Viacheslav Zhenylenko, Developer in San Francisco, CA, United States
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Viacheslav Zhenylenko

Verified Expert  in Engineering

Machine Learning Developer

Location
San Francisco, CA, United States
Toptal Member Since
June 13, 2019

Viacheslav has eight years of experience in data science and software engineering, focusing on Python, with production experience in Java and C++. He is passionate about the insights gained from raw data and enjoys converting them to create exceptional business value. Viacheslav is well-versed in applying advanced ML techniques, such as computer vision, NLP, product recommendation systems, networking data, and classical data science to solve data-heavy projects.

Software DevelopmentProgrammingPredictive AnalyticsMachine LearningData AnalysisArtificial Intelligence (AI)Data VisualizationAnalyticsSoftware EngineeringLinear RegressionStatisticsAlgorithmsComputer ScienceComputer VisionData AnalyticsSentiment AnalysisCNNFreelancePythonDataOps

Portfolio

Creating Possibilities Limited
Data Science, Machine Learning, Web Scraping, Natural Language Processing (NLP)...
Classic J. Vans INC.
Python, Data Scraping, Web Scraping, Selenium, Amazon Web Services (AWS)...
Spectation Sports LLC
Python, Data Science, Machine Learning, Data Engineering, R, Statistics...

Experience

Machine Learning - 7 yearsPython - 7 yearsScikit-learn - 7 yearsAmazon Web Services (AWS) - 7 yearsLinux - 7 yearsDeep Learning - 5 yearsTensorFlow - 5 yearsPyTorch - 4 years

Availability

Part-time

Preferred Environment

Eclipse, Visual Studio Code (VS Code), PyCharm, Jupyter, MacOS, Linux, Vim Text Editor, Sublime Text, Bash

The most amazing...

...project I've developed was an industry-first, self-reconfigurable AutoML system for congestion detection in RAN networks.

Work Experience

Data Scientist

2023 - 2023
Creating Possibilities Limited
  • Developed a parallel data collection process for hundreds of websites.
  • Utilized LLMs for summarization, topic extraction, sentiment analysis, report generation, and other tasks.
  • Deployed tool on AWS with Batch, EventBridge, Lambda, and others.
Technologies: Data Science, Machine Learning, Web Scraping, Natural Language Processing (NLP), GPT, Generative Pre-trained Transformers (GPT), Data Engineering, Python, Sentiment Analysis, Data Visualization, Language Models, Large Language Models (LLMs), OpenAI, OpenAI GPT-3 API, OpenAI GPT-4 API, ChatGPT, Selenium

Data Scientist

2023 - 2023
Classic J. Vans INC.
  • Developed tools to automatically gather information from multiple web sources in a structured way.
  • Utilized LLMs for Named Entity Extraction and classification from the raw text.
  • Utilized Selenium with a proxy to emulate web clients.
  • Deployed tool on AWS using EventBridge, ECS, Lambda, S3, QuickSight, SES, and others.
Technologies: Python, Data Scraping, Web Scraping, Selenium, Amazon Web Services (AWS), Language Models, Machine Learning, Deep Learning, Neural Networks, Business Intelligence (BI), Generative Pre-trained Transformers (GPT), GPT, Large Language Models (LLMs), OpenAI, OpenAI GPT-3 API, OpenAI GPT-4 API, ChatGPT

Data Scientist | Engineer

2023 - 2023
Spectation Sports LLC
  • Developed models for MMA pre-fight prediction and in-fight forecasts.
  • Utilized multiple machine learning techniques, such as boosted trees, regression, ensembling, stacking, imputation, and others.
  • Performed multistep feature engineering for individual fighters.
  • Identified, statistically, the most valuable features and best external sources of this data.
  • Deployed and integrated models into existing data pipelines, including elements of MLOps methodologies.
Technologies: Python, Data Science, Machine Learning, Data Engineering, R, Statistics, Scikit-learn, PyTorch, Deep Learning, Amazon Web Services (AWS), Neural Networks

