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Dr. Kirill Krinkin

Adjunct Professor of Computer Science (Software, Data and Technology)
School of Computer Science & Engineering
Email Address
kkrinkin@constructor.university
Research Interests

Intelligence Engineering

Creating embodied intelligence systems is a new era of engineering. Engineering's history is a chronicle of human innovation, starting from ancient civilizations till the latest areas like aerospace, electronics, digital technologies, robotics. At its core, engineering is the art of problem-solving through scientific and mathematical principles. It is inherently interdisciplinary, blending knowledge from various sciences to make life on the Planet better and safe.

After humanity discovered and learnt how to reliably engineer physical machines and software systems we face a challenge related to intelligent systems: we need to learn how to engineer the intelligence.

One possible way to think about it is Co-Evolutionary Hybrid Intelligence (CHI) paradigm. It represents a transformative approach to the collaboration between human and artificial intelligence. I focus on thinking about human-machine cognitive co-evolution. More can be found at Co-evolution.ai.
 

Next generation of operating systems and virtualization technologies

Current desing of operating systems mostly originated from very old impementations of the first systems like Unix. Nevertheless, the ideas developed by Von-Neumann and Turing are still valid, but unfortunately, still not implemented in modern systems. The main challenge in this area is to implement perceptions-feedback loop as we have in living systems. If you think that this idea is new you need to study the fundamental Von-Neumann report where he described this. Modern hardware is capable of implementing this idea, and I am working on it.
 

Next Generation Education Methods

The world where Large Language Models (LLM) are capable of generating text which can be used as a convenient tool for navigating in the information (I would say data) space is a coming reality. This means that the memorising became less important than ability to think critically and ability to practically apply the knowledge. Being a university teacher I am working on changing education model and transform it to the new reality. I believe, that mastering in creativity supported by immediate world's knowledge body access is a key ingredient of the future education.
 

Autonomous systems

The development of intelligent, fully autonomous embodied systems (mobile robots) is an extremely good engineering landmark. It is extremely fruitful for scientific research because it unite knowledge from different areas. From one side it is quite challenging, but the nice thing -- you always have the simple quality criteria for your solution: it simple does work or doesn't (This so simple to test!). The collateral beauty of the research of the autonomy is in self-organizing and self defining educational track (They call it STEM -- Science, technology, engineering, math). Studying STEM you always can apply your knowledge now and here.
 

My research in autonomy is mostly related to the following areas. Computer vision data processing (RGB and RGBD cameras, lidars, radars); SLAM algorithms; Building machine learning models for spatial partitioning tasks; building robust development processes for comprehensive systems like Smart-Cities.

Selected Publications

XAI evaluation: evaluating black-box model explanations for prediction

Y Zhang, F Xu, J Zou, OL Petrosian, KV Krinkin

2021 II International Conference on Neural Networks and Neurotechnologies …

2d slam quality evaluation methods

A Filatov, A Filatov, K Krinkin, B Chen, D Molodan

2017 21st Conference of Open Innovations Association (FRUCT), 120-126

Evaluation of the modern visual SLAM methods

A Huletski, D Kartashov, K Krinkin

2015 Artificial Intelligence and Natural Language and Information Extraction …

Comparison and explanation of forecasting algorithms for energy time series

Y Zhang, R Ma, J Liu, X Liu, O Petrosian, K Krinkin

Mathematics 9 (21), 2794

High-dimensional explainable AI for cancer detection

J Zou, F Xu, Y Zhang, O Petrosian, K Krinkin

International Journal of Artificial Intelligence 19 (2), 195

FI-SHAP: explanation of time series forecasting and improvement of feature engineering based on boosting algorithm

Y Zhang, O Petrosian, J Liu, R Ma, K Krinkin

Proceedings of SAI Intelligent Systems Conference, 745-758

Prediction of Next App in OS

R Ma, Y Zhang, J Liu, O Petrosian, K Krinkin

2022 III International Conference on Neural Networks and Neurotechnologies …

Integration of Smart-M3 applications: Blogging in smart conference

DG Korzun, IV Galov, AM Kashevnik, NG Shilov, K Krinkin, Y Korolev

Smart Spaces and Next Generation Wired/Wireless Networking: 11th …

Evaluation of modern laser based indoor slam algorithms

K Krinkin, A Filatov, A yom Filatov, A Huletski, D Kartashov

2018 22nd Conference of Open Innovations Association (FRUCT), 101-106

Three dimensional uav positioning for dynamic uav-to-car communications

SA Hadiwardoyo, CT Calafate, JC Cano, K Krinkin, D Klionskiy, ...

Sensors 20 (2), 356

Design and implementation Raspberry Pi-based omni-wheel mobile robot

K Krinkin, E Stotskaya, Y Stotskiy

2015 Artificial Intelligence and Natural Language and Information Extraction …

Chaordic learning: A case study

S Krusche, B Bruegge, I Camilleri, K Krinkin, A Seitz, C Wöbker

2017 IEEE/ACM 39th International Conference on Software Engineering …

Vinyslam: an indoor slam method for low-cost platforms based on the transferable belief model

A Huletski, D Kartashov, K Krinkin

2017 IEEE/RSJ International Conference on Intelligent Robots and Systems …

Data distribution services performance evaluation framework

K Krinkin, A Filatov, A Filatov, O Kurishev, A Lyanguzov

2018 22nd Conference of Open Innovations Association (FRUCT), 94-100

Geo-coding in smart environment: Integration principles of Smart-M3 and Geo2Tag

K Krinkin, K Yudenok

Conference on Internet of Things and Smart Spaces, 107-116

Co-evolutionary hybrid intelligence

K Krinkin, Y Shichkina, A Ignatyev

2021 5th Scientific School Dynamics of Complex Networks and their …

Models of telecommunications network monitoring based on knowledge graphs

K Krinkin, A Vodyaho, I Kulikov, N Zhukova

2020 9th Mediterranean Conference on Embedded Computing (MECO), 1-7

TinySLAM improvements for indoor navigation

A Huletski, D Kartashov, K Krinkin

2016 IEEE International Conference on Multisensor Fusion and Integration for …

Architecture of a telecommunications network monitoring system based on a knowledge graph

K Krinkin, I Kulikov, A Vodyaho, N Zhukova

2020 26th Conference of Open Innovations Association (FRUCT), 231-239

Geo2Tag performance evaluation

M Zaslavskiy, K Krinkin

2012 12th Conference of Open Innovations Association (FRUCT), 1-9

 

University Education

2000 – Engineer on Software, KnASTU

 

2004 – PhD, Software Engineering (05.13.11), SPb ETU

Work Experience

Lecturer at Computer Science Center

Leader at Open Source Linux Laboratory -- OSLL

Member at FRUCT

Vice-Rector for Digital Transformation at Saint Petersburg State Electrotechnical University "LETI"

CEO at Popov's Institute for Artificial Intelligence, Cybersecurity and Communications, SPbETU at Saint Petersburg State Electrotechnical University "LETI"

Head of Department of Software Engineering and Computer Applications at Saint Petersburg State Electrotechnical University "LETI"

Associated Professor, Computer Science Faculty at Saint Petersburg State Electrotechnical University "LETI"

Head of Lab on Mobile Robot Algorithms at JetBrains Research

Associated Professor at Academic University of Russian Academy of Sciences

Visiting Professor at SATTI at Samsung Electronics

Sr. Software Engineer at EMC