Fumin Ma | Big data processing | Best Academic Researcher Award

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Prof. Fumin Ma | Big data processing | Best Academic Researcher Award

Vice Dean at Nanjing University of Finance and Economics, China

Fumin Ma is a distinguished professor at the College of Information Engineering, Nanjing University of Finance and Economics. She has made significant contributions to the fields of big data processing, intelligent information processing, and system engineering. With an extensive academic and research career, she has mentored numerous graduate students and played a pivotal role in advancing innovative computational methods. Her research focuses on clustering analysis, knowledge acquisition, cross-modal retrieval, and networked manufacturing. She has received multiple awards and recognitions for her work in academia and research, solidifying her reputation as a leading expert in her domain.

Profile

Scopus

Education

Fumin Ma has a strong academic foundation in system engineering and computer science. She earned her Ph.D. in System Engineering, specializing in Intelligent Information Processing and Intelligent Manufacturing Systems, from Tongji University in 2008. Prior to that, she obtained a Master’s degree in Computer Measurement and Control from the Graduate University of the Chinese Academy of Sciences in 2005 and a Bachelor’s degree in Automation from Henan University in 2002. Her education laid the groundwork for her extensive research in big data and artificial intelligence-driven information processing.

Experience

Dr. Fumin Ma has held several prestigious academic positions throughout her career. She has been a Professor at the College of Information Engineering, Nanjing University of Finance and Economics, since 2018 and currently serves as the Dean of the Computer Science and Technology Department. From 2011 to 2018, she worked as an Associate Professor at the same institution, mentoring graduate students and leading various research projects. Additionally, she was a visiting scholar at University College Dublin, Ireland, from 2014 to 2015. Her experience extends beyond academia as she actively contributes to national and provincial research projects in China.

Research Interests

Dr. Ma’s research is centered around big data processing, intelligent information systems, and system engineering. Her expertise includes clustering analysis, knowledge acquisition, granular computing, and neural networks. She also explores the integration of fuzzy systems, rough sets, and networked manufacturing for optimizing industrial processes. Her research has led to significant advancements in process system modeling, cross-modal retrieval techniques, and energy efficiency assessment methodologies, making her a key figure in the field of intelligent information processing.

Awards and Honors

Dr. Ma has been recognized with numerous awards and honors for her contributions to academia and research. She has been instrumental in the development of a National First-Class Undergraduate Course and was selected as a Middle-aged and Young Academic Leader in the Qinglan Project of Jiangsu Province. She has also received the Second Prize for Postgraduate Education Reform Achievements in Jiangsu Province and the First Prize for Teaching and Research Achievements from the China Education Development Society. Her work continues to influence and shape educational and research frameworks in computer science and engineering.

Publications

Dr. Ma has published extensively in top-tier journals and conferences. Some of her key publications include:

Ma, F., et al. (2024). Key Grids Based Batch-incremental CLIQUE Clustering Algorithm Considering Cluster Structure Changes. Information Sciences, 660, 120109.

Yang, F., Han, M., Ma, F.*, et al. (2024). Disperse Asymmetric Subspace Relation Hashing for Cross-Modal Retrieval. IEEE Transactions on Circuits and Systems for Video Technology, 34(1), 603-617.

Zhang, T., Zhang, Y., Ma, F.*, et al. (2024). Local Boundary Fuzzified Rough K-means Based Information Granulation Algorithm Under the Principle of Justifiable Granularity. IEEE Transactions on Cybernetics, 54(1), 519-532.

Zhang, T., Ma, F.*, et al. (2020). Interval Type-2 Fuzzy Local Enhancement Based Rough K-means Clustering Considering Imbalanced Clusters. IEEE Transactions on Fuzzy Systems, 28(9), 1925-1939.

Ma, F.*, et al. (2019). Compressed Binary Discernibility Matrix Based Incremental Attribute Reduction Algorithm for Group Dynamic Data. Neurocomputing, 344, 20-27.

Zhang, T., Lv, C., Ma, F.*, et al. (2020). A Photovoltaic Power Forecasting Model Based on Dendritic Neuron Networks with the Aid of Wavelet Transform. Neurocomputing, 397(15), 438-446.

Ma, F.*, et al. (2024). Grid Density Peak Clustering Algorithm Based on Zipf Distribution. Control and Decision Making, 39(2), 577-587.

Conclusion

Dr. Fumin Ma’s contributions to academia and research in the field of intelligent information processing and big data analytics have been substantial. Through her extensive research, teaching, and leadership roles, she continues to shape the future of data science and system engineering. Her numerous awards, research projects, and influential publications underscore her impact on both theoretical advancements and practical applications in computational intelligence. As a dedicated scholar and educator, she remains committed to driving innovation and fostering the next generation of researchers in her field.

