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Salif Kanté

Tomsk, Russia

Salif Kanté

Research Engineer — Applied AI & Electromagnetic Compatibility

Engineer in the Department of Television and Control at TUSUR University, working between applied machine learning and computational electromagnetics — and building the web platforms that make those methods usable.

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About

Background

Portrait of Salif Kanté

I was born and raised in Bamako, Mali. From 2017 to 2022 I studied in Tunisia, completing an undergraduate degree in computer science followed by a master’s degree in data science and engineering.

I began with C and Java before moving into web and AI technologies. During my studies I completed several professional internships and contributed to production projects in Tunisia; between 2022 and 2023 I taught programming to students at private universities in Mali.

In late 2023 I moved to Tomsk, Russia. I now work as an engineer in the Department of Television and Control at TUSUR University, in the Fundamental Research on Electromagnetic Compatibility laboratory, alongside doctoral work in artificial intelligence and machine learning.

My work sits between applied machine learning and computational electromagnetics: deep-learning tools for antenna current prediction, hybrid semi-analytical methods for enclosure shielding, and distributed platforms for electromagnetic modelling and simulation.

Position

Affiliation

Position
Engineer — Department of Television and Control
University
Tomsk State University of Control Systems and Radioelectronics (TUSUR)
Research laboratory
Fundamental Research on Electromagnetic Compatibility
Doctoral work
Artificial intelligence and machine learning
Based in
Tomsk, Russia

Research

Publications & conferences

Papers presented at Russian and international scientific meetings.

  1. Tomsk, Russia

    Hybrid semi-analytical method for evaluating the shielding effectiveness of enclosures, based on the equivalent-circuit method and modified nodal analysis

    Scientific Session of TUSUR

    Original title: Гибридный полуаналитический метод оценки эффективности экранирования корпусов на основе метода эквивалентных схем и модифицированного метода узловых потенциалов

  2. Saint Petersburg, Russia

    Hybrid semi-analytical method for analyzing the effectiveness of enclosure shielding, combining equivalent circuits and modified nodal analysis

    XIV Congress of Young Scientists, ITMO University

  3. Tomsk, Russia

    Distributed web-based platform for EM modeling and simulation

    Scientific Session of TUSUR

  4. Saint Petersburg, Russia

    A deep learning-based tool for dipole antenna current prediction and visualization

    XIV Congress of Young Scientists, ITMO University

Co-authored preprint

Ninth author, through the IA Mali research community.

Read on arXiv(arXiv:2506.02443)

Work

Selected projects

Applications and interfaces built during studies, internships and teaching.

Web interfaces & sites

HTML · CSS · Bootstrap · JavaScript · jQuery · React

Django applications

Python · Django

MERN applications

MongoDB · Express · React · Node.js

Laravel applications

PHP · Laravel

Machine learning & model deployment

Python · Machine learning · Flask · Streamlit

Skills

Technical practice

Technologies used in research, teaching and delivered projects.

Programming languages

  • Python
  • JavaScript
  • PHP
  • Java
  • C
  • C++
  • SQL
  • HTML
  • CSS

Machine learning

  • TensorFlow
  • Deep learning
  • Machine learning with Python
  • Spark MLlib

Big data

  • Hadoop
  • Hive
  • Apache Spark
  • Beeline
  • Cloud storage clusters

Web development

  • React
  • Next.js
  • Node.js
  • Express
  • MongoDB
  • Django
  • Laravel
  • Flask
  • Streamlit
  • Bootstrap
  • jQuery

Cloud & tooling

  • AWS
  • Git
  • Vercel

Research methods

  • Electromagnetic compatibility
  • Equivalent-circuit method
  • Modified nodal analysis
  • Enclosure shielding analysis
  • Antenna current prediction

Credentials

Certifications, communities & languages

Certifications

CDOSS

  • Big Data Analytics with Hive Query Language and Beeline
  • Managing Big Data in a Hadoop Cluster
  • Hadoop Cluster Installation and Administration
  • Machine Learning with Spark
  • Machine Learning with Python
  • Deep Learning with Python

Coursera

  • Introduction to TensorFlow for Artificial Intelligence, Machine Learning, and Deep Learning
  • Analyzing Big Data with SQL
  • Managing Big Data in Clusters and Cloud Storage
  • AWS Cloud Technical Essentials

Communities

  • Doniyaso

    African knowledge-sharing and technology community.

    Member since 2023

  • IA Mali

    Artificial intelligence research community in Mali.

    Member since 2025

Languages

  • BambaraNative language
  • FrenchWorking language
  • EnglishB2 — IELTS 6.0 — 2022
  • RussianB1+ — TUSUR

Contact

Get in touch

Open to research collaboration and to contributing to serious technology projects.