Title: When adventurous individuals emerge

Abstract: Exploration in uncertain and changing environments poses a fundamental dilemma: While it benefits the group by generating valuable information, it imposes direct costs on individual explorers. What conditions allow such adventurous individuals to exist and persist in decentralized collectives? 

We address this question using a normative model of collective foraging in which agents decide whether to commit or remain idle with rewards and information shared across the group. Using dynamic programming and asymptotic analysis, we show that optimal performance arises from structured heterogeneity: A small, heterogeneous subset of risk-taking explorers ventures even when expected returns are negative while the majority of risk-averse individuals commit collectively once conditions become favorable. This decentralized composition matches the efficiency of a centrally coordinated group through simple threshold-based rules. 

The degree of heterogeneity peaks at intermediate commitment cost and moderate environmental switch amplitude but diminished in rapidly changing environments. These results reveal when and why adventurous individuals emerge, showing how collectives self-organize to balance exploration and exploitation under uncertainty.

Title: When adventurous individuals emerge

Abstract: Exploration in uncertain and changing environments poses a fundamental dilemma: While it benefits the group by generating valuable information, it imposes direct costs on individual explorers. What conditions allow such adventurous individuals to exist and persist in decentralized collectives? 

We address this question using a normative model of collective foraging in which agents decide whether to commit or remain idle with rewards and information shared across the group. Using dynamic programming and asymptotic analysis, we show that optimal performance arises from structured heterogeneity: A small, heterogeneous subset of risk-taking explorers ventures even when expected returns are negative while the majority of risk-averse individuals commit collectively once conditions become favorable. This decentralized composition matches the efficiency of a centrally coordinated group through simple threshold-based rules. 

The degree of heterogeneity peaks at intermediate commitment cost and moderate environmental switch amplitude but diminished in rapidly changing environments. These results reveal when and why adventurous individuals emerge, showing how collectives self-organize to balance exploration and exploitation under uncertainty.

Title: How Health Opinions Evolve under News and Social Influence

Abstract: How do social interactions and news exposure shape health-related opinions and behaviors, such as decisions about vaccination? To address this question, I will present a hybrid model of opinion dynamics on directed social networks in which individuals do not update continuously but instead accumulate evidence from socially filtered information and revise their opinions only when that evidence exceeds a threshold. 

This mechanism produces a rich variety of collective outcomes, including consensus, polarization and fragmentation, and these regimes can be organized in parameter space through interpretable controls of platform design, curation and user responsiveness. I will also discuss an extension that incorporates news media as a distinct external source with its own reach, attention level and receptivity. Motivated by vaccination and health information, this framework represents a step toward coupled information: epidemic models in which opinions influence behavior and epidemic prevalence feeds back into the information environment.

Title: How Health Opinions Evolve under News and Social Influence

Abstract: How do social interactions and news exposure shape health-related opinions and behaviors, such as decisions about vaccination? To address this question, I will present a hybrid model of opinion dynamics on directed social networks in which individuals do not update continuously but instead accumulate evidence from socially filtered information and revise their opinions only when that evidence exceeds a threshold. 

This mechanism produces a rich variety of collective outcomes, including consensus, polarization and fragmentation, and these regimes can be organized in parameter space through interpretable controls of platform design, curation and user responsiveness. I will also discuss an extension that incorporates news media as a distinct external source with its own reach, attention level and receptivity. Motivated by vaccination and health information, this framework represents a step toward coupled information: epidemic models in which opinions influence behavior and epidemic prevalence feeds back into the information environment.

Title: On the uniqueness of network identification of Boolean networks

Abstract: Finding conditions on input data that guarantee a wiring diagram has been an open problem since the introduction of algebraic geometry techniques to Boolean network analysis. In this talk, we characterize the data sets that identify a wiring diagram before conducting experiments. We show that the geometric features of the discrete data on an n-dimensional hypercube completely determine if network inference is guaranteed to be unique. This approach also provides a heuristic to minimize the number of candidate wiring diagrams, offering concrete criteria for experiment design.

Title: On the uniqueness of network identification of Boolean networks

Abstract: Finding conditions on input data that guarantee a wiring diagram has been an open problem since the introduction of algebraic geometry techniques to Boolean network analysis. In this talk, we characterize the data sets that identify a wiring diagram before conducting experiments. We show that the geometric features of the discrete data on an n-dimensional hypercube completely determine if network inference is guaranteed to be unique. This approach also provides a heuristic to minimize the number of candidate wiring diagrams, offering concrete criteria for experiment design.