Congratulations to Prof. Mridul Aanjaneya for receiving the Faculty Early Career Development (CAREER) Award from the National Science Foundation (NSF) for his project titled "CAREER: Modeling and Simulating Generalized Diffusion for Computer Graphics and Computational Science"! The award duration is for five years starting from April 1st, 2023 to March 31st, 2028. The total budget is $499,995.
The CAREER program is an NSF-wide activity that offers the National Science Foundation's most prestigious award in support of early-career faculty who have the potential to serve as academic role models in research and education and to lead advances in the mission of their department or organization.
Many problems that arise in computer graphics (such as virtual painting and phase changes like ice formation and dendrite growth) are driven by diffusion as pigment, crystals, or neural branches spread. The predominant model employed to capture diffusion is Fourier's law. However, this formulation prevents the simulation of anomalous diffusive processes, where diffusion occurs either faster (super-diffusion) or slower (sub-diffusion) than the rate predicted by Fourier's law. Currently, there is a need for efficiently simulating and visualizing super-diffusive phenomena, such as the super-spreader events for disease propagation witnessed during the COVID-19 pandemic or the melting of the permafrost due to global warming. This project will push the frontiers of physics simulation in computer graphics by developing a general framework for efficiently simulating all kinds of diffusive processes in large-scale applications. Project outcomes will have broad impact by supporting the visualization of such complex physical processes at greatly expanded scales. Additional broad impact will derive from the ability to run high resolution simulations on commodity workstations, which will allow a broad audience, particularly students in STEM, to simulate large-scale problems on their own workstations that previously may have required less-accessible enterprise-grade computational resources. Outreach and educational activities, such as workshops, will leverage diversity programs at Rutgers University to recruit and support students from under-represented groups.
More information about this award is available at the NSF website: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2238955&HistoricalAwards=false