def: which professors to collaborate and how that contributes to problem I wish to tackle ![[callmebyyourname.png]] My music starts from my forte; simulation-based test. This builds trust for approximations, especially for hierarchical Bayesian infamous for complex posterior geometry. I cannot find any better advisor than Hazhir. This research can be combined with large-scale simulation such as John's climatology as it would necessitate approxiate Bayesian computation for real-time decision. To design sample-based projections, policies, and tests, collaboration with decision-makers on top of digitized platform is crucial which Enroads can provide with John's help. Johan's durable dominance research helped me see the woods. Heralding unavoidable inequity with mathematical rigor touched my heart as it overlaps with my vision, affordable analytics. Johan's expertise in agent-based modeling and high valuation of Bayesian also fits well with spatio-temporal dynamic aggregation concept I wish to implement. Nelson and John's paper on capability trap, justified my desire to estimate failure function for product's life-cycle management. Pallet companies' request to operationalize pallet flow forecasts for reverse logistics taught me two lessons: forecasts matter and platform value of pallet. Problems of inequality from durable dominance or non-affordable analytics can be approached through win-win strategy with data-sharing. in Korea, to factories on which products are Reverse logistics for pallet company which aske and Tamara Broderick in the MIT Center for Collective Intelligence. Prof. Almaatouq’s project on highthroughput experimentation matches my ambition of designing sets of models that give precise boundaries of their effectiveness by parameterizing the scale and environment-dependent nature of such models. My interests in networks and agent-based models also align with his work on rewiring algorithms for enhanced collaborations. Prof. Malone’s interest in human-machine collaboration aligns with my goal of understanding the changes of human behaviors in computer-supported settings along with how to measure collective intelligence in such heterogeneous environments. I am looking forward to constructing social models and experiments to discover what makes a good collaborative team of humans and AI in terms of individual satisfaction, team performance, and adaptation to the larger organization. Also, Profs. Sinan Aral, Dean Eckles, and David Rand’s insights on online field experiment and information diffusion will help me understand how information technology changes the landscape of human communications and collaborations at population scales. After graduation, I hope to continue my research on collective intelligence as a professor in computational social science.