Experienced in leading multiple Data Science teams to deliver industry applications for Machine Learning, Predictive Analytics, and Data Architecture solutions, creating data products for Text Comprehension, Image Recognition, Recommender Systems, Targeted Advertising, Forecasting, User Understanding and more. Over a decade in Data Science and Education experience, applying and training others to apply SVMs, neural networks/deep learning algorithms, clustering, PCA/SVD, generalized regression models, Bayesian networks, collaborative filtering, feature selection/regularization, boosting methodologies, numerical and Monte Carlo approximation, data visualization, analytic approximation theory, enumerative and graphical combinatorics, and advanced implementations of operator algebras, probability theory, and statistics.

Chief Science Officer, EVP Galvanize Learning and Instruction @ From 2014 to Present (1 year) San FranciscoLead Data Science Instructor for DAT_7 summer weekend course in San Francisco @ From 2014 to 2014 (less than a year) San Francisco Bay AreaChief Data Scientist @ Leading the Data Science and Machine Learning Operations teams, delivering key inference models for the PersonaGraph user understanding platform. From 2013 to 2014 (1 year) Director of Data Science, Principal Data Scientist @ As a wholly owned subsidiary of Sears Holding, responsibilities at MetaScale included providing Data Science Consulting services to external facing clients. From July 2012 to October 2013 (1 year 4 months) Director of Data Sciences - Data Sciences Lab @ From July 2012 to October 2013 (1 year 4 months) San JoseFaculty Instructor @ Taught a wide variety of courses with topics including: • Principals of Artificial Intelligence • Rational Choice Modeling: expected utility and dominance reasoning strategies • Game Theory: zero-sum and non-conservative systems • Temporal Mechanics: classical and quantum CTC computation models • Causal and Inductive Reasoning - for Stochastic and binary processes • Symbolic Logic, including semantic completeness and modality operators From 2009 to 2012 (3 years) Mathematics Teaching Fellow @ Instructed or Assisted with the Instruction of • Multi-variable and Advanced Calculus (all levels), • Complex Variables, • Linear Algebra, • Combinatorics, • Differential Equations. From 2000 to 2003 (3 years)

Bachelor of Arts (BA), Philosophy: Mathematical Logic and Phil. of Physics @ Columbia University in the City of New York From 1999 to 2003 Bachelor's degree, Mathematics @ Columbia University in the City of New York From 1999 to 2003 Master of Science (MS), Theoretical and Mathematical Physics: Relativity Theory and Quantum Field Theory @ University of PittsburghMaster of Arts (M.A.), Mathematics: Operator Algebras, Differential Geometry and Statistics @ University of PittsburghDoctor of Philosophy (Ph.D.), Phil. Science: Modeling applications in General Relativity and Quantum Statistical Mech. @ University of Pittsburgh Mike PhD is skilled in: Data Science, Machine Learning, Predictive Modeling, Data Visualization, Python, Statistical Modeling, Artificial Intelligence, Statistics, Mathematical Modeling, R, Data Analysis, Data Mining, Analytics, Hadoop, Algorithms