Chris Schilling Email and Phone Number

Currently, I am developing technology for mining the unstructured web. Specifically, I build scalable solutions for discovering location based information which is then used to provide personalized, mobile recommendations. Techniques involved include machine based classification and clustering, collaborative filtering, and natural language processing using domain specific taxonomies.I was a founding member of Clever Sense, Inc (Sr. Data Mining Engineer) acquired by Google in 2011 where I developed algorithms and technology used for making personalized restaurant recommendations (via our mobile app Alfred). I am continuing in my role and working on leveraging Google's massive infrastructure and dataset for use in personalization systems. As a PhD physicist, I own a multi-faceted skill set. Besides having a deep understanding of the mathematics and theory behind the complex systems I studied, I am a data analyst and developer at heart. As a graduate student and postdoc at SLAC, I was developing scientific software for complex high-energy physics data analysis. These analyses involved extracting extremely rare (1 in 10e7) signal events from a highly multi-dimensional data sample containing billions of events. The techniques include implementing modern pattern recognition and machine learning techniques (neural networks, boosted/bagged decision trees, random forests), maximum likelihood estimation, and Monte Carlo simulations for testing and validating results. My work and leadership roles at SLAC led to four major publications and three PhDs including my own. I am an expert in programming C++ with object oriented design patterns in mind. Currently, I am developing mainly in Java and C++ with some general scripting thrown about.I am particularly interested in development of effective data mining systems and implementing feature extraction and personalization algorithms at massive scale.Specialties: Machine learning, feature extraction from unstructured data, recommendation engines, complex data analysis, pattern mining.