Ruodan Liu’s dissertation, completed in 2024 at the University at Buffalo under the guidance of Professor Naoki Masuda, represents a significant contribution to the fields of network science and gender studies. Her research delves into the complexities of dynamic processes on networks, including epidemic and evolutionary dynamics, and addresses pressing issues such as gender imbalance in academia. citeturn0search3
Unraveling Dynamic Processes on Networks
Liu’s work provides a comprehensive analysis of how interconnected systems evolve over time, offering insights into phenomena ranging from disease spread to population dynamics.
Epidemic Dynamics in Temporal Networks
In her dissertation, Liu explores how the timing of connections between individuals influences the spread of diseases within networks. She introduces Markovian temporal network models to study disease propagation, enhancing our understanding of how temporal structures impact epidemic thresholds. This research is particularly relevant in today’s context, where understanding the rapid transmission of diseases through social and technological networks is critical. citeturn0search3
Evolutionary Dynamics on Hypergraphs
Liu extends her research to hypergraphs, a generalized form of graphs where multiple edges connect nodes. She investigates the fixation probability of various node types within hypergraphs and develops analytical methods to model evolutionary behavior under diverse scenarios. This work bridges theoretical biology, network theory, and applied mathematics, offering advanced mathematical approaches to studying population evolution in complex structures. citeturn0search3
Addressing Gender Imbalance in Academia
Beyond network dynamics, Liu’s dissertation tackles the critical issue of gender imbalance in academia, particularly in East Asia. She examines systemic disparities in research output, publication practices, and citation patterns, providing a quantitative analysis of the gender gap and identifying factors contributing to these imbalances. Her work sheds light on the unequal representation of women in high-ranking academic positions and the structural challenges hindering gender equality in research environments. citeturn0search3
Impact and Recognition
Liu’s dissertation has garnered substantial recognition within the academic community. Her findings have been published in prestigious journals, including the European Journal of Applied Mathematics, the SIAM Journal on Applied Mathematics, and the Journal of Informetrics. Her work has been presented at prominent conferences and workshops, where experts have widely acknowledged her contributions. citeturn0search3
Postdoctoral Research and Future Directions
Following her doctoral studies, Liu continues to build on her groundbreaking research as a postdoctoral fellow at Santa Clara University. Her ongoing work focuses on advancing network dynamics and exploring broader applications of gender studies. Areas of future interest include developing more sophisticated models for epidemic and evolutionary dynamics and expanding the study of gender disparities across global academic systems. citeturn0search3
Conclusion
Ruodan Liu’s dissertation represents a blend of mathematical rigor, theoretical innovation, and societal relevance. By examining dynamic processes in networks, evolutionary dynamics, and gender imbalance in academia, Liu has made a lasting contribution to multiple disciplines. Her research enhances our understanding of complex systems and highlights pressing issues that require attention and action. As Liu continues her academic journey, her work serves as a foundation for future research and a source of inspiration for scholars exploring the interconnectedness of networks and society.
