Fangxia Zhao | Computational Methods | Best Researcher Award

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Mrs. Fangxia Zhao | Computational Methods | Best Researcher Award

Associate Professor at Capital University of Economics and Business, China

👨‍🎓 Profiles

Scopus

Orcid

Early Academic Pursuits 🎓

Dr. Fangxia Zhao embarked on her academic journey with a strong foundation in Transportation Engineering. Her advanced studies and research helped her gain a deep understanding of complex transportation networks and big data analytics. Over the years, she honed her expertise in the modeling of traffic systems, urban mobility, and data-driven optimization. Her academic pursuits, supported by several national-level projects, allowed her to make significant strides in theoretical research, laying the groundwork for her future professional achievements.

Professional Endeavors 💼

Dr. Zhao is currently an Associate Professor and Master’s Supervisor at the School of Management Engineering, where she also serves as the Head of the Department of Big Data. With years of academic leadership and research guidance, she has led cutting-edge projects funded by prestigious research bodies, including the Central University Research Fund and University Research Start-up Fund. Throughout her career, she has actively contributed to national and provincial research projects, consistently pushing the boundaries of transportation modeling and big data analytics.

Teaching Experience 👩‍🏫

Dr. Zhao is a dedicated educator, teaching courses such as:

  • Computer Network Technology and Applications
  • Data Structures
  • Principles and Applications of Databases
  • Python Programming Design
  • Green, Intelligent, and Shared Transportation

Her teaching focuses on equipping students with the skills needed to succeed in data science, network optimization, and smart transportation systems. She emphasizes hands-on learning and problem-solving, ensuring that her students are well-prepared for the challenges of modern transportation engineering.

Contributions and Research Focus 🔍

Dr. Zhao’s primary research interests include:

  • Complexity Modeling of Transportation Networks 🚗
  • Big Data Analysis in Transplantation 💉
  • Optimization of Urban Mobility 🏙️
  • Intelligent and Green Transportation 🌱

Her work has played a pivotal role in advancing transportation research, especially in the areas of electric vehicle behavior and network optimization. Through mathematical modeling, she has contributed to understanding how factors such as travel mode choice, vehicle scheduling, and urban road evolution influence the design of more efficient, sustainable, and intelligent transportation systems.

Academic Cites 📚

Dr. Zhao’s research has gained widespread recognition, particularly in the realms of transportation modeling and big data analytics. Her papers have been cited numerous times, including high-impact articles on the evolutionary dynamics of transportation networks, the role of electric vehicles, and the integration of bus services. Her work on the coevolution of population distribution and road networks has been particularly influential, establishing her as a key figure in the field of spatial economics and network theory.

Impact and Influence 🌟

Dr. Zhao’s influence in the academic community is reflected in her extensive publication record, including SCI-indexed papers in leading journals such as Physica A, Networks & Spatial Economics, and Plos One. With over 20 academic papers, she has made major contributions to the study of transportation networks, population distribution, and disaster prevention systems. Her research is widely cited, and her contributions are used by scholars and industry professionals to design smarter, more resilient transportation systems.

Technical Skills 💻

Dr. Zhao is a skilled data scientist, proficient in a variety of technical tools essential for big data analysis and computational modeling. Her expertise includes:

  • Python Programming 🐍
  • Database Management 🗄️
  • Network Design Optimization 🛠️
  • Data Visualization 📊
  • Algorithm Development ⚙️

These skills allow her to analyze complex datasets, develop robust optimization models, and design effective algorithms that improve transportation efficiency and sustainability. Additionally, her involvement in developing software like the School Bus Scheduling Solver and MaaS Systems highlights her technical prowess in real-world applications.

Invention Patents and Software Copyrights 💡

In addition to her research papers, Dr. Zhao holds a national invention patent for the Railway Disaster Prevention System and has developed two software copyrights:

  • School Bus Scheduling Solver
  • MaaS System Based on Knowledge Graphs

These patents and software showcase her ability to transform research ideas into practical solutions, driving innovation in the field of transportation safety and mobility services.Dr. Zhao’s legacy is marked by her pioneering work in the intersection of transportation, data science, and urban development, setting the stage for future breakthroughs in smart mobility and sustainable transportation systems.

