Sebastian Dobon is a talented Software Engineer at Verily, specializing in building infrastructure for ML efforts. With a passion for neuroscience, biology, music, art, and technology, Sebastian's programming projects range from creating online spaces for students to discover events on campus to conducting studies on cooperative behavior among schooling fish to avoid predators.
Sebastian's expertise also extends to machine learning and artificial intelligence, where he has developed projects such as an image recognition scavenger hunt played using a cell phone's camera and a lyric generator for hit songs using Long Short-Term Memory Recurrent Neural Networks (LSTM RNN) to mimic lyrics from different decades. Additionally, Sebastian has explored the field of robotics, enhancing localization in an autonomous maze solver robot through locally weighted regression. With a creative touch, Sebastian has even conceptualized an art project involving covering every building in the world with fur.
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