Publication
Machine Learning Video Analysis: Identifying Fish
https://www.toptal.com/developers/machine-learning/machine-learning-video-analysis
Michael is currently unavailable
Michael Karchevsky
Verified Expert in Engineering
Image Processing Developer
Batumi, Adjara, Georgia
Toptal member since September 12, 2016
Bio
Michael has a strong background in machine learning and AI, with diverse research experience in industry and academia. He has successfully led development cycles and has expertise in working with various data types. Michael has strong leadership, teamwork, quick learning skills, and a results-oriented approach. He excels under pressure and can meet challenging deadlines, and these qualifications make him a valuable candidate for positions in ML and AI.
Portfolio
DemandBase
PyTorch, Generative Pre-trained Transformers (GPT)...
Zarplata.ru
PyTorch, Python, Generative Pre-trained Transformers (GPT)...
Aurteen, Inc.
Image Processing, Python, PyTorch, TensorFlow, Deep Learning, Computer Vision...
Experience
- Image Processing - 11 years
- Computer Vision - 9 years
- Generative Pre-trained Transformers (GPT) - 6 years
- Deep Learning - 6 years
- Python - 6 years
- Natural Language Processing (NLP) - 6 years
- Machine Learning - 5 years
- Amazon Web Services (AWS) - 4 years
Preferred Environment
PyTorch, Machine Learning, Data Science, Artificial Intelligence (AI), Python, Deep Learning, Generative Pre-trained Transformers (GPT), Natural Language Processing (NLP), Computer Vision
The most amazing...
...was the development of a text embedding system for a job board. This system yielded significant benefits in terms of recommender and search engine performance.
Work Experience
Senior Machine Learning Engineer
2021 - 2022
DemandBase
- Managed a full-stack machine learning development cycle from research to deployment.
- Performed data extraction from text sequences by extracting specific pieces of information or data from a larger body of text.
- Developed deep learning models using machine learning techniques to train artificial neural networks to perform tasks.
- Maintained the API in production, which involved ensuring that APIs function properly and efficiently in a live environment.
Technologies: PyTorch, Generative Pre-trained Transformers (GPT), Natural Language Processing (NLP), Deep Learning, Python, Machine Learning, Data Science, Named-entity Recognition (NER), Amazon Elastic MapReduce (EMR), Amazon S3 (AWS S3), Amazon EC2
Data Science Team Lead
2019 - 2021
Zarplata.ru
- Directed a team of four data science and two data engineer professionals.
- Led research and problem formalization (recommendation and search system, NLP, Churn, CV).
- Oversaw the development of machine learning models.
- Coordinated the deployment and maintenance of APIs in production.
Technologies: PyTorch, Python, Natural Language Processing (NLP), Generative Pre-trained Transformers (GPT), Recommendation Systems, Named-entity Recognition (NER), Computer Vision, Agile, Deep Learning, Management, Big Data, Machine Learning, LightGBM, Lighting, Artificial Intelligence (AI), Analytics, IT Deployments
Senior Data Scientist (Deep Learning)
2018 - 2018
Aurteen, Inc.
- Supervised the research and the design of deep learning models.
- Produced medical image segmentation and classification.
- Developed complex production pipelines, from training to deployment.
- Researched and implemented state-of-the-art data science techniques.
Technologies: Image Processing, Python, PyTorch, TensorFlow, Deep Learning, Computer Vision, IT Deployments, Medical Imaging
Data Scientist
2017 - 2018
SeatCrawler
- Researched and developed new machine learning algorithms.
- Implemented data crawlers and ETL.
- Developed and improved data science pipelines.
- Established a fault-tolerant multiprocessing workflow.
- Maintained a Python web service (front-end + back-end), improved API integration, and developed new features.
- Developed prediction of ticket prices and ticket sales.
