Christopher Algire

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Chris is a PhD student at the University of Missouri’s Institute for Data Science and Informatics. His research interests explore the intersection of Informatics and machine learning. He seeks to advance machine learning algorithms through novel methods using a multi-disciplinary approach, with an emphasis on the role of Informatics in optimizations and representations.

His previous experience in industry and government focused on multi-modal data fusion. He implemented agent-based systems and evolutionary algorithms at IBM before working on NLP applications. He also implemented high-performance architectures which resulted in distributed systems for the algorithms he developed. Chris also managed and led a high-risk, high payoff research program at IARPA, which investigated novel methods for data representation and optimizations.

In his spare time, Chris likes to scan arxiv for relevant research. He also enjoys facilitating machine learning hackathons or whiteboarding sessions with colleagues. Beyond academics, Chris enjoys learning the piano, and catching up on pharmacology topics.