I am developing Machine Learning algorithms for prediction, classification and pattern recognition for motion, speech, video, text and unstructured data based on Deep Learning and Neural Networks (DNN, CNN, RNN, other NN). Specialties: Expert in probabilistic and statistical algorithms, machine learning and computational methods for data compression, image analysis, classification and recognition: (Bayesian Classifiers, Decision Trees, Support Vector Machines, Hidden Markov Models, Neural Networks, Monte Carlo Methods, Hadoop, Map-Reduce, Numerical Methods). Fluent with C/C++, Java, Python, Shell Scripting, Octave/Matlab.

Principal Speech Processing ASR Engineer @ Developing Artificial Intelligence in Any Sense by Farming and Schooling Neural Nets. From April 2015 to Present (5 months) San Jose, CALead Algorithm Engineer @ Sensing and Understanding Everything With Deep Neural And Bayesian Nets. From July 2014 to April 2015 (10 months) Algorithm Engineer @ Using Machine Learning To Make Smartphones Smarter: Motion Classification And Understanding With Deep Convolutional Neural Nets. From December 2013 to July 2014 (8 months) Sr. Research Scientist @ Developing and Implementing Machine Learning Algorithms for Big Analytics, Big Recommendations and Big Predictions for Big Data and Social Networks. Proposed, developed and implemented Markov Models for Social Networks: predicting behavior from interactions on Social Graphs. From March 2011 to December 2013 (2 years 10 months) Principal Imaging Engineer @ From November 2009 to March 2011 (1 year 5 months) Compression Researcher @ From 2007 to 2009 (2 years) Lead Software Engineer @ From 2000 to 2007 (7 years) Senior System Architect @ From 1999 to 2000 (1 year) Staff Scientist @ From 1997 to 1999 (2 years) Computer Scientist @ From 1996 to 1997 (1 year) Software Engineer @ From 1995 to 1996 (1 year) Senior Research Scientist @ From 1989 to 1995 (6 years)

No degree, Neural Networks for Machine Learning, by Prof. GEOFFREY E. HINTON @ University of Toronto From 2012 to 2012 Online course, no degree, Introduction to Artificial Intellligence @ Stanford University From 2011 to 2011 Online course, no degree, Machine Learning @ Stanford University From 2011 to 2011 PhD, Theoretical & Mathematical Physics, Nizhniy Novgorod State University, Russia @ Нижегородский Государственный Университет им. Н.И. Лобачевского (ННГУ) From 1990 to 1992 Michael Tetelman is skilled in: C/C++ STL, Java, Python, Hadoop, Neural Networks, Shell Scripting, Hidden Markov Models, Monte Carlo Simulation, SVM, Image Analysis, Algorithms, Machine Learning, Computer Vision, Numerical Analysis, C++, Image Processing, C, Linux, Distributed Systems, Matlab, Data Mining, Unix, Statistics, Natural Language..., Mathematics, Data Analysis, Software Engineering, Artificial Intelligence, Pattern Recognition, Information Retrieval, R&D, Compression, High Performance..., Mathematical Modeling, Video Processing, Text Mining, MapReduce, Simulation, OOP, Object Oriented Design, Scientific Computing, Physics, Digital Image Processing, Bash, Scalability, Image Segmentation, Statistical Modeling, Machine Vision, Recommender Systems, Cloud Computing