Technologies: Bottle.py, Luigi, StatsModels, Scikit-learn, SQL, Pandas, Python
Big Data Analyst
2016 - 2017
P2 Energy Solutions
- Automated a database migration pipeline from RDS to Redshift.
- Built a new data warehouse to serve analytic operations.
- Designed and implemented SQL scripts for data analysis.
- Maintained and modified Spotfire data visualization pages.
Technologies: Amazon Web Services (AWS), Python, Spotfire, TIBCO, PostgreSQL, Redshift, Amazon EC2, Relational Database Services (RDS), Amazon S3 (AWS S3)
Software Developer
2013 - 2017
StreamData
- Implemented a detection system and tracking of people on video, to help determine statistics in the supermarket.
- Created software for automatic data processing and visualization of results.
- Created an algorithm for a data science predictive model.
- Developed image analysis algorithms for medical equipment.
- Created neural network architecture and an API for styling images.
Technologies: PyTorch, Natural Language Toolkit (NLTK), Python, OpenCV, TensorFlow, Keras
Teacher of IT and Computer Science
2014 - 2016
Novosibirsk State University
- Created an education methodology. Created lectures for fast understanding of key aspects. Structured programming knowledge.
- Approved communication and presentation skills. Learned to transfer thoughts and ideas to students.
- Got two students for scientific advisory as a result of acceptance of good training methodologies.
- Trained students to be the best at programming, as measured by the results of the final exams.
Technologies: Image Processing, Python, OpenCV, Git, Object-oriented Programming (OOP), C++
Junior Researcher
2014 - 2015
Baker Hughes
- Gained experience in fluid dynamics of wells and Monte Carlo methods.
- Created optimization methods for solving the inverse problem (based on the Monte Carlo algorithms).
- Implemented detailed statistical analysis of experimental data of drill bits.
- Created an electromagnetic device model to predict sensor values.
- Implemented 30+ data processing scripts (with full visualization).
Technologies: Mathematica, Wolfram, Python, OpenCV, C++
Laboratory Research Assistant
2009 - 2014
Novosibirsk State University, Institute of Thermophysics
- Developed and modified algorithms for particle image velocimetry (PIV) and particle tracking velocimetry (PTV).
- Implemented deep mathematical image processing algorithms.
- Gained experience in analyzing algorithm documentation and using it as instructions for implementation.
- Participated in many conferences, authoring or co-authoring thirteen scientific papers.
- Created utilities and plugins for data processing.
Technologies: Tecplot, Linux, D3.js, OpenCV, Python, C++
Intern
2013 - 2013
Schlumberger
- Modeled hydraulic fracturing.
- Developed numerical data analysis algorithms.
- Gained experience in computer simulations of physical processes, mathematical modeling, and numerical analysis.
- Implemented visualization and preparation of technical presentations.
Technologies: D3.js, Petrel, Python, C++
Experience
4th PIV Challenge
I participated in the international scientific competition in data processing for the PIV and PTV algorithms. In the course of this work, I have created, implemented, or improved about 20 algorithms. Technologies used for development were C, C++, Python, OpenCV, OpenMP, machine learning, and MATLAB.
Home Credit Default Risk
https://www.kaggle.com/c/home-credit-default-risk554th (top 8% out of 7198) - Home Credit Default Risk Kaggle challenge.
TGS Salt Identification Challenge
https://www.kaggle.com/c/tgs-salt-identification-challengeI am proud to have achieved 27th place, ranking in the top 1% out of 3,234 participants, in a Kaggle competition focused on image and data processing. This competition was particularly challenging as it aimed to improve the accuracy of seismic imaging and 3D renderings by identifying salt deposits beneath the Earth's surface. The competition was hosted by TGS, a leading geoscience data company, who sought to leverage the power of machine learning to automate the identification of subsurface targets, ultimately creating more accurate and safer drilling practices for oil and gas companies.
PLAsTiCC Astronomical Classification
https://www.kaggle.com/c/PLAsTiCC-201852nd place (top 5% out of 1094) in a time series and data processing competition.
