Wenyan Bi is a Postdoctoral Associate at Yale specializing in computational models of human visual perception, with eight years of experience bridging probabilistic modeling, physics-based simulation, and perceptual experiments. She designs and implements generative physics engines and online Bayesian inference pipelines—often combining Julia/Gen particle filters with C++/Python simulation and Singularity containers—to probe how observers infer material properties like cloth behavior. Her skill set spans deep learning (TensorFlow, PyTorch), high-performance rendering and simulation (Nvidia FleX, Blender), VR/Unity development, and large-scale psychophysics via web crowdsourcing and fMRI. Wenyan’s work uniquely integrates graphics, psychophysics, and probabilistic programming to make inference about the physical world tractable and testable in humans. Based in New Haven, she pairs rigorous experimental design with production-ready engineering across HPC and cloud environments.
9 years of coding experience
4 years of employment as a software developer
Doctor of Philosophy - PhD, Cognition and Neuroscience, 3.85/4.0, Doctor of Philosophy - PhD, Cognition and Neuroscience, 3.85/4.0 at American University
Bachelor's degree, PSYCHOLOGY, 88.8/100, Bachelor's degree, PSYCHOLOGY, 88.8/100 at Beijing Normal University
Contributions:12 commits, 11 pushes, 1 branch in 1 year 6 months
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