Mikhail Gorelkin

1612 Worcester Rd, Apt. 204A, Framingham, MA 01702


I am an AI scientist / architect / developer building AI systems.




AI Scientist & Mathematician / Consultant, Boston, MA 04.2005 - current

Principal AI Architect & Developer / Consultant, Boston, MA 04.2005 - current

Partial Project List:

Compuware Corp., Technology Department, Detroit, MI 03.2000 – 11.2004
Software Developer VII

Developed several advanced features for the QALoad...

Central Transport International, Inc., Sterling Heights, MI 03.1998 – 02.2000
Systems Architect


Resource Technologies, Troy, MI 08.1997 – 03.1998
Software Consultant

Developed the scalable architecture for terminal operations based on MTS and MS SQL Server with up to 300 MS-DOS clients / hand-held computers using MS RPC. After several months of work, the client hired me as a Systems Architect to lead the technical reconstruction of his IT.

Advanced System & Designs, Inc., Troy, MI 01.1996 – 05.1997
Software Engineer

Designed and developed the DoES for Windows - the primary product for the Shainin approach to Design of Experiment, and the ANOVA-TM 2.x for Windows - the primary product for the Taguchi approach to DoE.

DataNet Technologies, Inc., Troy, MI 02.1993 – 06.1994
Software Engineer

Developed all statistics for the WinSPC including non-normal capability analysis for all types of Pearson's and Johnson's distributions.


Voronezh State University, the Department of Algebra and Topological Analysis Methods, Voronezh, Russia
Master of Science, Mathematics

Specialization: non-linear functional analysis. The master's thesis: diffeomorphisms in Banach spaces.


Model Thinking, Coursera / University of Michigan - Ann Arbor, 2012
Introduction to Complexity, Santa Fe Institute, 2013
Introduction to Dynamical Systems and Chaos, Santa Fe Institute, 2014
Algorithmic Information Dynamics, Santa Fe Institute, 2018
Decision Making in a Complex & Uncertain World, FutureLearn / University of Groningen, 2014
Game Theory, Coursera / Stanford University, 2013
Big Data and Social Physics, edX / MIT, 2014
Data Mining with Weka. Parts 1 & 2, University of Waikato, 2014
Mining Massive Datasets, Coursera / Stanford University, 2014
Machine Learning, Coursera / Stanford University, 2012
Statistical Learning, Stanford University, 2014
Natural Language Processing, Coursera / Columbia University, 2013
Text Mining and Analytics, Coursera / University of Illinois at Urbana-Champaign, 2015
Algorithms: Design and Analysis. Parts 1 & 2, Coursera / Stanford University, 2013
Parallel Programming, Coursera / École Polytechnique Fédérale de Lausanne, 2017


Web Intelligence and Big Data, Coursera / Indian Institute of Technology - Delhi, 2012
Machine Learning: Reinforcement Learning, Udacity / Georgia Tech, 2014
Scalable Machine Learning (Spark / PySpark), edX / UC - Berkeley, 2015
Neural Networks for Machine Learning, Coursera / University of Toronto, 2015
Deep Learning for Natural Language Processing, Stanford University, 2015
Deep Natural Language Processing, University of Oxford & Google DeepMind, 2017
Deep Learning (TensorFlow), Udacity / Google, 2016
Probabilistic Graphical Models, Coursera / Stanford University, 2016
Bayesian Methods for Machine Learning, Coursera / National Research University Higher School of Economics, 2019
Artificial Intelligence. Part 1, edX / UC - Berkeley, 2014
Knowledge-Based AI: Cognitive Systems, Udacity / Georgia Tech, 2016
Approximation Algorithms. Parts 1 & 2, Coursera / École Normale Supérieure, 2016
Functional Programming Principles in Scala, Coursera / École Polytechnique Fédérale de Lausanne, 2015
Superhuman OS, Integral Institute, 2018


IEEE International Conference on Self-Adaptive and Self-Organizing Systems (SASO'07)
O'Reilly Artificial Intelligence Conference, 2016-2018
The International Conference on Probabilistic Programming, 2018


Cognitive Computing Consortium