I'm Dawn Chen, a cognitive scientist interested in human and machine learning. My research has combined computational modeling and behavioral experiments to shed light on how humans learn a variety of representations, including relational concepts necessary for analogy and heuristics for efficiently solving problems in a given domain. I've also examined the ways in which representations acquired by machine learning algorithms capture and deviate from human cognition. You can find my papers, presentations, datasets, and code under Publications.
I've just completed a postdoc with Tom Griffiths at the Institute of Cognitive and Brain Sciences at UC Berkeley. I'm now looking for a position in industry as a Software Engineer or Data Scientist, or another role fitting for my skills and experience. My interdisciplinary background in Computational Cognitive Science has provided me with a solid understanding of statistics and machine learning, as well as extensive experience in designing and conducting behavioral experiments, analyzing data, and exploring data to find insights. Moreover, I have many years of programming experience, am fluent in several programming languages, and can quickly learn new languages and tools. You can download my resume here.