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Dimitry Gorinevsky
IEEE Life Fellow
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My interests are in AI for Industrial Applications and Data Intelligence.
I consult to Stanford in Industrial AI area.
As Consulting Professor (2003-2015) and then Adjunct Professor (2015-2025), I advised several PhD thesis and MS students.
A seminar class on Industrial AI was taught in
2025,
2024,
2023,
2021.
Its predecessor, a seminar on Industrial IoT Applications, was taught in
Spring 2019,
2018,
2017, and
2016.
Seminar on
Intelligent Energy Systems was taught in
2015,
2014,
2013,
2012, and
2011.
Past classes include
Fault Diagnostics Systems in Spring 2009
as well as
Control Engineering in Industry in Spring 2005 and in
Winter 2003.
I am currently busy with AI startup,
Mitek Analytics,
in the rapidly growing Data Intelligence area
and not teaching. The AI applications to supply chain and sustainment operations focus on costs that dominate lifecycle in physical asset fleets. High impact of the AI on effectiveness of sustainment of Aerospace & Defense systems has been documented. There are opportunities for Stanford collaboration.
Common theme is Explainable AI for Data Intelligence: supporting mission critical decisions based on limited available data. The problems in Machine Learning (ML) and AI inference involve applied math methods related to Statistics, Optimization, Signal Processing, Decision & Control, and Operations Research. Many applications are in sustainability and sustainment processes. Selected examples are below