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Sergey Lukyanchikov
  • Male
  • Paris
  • France
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Sergey Lukyanchikov's Page

Profile Information

Short Bio:
End-to-end implementation of in-platform and edge real-time AI offering: from product design until going to market. Contributed to creation of data science practices at leading data platform vendors. Actively involved in achieving market acceptance of their technologies.
Company:
InterSystems
Job Title:
Data Science Offering Engineer
Seniority:
Consultant
Job Function:
Data Scientist
Country
France
Number of employees:
1.000 to 4.999
Industry:
Research and Consulting
LinkedIn Profile:
http://www.linkedin.com/in/lukyanchikov
Interests:
Contributing, Networking
Topics of Interest
Data Science, Data Journalism, Mathematics

Sergey Lukyanchikov's Blog

SAP BW Data Mining Analytics: Model Reporting (Part 1)

Posted on September 15, 2021 at 4:00am 0 Comments

SAP BW Data Mining allows creating data mining models that implement respective analysis methods (either supplied by SAP as built-in with SAP BW Data Mining or supplied by certified vendors). Although analysis methods available via SAP BW Data Mining provide extensive reporting and visualizations, there could be a need for…

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AI Robotization with InterSystems IRIS Data Platform

Posted on July 16, 2021 at 4:00am 0 Comments

Fixing the terminology

A robot is not expected to be either huge or humanoid, or even material (in disagreement with Wikipedia, although the…

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Distributed Artificial Intelligence with InterSystems IRIS

Posted on April 3, 2021 at 3:00am 0 Comments

What is Distributed Artificial Intelligence (DAI)?

Attempts to find a “bullet-proof” definition have not produced result: it seems like the term is slightly “ahead of time”. Still, we can analyze semantically the term itself – deriving that distributed artificial intelligence is the same AI (see…

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Horowitz Index Day-Ahead Change Prediction in Real Time

Posted on December 14, 2020 at 3:00am 0 Comments

Rationalizing the effort of our intensive care staff by predicting patient condition indicators in real time is a challenge because of an impressive number of externally imposed and internally unavoidable restrictions. Patient data privacy requirements, variety of types and lack of standardization within one type of equipment, limited availability of “pure” examples of this or that patient condition patterns – just to name a few complexity factors.

Computational approaches to model…

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