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One of the biggest obstacles in deploying Autonomous Vehicle (AV) is that without vehicle-to-vehicle communication, AV has to be able to predict human driver’s intentions and planning and control its action accordingly, while equally importantly, AV also has to behave just like a typical human driver such that other road users can infer the AV’s intentions. We propose to learn the human driver’s mental model in lane change decision making.
With options (i.e., multiple step actions) learned from manual book, hierarchical reinforcement learning achieve human-level learning efficiency and state-of-the-art performance in playing challenge games, e.g., Tennis, Pong, etc.
Detect, extract, and recognise texts in advertisement pictures. The recognized text will be feed to advertisement conversion prediction machine learning models.
Published in Acta Aerodynamica Sinica, 2014
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Published in Journal of Aircraft, 2015
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Published in arXiv preprint arXiv:1909.12465, 2019
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Generate random density perturbations from frequency spectra with Fourier transform. Download paper here. More information here
Undergraduate mathematics course, Florida State University, Mathematics Department, 2018
Instructor for the MAC 2311. This course covers polynomial, trigonometric, exponential, and logarithmic functions; first and second derivatives and their interpretations; definition and interpretation of the integral; differentiation rules; implicit differentiation; applications of the derivative; anti-derivatives; fundamental theorem of calculus.
Undergraduate mathematics course, Florida State University, Mathematics Department, 2018
Solo instructor for MAC 1140.