I’m proficient in such machine learning and deep learning areas as computer vision, natural language processing, predictive analytics. Also I have more than seven years of experience in science and strong background as a researcher. I have 19 publications in well-known magazines. My main programming language is Python (with additional libraries such as numpy, scipy, matplotlib, pandas, scikit-learn), also I’m using Keras and PyTorch for deep learning. Due to mathematical education, I have background in pure mathematics and statistics.

My Interests:

AI in cyber security, AI in healthcare, computer vision, MLOps, start-ups

Top Publications:

Here represented some of my scientific papers:

• Radiation of high-power ultrawideband pulses with elliptical polarization by fourelement array of cylindrical helical antennas, 2018, Laser and Particle Beams
  
• Numerical Modeling of Ultra Wideband Combined Antennas, 2017, Russian Physics Journal
  
• A source of high-power pulses of elliptically polarized ultrawideband radiation, 2014, Review of Scientific Instruments
  

Other papers accessible via Google Scholar profile

Also I have a Medium Blog, where I’m writing about different machine learning applications

Certifications

• Data Engineering with Google Cloud

  Coursera, Google, 2020
  This specialization contains 6 courses and helps you to get familiar with GCP services for data engineering and machine learning. This specialization include following courses: Google Cloud Big Data and Machine Learning Fundamentals, Modernizing Data Lakes and Data Warehouses with GCP, Building Batch Data Pipelines on GCP, Building Resilient Streaming Analytics Systems on GCP, Smart Analytics, Machine Learning, and AI on GCP, Preparing for the Google Cloud Professional Data Engineer Exam.

• Specialization IBM AI Engineering

  Coursera, IBM, 2020
  This specialization contains 6 courses such as: Machine Learning with Python, Scalable Machine Learning on Big Data using Apache Spark, Introduction to Deep Learning & Neural Networks with Keras, Deep Neural Networks with PyTorch, Building Deep Learning Models with TensorFlow, AI Capstone Project with Deep Learning.

• Neural Networks and Computer Vision

  stepik.org, Samsung RnD Center, 2019
  It was amazing course which I can advice to you. This course contains a bunch of intresting and challenging mathematical problems and practical assighnments on convolutional neural networks with Pytorch. With final assighment which is hosted on Kaggle.

• Java

  stepik.org, Computer Science Center, 2018
  Good course on Java basics by Computer Science Center.

• Hadoop. System for big data processing

  stepik.org, Mail.ru Group, 2018
  Course which is focused on Hadoop ecosystem, MapReduce concept, NoSQL DataBases and Spark.

• Introduction to Machine Learning

  Coursera, HSE&Yandex, 2018
  This course is performed by Higher School of Economics and Yandex School of Data Analysis. People who want to take this course must have a strong mathematical background.

• Machine leaning

  Coursera, Stanford University, 2017
  This course is must have for every beginner machine learner engineer, which includes all standard machine learning methods, feed forward networks, recomendation systems, anomality detection.