AI Engineer

2022 - 2023
Briefly
  • Utilized OpenAI models for multiple tasks for productivity and customer success domains. Performed fine-tuning, RAG, agents, function calling, and others.
  • Developed distributed cloud infrastructure using Terraform, Amazon Elastic Container Service (Amazon ECS), Amazon DynamoDB, Amazon EventBridge, Amazon Simple Queue Service (SQS), AWS Lambda, and Amazon Simple Email Service (SES).
  • Performed API integrations with external services and tools, including OpenAI, Google services, Slack, Notion, and Hubspot.
  • Designed and built a number of Django APIs with business logic.
Technologies: Django, Web Frameworks, PostgreSQL, SQL, Natural Language Processing (NLP), GPT, Generative Pre-trained Transformers (GPT), OpenAI Gym, React, Jupyter Notebook, ChatGPT, Automation, OpenAI GPT-3 API, OpenAI GPT-4 API, APIs, HubSpot, Notion, HubSpot CRM, OpenAI, Large Language Models (LLMs), REST APIs, Language Models, Machine Learning, Deep Learning, Python, Amazon Web Services (AWS), Neural Networks, LangChain

Senior Data Engineer

2022 - 2022
Grata Inc.
  • Developed end-to-end distributed NLP-based geocoding pipeline using Celery on Kubernetes.
  • Implemented scraping from company websites and aggregators.
  • Developed and deployed on the AWS SageMaker web page category classification model.
  • Implemented a hybrid geocoding model with query lookup, query relaxation, result validation, prioritization, and fallback mechanisms.
  • Used combinations of available geo databases and offline entity extractors like libpostal and third-party geocoding services to combine it in a single view.
  • Increased a fraction of parsed addresses, reduced incorrect addresses by 95%, and improved the overall data quality score by 20%.
Technologies: Python, Docker, Elasticsearch, Celery, Kubernetes, Jenkins, PostgreSQL, REST, Geocoding, Grafana, DataOps, Datadog, Pandas, NumPy, Natural Language Toolkit (NLTK), GIS, React, Cloud Infrastructure, SQL, Deep Learning, Amazon Web Services (AWS), Git, Agile Software Development, Linux, Bash, Sublime Text, Vim Text Editor, Classification, Data Pipelines, Django, Jupyter, Generative Pre-trained Transformers (GPT), GPT, Natural Language Processing (NLP), Parallel Programming, PyCharm, Data Science, Flask, React Redux, Algorithms, Data Analysis, Python 3, SciPy, DevOps, Amazon SageMaker, Data Scraping, Software Development, Programming, Transformers, Concurrent Programming, Data Engineering, Analytics, API Integration, Data Validation, Data Visualization, Dashboards, Databases, Software Engineering, Scikit-learn, Matplotlib, Unit Testing, ETL, GeoPandas, Quality Assurance (QA), APIs, Jupyter Notebook, Web Frameworks, REST APIs, Machine Learning