Top Noted Publications

Multi-depot vehicle scheduling with multiple vehicle types on overlapped bus routes

  • Authors: Shang, H., Liu, Y., Wu, W., Zhao, F.
    Journal: Expert Systems with Applications, 2023

Role of electric vehicle driving behavior on optimal setting of wireless charging lane

  • Authors: Zhao, F., Shang, H., Cui, J.
    Journal: Physica A: Statistical Mechanics and Its Applications, 2023

Integration of conventional and customized bus services: An empirical study in Beijing

  • Authors: Shang, H., Chang, Y., Huang, H., Zhao, F.
    Journal: Physica A: Statistical Mechanics and Its Applications, 2022

Role of transportation network on population distribution evolution

  • Authors: Zhao, F.X., Shang, H.Y.
    Journal: Physica A: Statistical Mechanics and Its Applications, 2021

 

 

Maurizio Dapor| Computational Methods | Best Researcher Award

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Dr. Maurizio Dapor| Computational Methods | Best Researcher Award

Physicist at Fondazione Bruno Kessler, Italy

Maurizio Dapor is an esteemed Italian physicist and Senior Research Scientist at the Interdisciplinary Laboratory for Computational Science at ECT*-FBK. Born on April 23, 1959, he has made significant contributions to both theoretical and experimental physics. With dual habilitations as a Full Professor in these fields, Dapor has been pivotal in advancing computational methods in materials science. His role as an Associate Editor for Computational Materials Science and various visiting professorships across Europe further exemplify his commitment to research and education. Recognized as one of Stanford’s Top 2% Scientists, his work continues to impact the scientific community.

 🎓Profile: 

Education:

Dapor earned his M.Sc. in Physics with Summa Cum Laude from the University of Trento in 1984. He later pursued a Ph.D. in Materials Science and Engineering from the same institution, completing it in 2013. His educational journey began at Liceo Antonio Rosmini, where he graduated with a High School Diploma in 1978. This strong academic foundation has enabled him to excel in various roles in academia and research, contributing extensively to the scientific understanding of materials and their applications.

Professional Experience:

With over three decades of experience, Dapor has held key positions, including Senior Scientist at ECT* and Head of the FBK Interdisciplinary Laboratory for Computational Science. He has served as a Teaching Fellow at the University of Trento, focusing on Solid State Physics and Computational Methods. His international experience includes visiting professorships at Gdansk University of Technology and the University of Sheffield, enhancing his global academic profile. Additionally, Dapor has contributed as a scientific consultant at ETH Zurich, reinforcing his expertise in computational materials research and development.

Research Focus:

Maurizio Dapor’s research primarily centers on computational science and its application to materials physics. He investigates complex phenomena in solid-state systems and develops innovative computational methods to enhance our understanding of material properties. His work addresses critical challenges in transport phenomena and aims to bridge theoretical insights with practical applications. By focusing on interdisciplinary collaborations, Dapor’s research not only advances theoretical frameworks but also contributes to the development of cutting-edge materials for various technological applications.

Awards and Honors:

Dapor’s contributions to physics and materials science have earned him notable recognition, including the distinction of being listed among Stanford’s Top 2% Scientists. His academic achievements are further highlighted by two National Scientific Habilitations as a Full Professor in both Theoretical and Experimental Physics of Matter. His work as an Associate Editor for Frontiers in Materials demonstrates his leadership in advancing the field. These accolades reflect his dedication to research excellence and his influence on the scientific community.

📚Publication Top Notes:

Title: Charge Phenomena in the Elastic Backscattering of Electrons from Insulating Polymers
  • Authors: Dapor, M.
    Publication Year: 2024
    Citations: 0
Title: Electron-induced hydrogen desorption from selected polymers (polyacetylene, polyethylene, polystyrene, and polymethyl-methacrylate)
  • Authors: Dapor, M.
    Publication Year: 2024
    Citations: 1
Title: The role of low-energy electrons in the charging process of LISA test masses
  • Authors: Taioli, S., Dapor, M., Dimiccoli, F., Villani, M., Weber, W.J.
    Publication Year: 2023
    Citations: 11
Title: Mechanical Properties of Twisted Carbon Nanotube Bundles with Carbon Linkers from Molecular Dynamics Simulations
  • Authors: Pedrielli, A., Dapor, M., Gkagkas, K., Taioli, S., Pugno, N.M.
    Publication Year: 2023
    Citations: 6
Title: The Role of Molecular Structure in Monte Carlo Simulations of the Secondary Electron Yield and Backscattering Coefficient from Methacrylic Acid
  • Authors: Wiciak-Pawłowska, K., Winiarska, A., Taioli, S., Franz, M., Franz, J.
    Publication Year: 2023
    Citations: 0
Title: Spin-polarization after scattering
  • Authors: Dapor, M.
    Publication Year: 2023
    Citations: 1
Title: In search of the ground-state crystal structure of Ta2O5 from ab initio and Monte Carlo simulations
  • Authors: Pedrielli, A., Pugno, N.M., Dapor, M., Taioli, S.
    Publication Year: 2023
    Citations: 5

 

 

 

D. Easwaramoorthy | Computational Methods | Best Researcher Award

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Assoc Prof Dr. D. Easwaramoorthy | Computational Methods | Best Researcher Award

Associate Professor at Vellore Institute of Technology, Vellore, India

Dr. D. Easwaramoorthy is an Associate Professor in the Department of Mathematics at Vellore Institute of Technology, Tamil Nadu, India. With a passion for mathematics and education, he has dedicated over 11 years to teaching and nurturing the next generation of mathematicians. Dr. Easwaramoorthy’s commitment to academic excellence is evident through his extensive research and publication record, which has earned him recognition both nationally and internationally. He actively engages in interdisciplinary research and is known for his contributions to fuzzy mathematics and fractal analysis.

