develop advanced models for groundwater prediction and resource management using clustering and regression techniques.

Awards

Akeredolu has been recognized for his contributions to geophysics and the environment. His award nominations include the prestigious “Geophysicist of the Year” award by the Society of Exploration Geophysicists (SEG), reflecting his consistent excellence and innovative work in the field. He has also been nominated for awards related to his contributions to sustainable development in environmental science, particularly his work in groundwater resource management and environmental impact assessments.

Publications

Akeredolu, B. E., Adiat, K. A. N., Akinlalu, A. A., Olayanju, G. M., & Afolabi, D.O. (2024). Spatial characterisation of groundwater systems using fuzzy c-mean clustering: A multiparameter approach in crystalline aquifers. Resources, Conservation and Recycling, 100051, ISSN 2211-148, https://doi.org/10.1016/j.rines.2024.100051.

Adegbola, R.B., Whetode, J., Adeogun, O., Akeredolu, B., & Lateef, O. (2023). Geophysical Characterization of the subsurface using Electrical Resistivity Method. Journal of Research and Review in Science, 10, 14-20, DOI: 10.36108/jrrslasu/2202.90.0250.

Akeredolu, B. E., Adiat, K. A. N., Akinlalu, A. A., & Olayanju, G. M. (2022). The Relationship Between Morpho-Structural Features and Borehole Yield in Ilesha Schist Belt, Southwestern Nigeria: Results from Geophysical Studies. Earth Sciences, 11(1), 16-28, doi: 10.11648/j.earth.20221101.13.

Adiat, K. A. N., Akeredolu, B. E., Akinlalu, A. A., & Olayanju, G. M. (2020). Application of logistic regression analysis in prediction of groundwater vulnerability in gold mining environment: a case of Ilesa gold mining area, southwestern, Nigeria. Environmental Monitoring and Assessment, 192(9), doi:10.1007/s10661-020-08532-7.

Adiat, K. A. N., Adegoroye, A. A., Akeredolu, B. E., & Akinlalu, A. A. (2019). Comparative assessment of aquifer susceptibilities to contaminant from dumpsites in different geological locations. Heliyon, 5(5), e01499.

Bawallah, M. A., Akeredolu, B. E., et al. (2019). Integrated Geophysical Investigation of Aquifer and its Groundwater Potential in Camic Garden Estate, Ilorin Metropolis North-Central Basement Complex of Nigeria. IOSR Journal of Applied Geology and Geophysics, 7(2), 01-08.

Akinlalu, A. A., Akeredolu, B. E., & Olayanju, G. M. (2018). Aeromagnetic mapping of basement structures and mineralisation characterisation of Ilesa Schist Belt, Southwestern Nigeria. Journal of African Earth Sciences, 138, 383-389.

Conclusion

Busuyi E. Akeredolu stands as a highly skilled and experienced Earth scientist whose expertise spans geophysical data analysis, mineral exploration, and environmental management. His work has not only contributed to the academic field but has also had a direct impact on practical applications in resource management and environmental sustainability. Akeredolu’s research continues to provide valuable insights into groundwater systems, mineral exploration, and environmental impact assessments, marking him as a leader in his field. His continued commitment to scientific innovation and practical applications will undoubtedly shape the future of Earth sciences and geospatial data analysis.