Lead Data Scientist

2020 - 2022
Botprise, Inc.
  • Developed the back end for the full ML cycle, ModelOps, and MLOps, on the platform. Added a wrapper on top of the AWS SageMaker.
  • Worked on dozens of automation workflows (use cases), including MLOps, analytics, DataOps, networks, and ITOps.
  • Created the back- and front-end elements using React for a drag-and-drop, chatbot-building application.
  • Implemented and deployed dozens of algorithms (classification, clustering, time series, NLP, and computer vision) for different use cases.
  • Led a small ML team, including planning, management, monitoring, and leadership.
Technologies: Amazon Web Services (AWS), Python, Flask, MongoDB, Apache Kafka, React Redux, REST, Docker, Kubernetes, Amazon SageMaker, SciPy, NumPy, Pandas, PyTorch, TensorFlow, Transformers, Management, PostgreSQL, Machine Learning Operations (MLOps), React, Cloud Infrastructure, SQL, Computer Vision, Deep Learning, Keras, Git, Agile Software Development, Linux, Object Detection, Convolutional Neural Networks (CNN), Bash, Sublime Text, Vim Text Editor, Anomaly Detection, Classification, Data Pipelines, AutoML, TCP/IP, Networks, Time Series Analysis, Concurrent Programming, Predictive Analytics, Jupyter, OpenCV, Predictive Modeling, Machine Learning Automation, Natural Language Processing (NLP), Generative Pre-trained Transformers (GPT), GPT, PyCharm, Data Science, Algorithms, Python 3, AWS CloudFormation, DataOps, Software Development, Networking, AWS Lambda, Artificial Intelligence (AI), Programming, Datadog, Natural Language Toolkit (NLTK), Data Engineering, Analytics, API Integration, Data Validation, Data Visualization, Neural Networks, Dashboards, Databases, Software Engineering, Linear Regression, Microsoft Excel, Spreadsheets, Scikit-learn, Matplotlib, Statistical Modeling, Unit Testing, ETL, Plotly, APIs, Jupyter Notebook, Automation, Web Frameworks, REST APIs, Machine Learning

Data Analyst

2020 - 2020
Spin (Tier Mobility)
  • Performed a time-series forecasting of the demand for e-scooters for a global e-scooter rental company (hundreds of cities) with models for auto selection and auto retraining.
  • Performed ad-hoc data analysis and built Looker dashboards.
  • Performed an intervention-effect analysis (for promotions and other events).
Technologies: Data Validation, Data Analysis, Data Analytics, Python, SQL, R, Data Science, Data Visualization, Google Cloud, Google Cloud Platform (GCP), Looker, BigQuery, Google BigQuery, Pandas, NumPy, Git, Agile Software Development, Linux, Cloud Infrastructure, Bash, Sublime Text, Vim Text Editor, Data Pipelines, Time Series Analysis, Predictive Analytics, Jupyter, Predictive Modeling, PyCharm, Apache Airflow, Algorithms, Docker, Python 3, SciPy, Software Development, Programming, Analytics, Business Intelligence (BI), Dashboards, Databases, Software Engineering, Linear Regression, Spreadsheets, Scikit-learn, Matplotlib, Statistical Modeling, ETL, Plotly, Jupyter Notebook, Internet of Things (IoT), REST APIs, Machine Learning

Senior MLOps Engineer

2020 - 2020
Pro Football Focus, LLC
  • Introduced and implemented MLOps techniques, tools, and approaches.
  • Rebuilt a dozen monolithic R pipelines into distributed, modular, and functional-styled Python pipelines.
  • Developed an MLOps layer on top of Dagster, Seldon, Feast, and other tools.
  • Fine-tuned existing model hyperparameters both for speed and performance.
Technologies: Data Science, Python, R, Machine Learning, React, Python 3, Seldon, Dagster, RabbitMQ, PostgreSQL, Feast, Machine Learning Operations (MLOps), Cloud Infrastructure, SQL, Deep Learning, Pandas, NumPy, Amazon Web Services (AWS), Git, Agile Software Development, Linux, Bash, Sublime Text, Vim Text Editor, Classification, Data Pipelines, Explainable Artificial Intelligence (XAI), Predictive Analytics, Jupyter, Predictive Modeling, Parallel Programming, PyCharm, Visual Studio Code (VS Code), Data Analytics, Apache Airflow, REST, Algorithms, Kubernetes, Docker, SciPy, Prefect, AWS CloudFormation, DevOps, Software Development, AWS Lambda, Programming, Dask, Data Engineering, Databases, Software Engineering, Linear Regression, Sports, Scikit-learn, Matplotlib, Statistical Modeling, Unit Testing, ETL, Plotly, Quality Assurance (QA), Jupyter Notebook, Web Frameworks, APIs, REST APIs, DVC

