Quantifying how individual behavior shapes collective outcomes: A conversation with Gökçe Dayanıklı
- NITMB
- Feb 26
- 4 min read
The NSF-Simons National Institute for Theory and Mathematics in Biology comprises a wide array of investigators driving innovation at the interface of mathematics and biology. NSF-Simons NITMB Affiliate Members bring unique perspectives vital for developing new mathematics and inspiring biological discovery. One such NITMB Affiliate Member integrating mathematics and biology to explore how individual behavior shapes societal outcomes is Gökçe Dayanıklı.
Gökçe Dayanıklı is an assistant professor of Statistics at the University of Illinois Urbana-Champaign (UIUC). Dayanıklı also holds affiliate appointments in the Department of Industrial & Enterprise Systems Engineering and the Carl R. Woese Institute for Genomic Biology at UIUC. Her work focuses on the mathematical and computational foundations of large-scale multi-agent systems, especially in settings relevant to biology, public health, financial systems, and energy markets.
We spoke with Gökçe Dayanıklı to discover how integrating mathematical tools in the study of human behavior is generating new insight into societal outcomes.
What is a big question you’ve been asking throughout your research?
“I study how individual behavior and decision‑making shape collective outcomes in large, complex systems, especially those involving uncertainty, possible networks, and strategic interactions and decision-making processes of the individuals. A guiding question is: ‘How can we mathematically model and influence agent (individuals, banks, electricity producers, etc.) behavior to improve societal outcomes?’”
What disciplines does your research integrate?
“My research integrates ideas from stochastic control, game theory, mean field games, machine learning, and mathematical biology. I collaborate across disciplines, particularly with microbiology and engineering, to ensure that the mathematical models I build capture the key mechanisms in real systems.”
Where do you find inspiration?
“I am inspired by societal problems where individual decision-making matters, such as infectious disease spread, energy market operations, or financial stability. Talking with colleagues in different areas such as biology, public health, statistics, mathematics, and engineering often sparks new questions and helps me understand what mathematical tools can help us model real-life phenomena with tractable models.”
What aspects of your work could be interesting to mathematicians or applied to biology?
“One aspect is to define and characterize different equilibrium structures. In large population dynamic and stochastic models, we first characterize the equilibrium of interest with forward-backward differential equations. Then my work mathematically raises fundamental questions about this characterization proof and the existence and uniqueness of solutions. Except for special cases where explicit solutions can be found, many solutions require implementation of numerical algorithms, where the proof of convergence for these learning algorithms for large-population systems would be of interest. Biologically, these models provide a way to quantify human behavioral response in policy making, such as during an epidemic spread, and can help explore optimal intervention design.”
What excites you about NITMB?
“NITMB’s mission of advancing biology through mathematical theory strongly resonates with me. I am excited about its commitment to interdisciplinary research and bringing many experts from different areas together. The Institute lowers barriers to interdisciplinary collaboration, provides access to domain expertise, and creates opportunities to translate theoretical models into biologically meaningful insights. Being part of NITMB provides me with the environment and community to further my work at the interface of mathematics and biology. It also helps me interact with other researchers to share methods and tools through workshops or long programs that I am looking forward to being a part of.”
What career achievement are you most proud of?
“I am particularly proud of receiving an NSF DMS grant that supports my research on incorporating behavioral response modeling to optimize epidemic mitigation policies. It reflects my efforts to connect mathematical theory with real-world public health challenges, as well as the interdisciplinary collaborations that I’ve built for this task, such as with co-PI Dr. Pamela Martinez.”
Outside of your research, what other interests do you have?
“I like spending time outdoors, walking or biking by the lake or the river. I like being active, especially running. Nowadays, since the winter has been harsh, I spend time in coffee shops and really enjoy reading a book while getting some tea. I also enjoy going to concerts of my favorite bands.”
What are you hoping to work on in the future?
“Going forward, I plan to deepen my work on learning from data and model-free learning, including the incorporation of Bayesian methods in mean field games, (inverse) reinforcement learning, and methods for learning individuals’ objective functions from observed behavior. I am also excited to explore connections of my work to evolutionary game theory, which I believe will open new research directions in epidemic control and biological systems. I have also been working on modeling altruism and introducing new equilibria notions in mean field games, and I would be interested in extending these ideas. Continued interdisciplinary collaborations, especially within NITMB, will play a big role in these efforts.”
Is there anything else you would like the NITMB community to know about you?
“I value collaboration and interdisciplinary exchange and learning from the expertise of others, and I am eager to contribute to the intellectual community at NITMB. I believe that combining rigorous mathematics with biological insight is essential for addressing many modern challenges, and I look forward to being part of that shared mission.”