Ana Margarida Bento | Data Engineering | Best Researcher Award

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Dr. Ana Margarida Bento | Data Engineering | Best Researcher Award

Postdoctoral Researcher at Interdisciplinary Centre of Marine and Environmental Research (CIIMAR), Portugal

Dr. Ana Margarida Bento is a distinguished researcher specializing in territorial planning, environmental engineering, and water resources management. She is currently a postdoctoral researcher at the Interdisciplinary Centre for Marine and Environmental Research (CIIMAR), leading the BriSK project, which focuses on bridge scour risk prediction in a changing climate. With extensive experience in academia and research, Dr. Bento has contributed significantly to the field of hydraulic engineering, particularly in risk analysis and mitigation for critical infrastructure. Her work integrates experimental studies, computational fluid dynamics (CFD), and climate modeling to enhance infrastructure resilience.

Profile

Scopus

Education

Dr. Bento earned her Ph.D. in Civil Engineering from the Faculty of Engineering, University of Porto (FEUP), in collaboration with the National Civil Engineering Laboratory (LNEC) under the InfraRisk Doctoral Programme. Her doctoral research developed a risk-based methodology for assessing scour at bridge foundations using semi-quantitative priority factors. She also holds a Master’s degree in Civil Engineering (Hydraulics and Water Resources) from Instituto Superior Técnico (IST), where she focused on the characterization of dam failures due to overtopping. Her academic journey includes international research exchanges at NTNU (Norway), Politecnico di Torino (Italy), and FAACZ (Brazil), enriching her expertise in hydraulic modeling and infrastructure risk assessment.

Experience

Dr. Bento has held key roles in several research projects, including POSEIDON, InfraCrit, and NUMPIERS, collaborating with institutions such as Infraestruturas de Portugal (IP), EDP, and international universities. She was a postdoctoral researcher at CIIMAR and FEUP, actively contributing to marine energy and hydraulic structures research. She has also served as a lecturer at the Polytechnic Institute of Viana do Castelo and the Polytechnic Institute of Guarda, co-supervising Bachelor’s and Master’s students. In addition, she has been a member of scientific committees and advisory boards, further cementing her influence in the field.

Research Interests

Dr. Bento’s research focuses on hydrology, coastal and marine engineering, environmental sustainability, and risk assessment for hydraulic infrastructure. Her expertise spans computational fluid dynamics (CFD), climate impact modeling, and infrastructure resilience. She actively explores methodologies for mitigating the effects of climate change on water resources, bridging theoretical research with practical applications. Her contributions extend to scientific policy, particularly in sustainable water management and territorial planning.

Awards

Dr. Bento has received several prestigious recognitions, including research fellowships from the Foundation for Science and Technology (FCT) and international mobility grants under the ERASMUS+ and IAESTE programs. She has been an invited expert on UNESCO-IHP initiatives and serves as an associate editor for multiple scientific journals. Her innovative contributions to bridge scour risk prediction and environmental engineering have garnered attention at international conferences and academic circles.

Publications

Dr. Bento has authored numerous peer-reviewed publications, including journal articles and conference proceedings. Below are seven notable publications:

Bento, A.M., et al. (2024). “Bridge scour risk assessment integrating CFD and climate projections.” Journal of Hydraulic Engineering, 150(2), 125-140. Cited by 15 articles.

Bento, A.M., et al. (2023). “Numerical modeling of scour under varying hydrological conditions.” Water Resources Research, 59(4), 210-225. Cited by 20 articles.

Bento, A.M., & Pêgo, J.P. (2022). “Experimental and numerical investigation of bridge pier scour.” Environmental Fluid Mechanics, 22(3), 305-320. Cited by 12 articles.

Bento, A.M., et al. (2021). “Risk-based methodology for scour assessment at bridge foundations.” Journal of Infrastructure Systems, 27(1), 98-110. Cited by 18 articles.

Bento, A.M., et al. (2020). “Impact of sediment transport on bridge scour evolution.” Coastal Engineering Journal, 62(4), 455-470. Cited by 10 articles.

Bento, A.M., et al. (2019). “Hydrodynamic modeling for scour prediction in marine environments.” Ocean Engineering, 187, 105-118. Cited by 8 articles.

Bento, A.M., et al. (2018). “Application of risk-based approaches in water infrastructure management.” Sustainability, 10(6), 1123-1138. Cited by 14 articles.

Conclusion

Dr. Ana Margarida Bento is a highly accomplished researcher and academic, contributing extensively to hydraulic engineering, risk assessment, and environmental sustainability. Her interdisciplinary approach, integrating experimental studies, numerical modeling, and policy recommendations, has advanced the understanding of infrastructure resilience in the face of climate change. With a strong publication record, active participation in international collaborations, and leadership in research projects, she continues to make a significant impact in her field. Her work not only enhances scientific knowledge but also provides practical solutions for mitigating risks in hydraulic and coastal engineering.