Prof. Dr Jozef Ristvej | Security Sciences | Best Researcher Award |

Prof. Dr. Jozef Ristvej | Security Sciences | Best Researcher Award | 

Professor, at University of Žilina, Slovakia.

Prof. Dr. Jozef Ristvej is a distinguished researcher and academic in crisis management, specializing in disaster risk assessment, decision-making support systems, and security engineering. Currently serving as a Full Professor at the Department of Crisis Management, Faculty of Security Engineering, University of Žilina, Slovakia, he is also the Vice-Rector for International Relations and Marketing. With extensive international experience, he has been a Visiting Scholar at UC Berkeley, USA, and has collaborated with leading institutions worldwide. His work integrates technology, policy, and emergency response strategies to enhance crisis preparedness and resilience.

Professional Profile

Scopus

Orcid

Google Scholar

Education 🎓

Prof. Ristvej holds a Ph.D. in Crisis Management from the University of Žilina, where he focused on the economic impacts of disasters. His academic journey includes research stays at renowned institutions such as the University of Pittsburgh (USA), Tilburg University (Netherlands), and Linköpings University (Sweden). He has also participated in prestigious international programs, including the ISCRAM-TIEMS Summer School on Global Disaster Risks and Humanitarian Assistance.

Professional Experience 💼

Prof. Ristvej has held several key academic and administrative positions:

Vice-Rector for International Relations and Marketing at the University of Žilina (2014–present).

Full Professor in Crisis Management at the Faculty of Security Engineering, University of Žilina (2019–present).

Visiting Scholar at UC Berkeley, USA (2024), focusing on catastrophic risk management.

Research Fellow at the University of Pittsburgh, USA (2010), working on decision-making support systems.

Erasmus Scholar at Linköpings University, Sweden (2003), studying European integration.

Research Interests 🌍

His research primarily revolves around crisis management, disaster risk assessment, decision-making support systems, security engineering, and information systems for emergency response. Prof. Ristvej has contributed to the development of frameworks that improve risk analysis, crisis preparedness, and the integration of technology in disaster response. His work has significant implications for both government policies and private sector risk management strategies.

Awards & Honors 🏆

Throughout his career, Prof. Ristvej has been recognized for his contributions to crisis management and security studies. He has been a key member of Slovak delegations at the UNESCO Youth Forum in Paris and international science fairs in the USA. His leadership in organizing international conferences and academic events has further solidified his reputation as a leading researcher in the field.

Top Noted Publications 📚

Smart city, safety and security – M. Lacinák, J. Ristvej (Citations: 292, Published: 2017, Procedia Engineering 192, 522-527)

On smart city and safe city concepts – J. Ristvej, M. Lacinák, R. Ondrejka (Citations: 124, Published: 2020, Mobile Networks and Applications 25, 836-845)

Data mining and machine learning in the context of disaster and crisis management – A. T. Zagorecki, D. E. A. Johnson, J. Ristvej (Citations: 82, Published: 2013, International Journal of Emergency Management 9 (4), 351-365)

Assessing importance of disaster preparedness factors for sustainable disaster risk management: The case of the Slovak Republic – M. Titko, J. Ristvej (Citations: 58, Published: 2020, Sustainability 12 (21), 9121)

Critical infrastructure protection systems effectiveness evaluation – T. Lovecek, J. Ristvej, L. Simak (Citations: 52, Published: 2010, Journal of Homeland Security and Emergency Management 7 (1))

Conclusion

With his extensive expertise, international collaborations, and impactful research in crisis management, Prof. Dr. Jozef Ristvej is a respected scholar in his field. His dedication to advancing risk assessment, security engineering, and decision-making systems has made significant contributions to both academia and real-world crisis response strategies.

Dr Yan Wang | Risks | Best Researcher Award |

Dr. Yan Wang | Risks | Best Researcher Award

Applied Scientist, at Kennesaw State University, United States

Dr. Yan Wang is a distinguished researcher in data science, analytics, and machine learning, specializing in credit risk modeling, statistical analysis, and investment decision-making. With an exceptional academic background and hands-on industry experience, Dr. Wang has made significant contributions to predictive modeling, fraud detection, and financial risk assessment. Her work integrates advanced statistical techniques, machine learning algorithms, and big data analytics, impacting both academia and industry.

Professional Profile

Scopus

Education 🎓

Dr. Wang holds a Ph.D. in Analytics and Data Science from Kennesaw State University (GPA: 4.00), where she pioneered research in data-driven investment decision-making in peer-to-peer lending. She also earned an M.S. in Statistics from the University of Georgia (GPA: 4.00), further strengthening her expertise in mathematical modeling and predictive analytics. Her foundational education includes an M.S. in Pharmacokinetics (GPA: 3.92) and a B.S. in Pharmacy (GPA: 3.81) from China Pharmaceutical University, providing a unique interdisciplinary perspective in data science applications within finance, healthcare, and pharmaceuticals.

Experience 💼

Currently, Dr. Wang is a Statistician at Credigy Solutions, where she applies advanced analytics and machine learning to credit risk modeling and investment strategies. Her expertise in data visualization, predictive analytics, and risk assessment has led to a 10% reduction in model errors and improved financial forecasting. Previously, she interned at Hexaware Technologies, where she developed fraud detection models for Starbucks, leveraging cost-sensitive learning methods and ensemble techniques.

Research Interest 🔬

Dr. Wang’s research revolves around machine learning applications in financial analytics, statistical modeling, and credit risk assessment. She has developed novel models for predicting loan defaults, fraud detection, and investment risk. Her work integrates time-series analysis, ensemble learning, deep learning, and feature selection techniques to enhance model accuracy and efficiency. She has also contributed to text mining and natural language processing (NLP), applying these techniques to analyze National Science Foundation (NSF) funding trends.

Award 🏅

Dr. Wang has been recognized for her research excellence with multiple accolades, including the Best Poster Award at ACMSE 2019 for her groundbreaking work in fraud detection. Her proposed machine learning models have significantly improved industry-standard risk assessments, and her patent-pending innovation in predictive modeling showcases her contributions to data-driven financial decision-making.

Top Noted Publication 📑

Title: A Survey of Machine Learning Methodologies for Loan Evaluation in Peer-to-Peer (P2P) Lending

Authors: Yan Wang, Xuelei (Sherry) Ni

This book chapter provides a comprehensive overview of machine learning techniques applied to loan evaluation in P2P lending, exploring methodologies such as supervised learning, ensemble models, and deep learning to enhance credit risk assessment and investment decision-making

Conclusion

Yan Wang is an exceptional candidate for the Best Researcher Award, with an impeccable academic record, innovative research, and real-world industry contributions in data science, finance, and machine learning. Strengthening publication output and expanding interdisciplinary collaborations will further enhance their research impact.