Russian Engineering Competition
I won the Russian Engineering Competition, 2015. Technologies used for development were C, C++, Python, OpenCV, and machine learning.
N+1 Fish, N+2 Fish Data Science Competition
https://www.drivendata.org/competitions/48/identify-fish-challenge/11th place in Video Processing N+1 Fish, N+2 Fish competition (source data - videos).
Planet: Understanding the Amazon from Space Data Science Competition
https://www.kaggle.com/c/planet-understanding-the-amazon-from-space222nd place (top 24%) - Planet: Understanding the Amazon from Space competition (source data - images)
Toxic Comment Classification Challenge
https://www.kaggle.com/c/jigsaw-toxic-comment-classification-challenge406th place (top 9% out of 4551) in a text processing competition.
Avito Demand Prediction Challenge
https://www.kaggle.com/c/avito-demand-prediction131st place (top 7% out of 1917) in a text, image, and data processing competition.
2018 Data Science Bowl
https://www.kaggle.com/c/data-science-bowl-2018130th place (top 4% out of 3634) in automated nucleus detection.
Education
2015 - 2017
Masters's Degree in Data Analysis
Yandex School of Data Analysis - Moscow
2014 - 2016
Postgraduate Degree in Physical and Technical Information Technology
Novosibirsk State University - Novosibirsk
2012 - 2014
Master's Degree in Automation of Physical and Technical Research
Novosibirsk State University - Novosibirsk
2008 - 2012
Bachelor of Science Degree in Automation of Physical and Technical Research
Novosibirsk State University - Novosibirsk
Skills
Libraries/APIs
Pandas, NumPy, SciPy, Keras, Matplotlib, Natural Language Toolkit (NLTK), OpenCV, Scikit-learn, SpaCy, PyTorch, NetworkX, SQLAlchemy, TensorFlow, Python Imaging Library, D3.js, Luigi, Bottle.py, Beautiful Soup, Java Digital Image Processing (DIP), Standard Template Library (STL), OpenMP
Tools
Seaborn, Gensim, Scikit-image, Git, Plotly, Mathematica, StatsModels, Jupyter, IPython, PyCharm, Tecplot, Amazon Simple Email Service (SES), Google Analytics, IPython Notebook, Spotfire, Apache, SQLiteManager, Named-entity Recognition (NER), Amazon Elastic MapReduce (EMR), ImageJ
Languages
Python, Multiscale Modeling Language (MML), SQL, Wolfram, Java, UML, C++
Paradigms
Functional Programming, REST, Distributed Computing, Object-oriented Programming (OOP), Parallel Computing, Concurrent Programming, Data-driven Programming, Model-driven Engineering (MDE), Agile, Management
Platforms
Jupyter Notebook, Amazon Web Services (AWS), Linux, Amazon, Amazon EC2, Petrel
Frameworks
Scrapy, Flask, LightGBM
Storage
PostgreSQL, Redshift, MySQL, JSON, SQLite, NoSQL, Amazon S3 (AWS S3)
Other
Data Science, Computer Vision Algorithms, Pipelines, Data Processing, Neural Networks, Deep Learning, Algorithms, Analytics, Image Processing, Data Analysis, Computer Vision, Mathematics, Machine Learning, Scientific Computing, Artificial Intelligence (AI), Predictive Modeling, Time Series, Text Classification, Text Categorization, Sequence Classification, Extractive Question Answering (EQA), Text Generation, Leadership, Bokeh, Tesseract, Physics Simulations, Statistics, Data Structures, Numerical Methods, Network Programming, JetBrains IDE, Relational Database Services (RDS), TIBCO, Natural Language Processing (NLP), Recommendation Systems, Search, 3D Image Processing, Patterns, Time Series Analysis, Programming, Physics, Big Data, Lighting, IT Deployments, Medical Imaging, Images, Generative Pre-trained Transformers (GPT)
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