🎓Profile:

Education:

Dr. Easwaramoorthy holds a Ph.D. in Mathematics from The Gandhigram Rural Institute, where he completed his thesis on Fuzzy Fractal Analysis with Applications. He earned his M.Sc. in Mathematics from Bharathidasan University with a focus on the Stone-Weierstrass Theorem, achieving a commendable 79.5%. His academic journey began with a B.Sc. in Mathematics from Bishop Heber College, where he excelled with 82%. His educational qualifications reflect a strong foundation in mathematical principles, further enhanced by various certifications in advanced topics, including machine learning and data science.

Professional Experience:

Dr. Easwaramoorthy has over 16 years of research experience and 11 years of teaching experience. He began his academic career as a Junior Assistant Professor at Vellore Institute of Technology and has progressed to his current role as an Associate Professor. Throughout his tenure, he has taught various courses, including Discrete Mathematics, Graph Theory, and Machine Learning. His role as a Ph.D. guide demonstrates his commitment to mentoring aspiring researchers. Dr. Easwaramoorthy’s experience is complemented by participation in international conferences and collaborative projects, enhancing his profile as a well-rounded academic.

Research Focus:

Dr. Easwaramoorthy’s research primarily focuses on Fractal Analysis, Fuzzy Mathematics, and Signal and Image Analysis. His notable work includes publications in peer-reviewed journals and contributions to various academic books. He is particularly interested in applying mathematical concepts to real-world problems, emphasizing the significance of fuzzy logic and fractals in various domains. His involvement in a UGC-funded project exploring chaotic dynamics in the human brain demonstrates his interdisciplinary approach to research. Dr. Easwaramoorthy continues to explore new frontiers in mathematics, aiming to contribute to both theoretical and applied mathematics.

Awards and Honors:

Dr. Easwaramoorthy has received several accolades for his contributions to mathematics, including the Young Scientist Award at the International Scientist Awards on Engineering, Science, and Medicine. He qualified for the Tamil Nadu State Eligibility Test (TNSET) in 2017, showcasing his proficiency in mathematical sciences. Additionally, he was awarded the GRI-Fellowship at The Gandhigram Rural Institute, further recognizing his academic achievements. His accolades reflect not only his research excellence but also his commitment to fostering a culture of academic achievement and innovation.

📚Publication Top Notes:

Generation of Fractals via Iterated Function System of Kannan Contractions in Controlled Metric Space
    • Authors: Thangaraj, C., Easwaramoorthy, D., Selmi, B., Chamola, B.P.
    • Year: 2024
    • Citations: 6
Enumeration of Multivariate Independence Polynomial for Iterations of Sierpinski Triangle Graph
    • Authors: Nithiya, K.S., Easwaramoorthy, D.
    • Year: 2024
    • Citations: 0
Multifractal Detrended Fluctuation Analysis on COVID-19 Dynamics
    • Authors: Dhanzeem Ahmed, M., Easwaramoorthy, D., Selmi, B., Darabi, S.
    • Year: 2023
    • Citations: 1
An Integrated Perspective of Fractal Time Series Analysis for Infected Cases of COVID-19
    • Authors: Gowrisankar, A., Easwaramoorthy, D., Valarmathi, R., Ananth, C., Vasiliev, I.
    • Year: 2023
    • Citations: 0
Fractal Based Automatic Detection of Complexity in COVID-19 X-ray Images
    • Authors: Thangaraj, C., Easwaramoorthy, D., Muhiuddin, G., Selmi, B., Kulish, V.
    • Year: 2023
    • Citations: 0
Fractals via Controlled Fisher Iterated Function System
    • Authors: Thangaraj, C., Easwaramoorthy, D.
    • Year: 2022
    • Citations: 2
Generalized Fractal Dimensions Based Comparison Analysis of Edge Detection Methods in CT Images for Estimating the Infection of COVID-19 Disease
    • Authors: Thangaraj, C., Easwaramoorthy, D.
    • Year: 2022
    • Citations: 9