Machine Learning Engineer

2020 - 2020
Plutoshift, Inc.
  • Introduced MLOps tools to existing infrastructure with Seldon, Feast, Great Expectations, and others.
  • Migrated existing hardcoded models to introduce the MLOps infrastructure.
  • Developed back-end APIs using Django for ML-related services.
  • Implemented classification and time series forecasting models for manufacturing sensors.
Technologies: Machine Learning, Python, Django, Convolutional Neural Networks (CNN), Object Detection, TensorFlow, PyTorch, Keras, Apache Airflow, Cloud Infrastructure, Google Cloud Platform (GCP), Azure, Cassandra, Apache Cassandra, Seldon, Feast, SQL, Deep Learning, Pandas, NumPy, Git, Agile Software Development, Linux, Google Cloud, Bash, Sublime Text, Vim Text Editor, Anomaly Detection, Classification, Data Pipelines, Time Series Analysis, Predictive Analytics, Jupyter, Predictive Modeling, PyCharm, Data Science, Flask, REST, Algorithms, Kubernetes, Docker, Python 3, SciPy, Software Development, AWS Lambda, Programming, Datadog, Data Engineering, Data Visualization, Databases, Software Engineering, Linear Regression, Scikit-learn, Matplotlib, Statistical Modeling, Unit Testing, ETL, Quality Assurance (QA), Jupyter Notebook, Internet of Things (IoT), APIs, REST APIs

Senior AI Developer

2019 - 2020
Akcelita
  • Developed an ingestion and processing pipeline on AWS for photos from surveillance cameras.
  • Experimented with various non-DL and DL approaches and tested them. I also used and trained Siamese Neural Networks with an attention mechanism, achieving 95+% accuracy.
  • Created and shared presentations with analytics to executives and developed and maintained a Wiki for the project.
Technologies: Amazon Web Services (AWS), TensorFlow, Python, Docker, PyTorch, AWS Lambda, Computer Vision, Deep Learning, Machine Learning, Classification, Artificial Intelligence (AI), Cloud Infrastructure, SQL, Pandas, NumPy, Keras, Git, Agile Software Development, Linux, Convolutional Neural Networks (CNN), Bash, Sublime Text, Vim Text Editor, Data Pipelines, Predictive Analytics, Jupyter, OpenCV, Predictive Modeling, PyCharm, Data Science, Algorithms, Python 3, SciPy, Software Development, Programming, Data Visualization, Neural Networks, Software Engineering, Scikit-learn, Matplotlib, Statistical Modeling, Unit Testing, ETL, Jupyter Notebook, REST APIs

Team Lead

2018 - 2019
The National Academy of Sciences of Ukraine
  • Led and mentored a team of students. I defined objectives and controlled the process using the Agile methodology.
  • Created a tool for crop classification and map creation.
  • Collected data manually and via web scraping using Mapillary and oversaw data labeling.
  • Implemented and tested DeblurGAN and several other classic deblurring methods.
  • Oversaw field localization (YOLO) and crop classification by fine-tuning a ResNet model.
Technologies: OpenCV, PyTorch, TensorFlow, Keras, Python, Python 3, Computer Vision, Generative Adversarial Networks (GANs), Cloud Infrastructure, Deep Learning, Pandas, NumPy, Amazon Web Services (AWS), Git, Agile Software Development, Linux, Object Detection, Convolutional Neural Networks (CNN), Bash, Sublime Text, Vim Text Editor, Classification, Data Pipelines, Predictive Analytics, Jupyter, Predictive Modeling, PyCharm, Visual Studio Code (VS Code), Data Science, Algorithms, Docker, SciPy, Beautiful Soup, Web Scraping, Data Scraping, Software Development, AWS Lambda, Programming, GIS, API Integration, Neural Networks, Software Engineering, Scikit-learn, Matplotlib, Statistical Modeling, Unit Testing, GeoPandas, Jupyter Notebook, REST APIs, Machine Learning

Senior Data Scientist

2017 - 2019
Openwave Mobility
  • Created a multi-staged data pipeline from raw packet data (TCP/IP layer) to consumable inputs for machine learning models with multi-processing implementation in Python (CPython).
  • Trained, tuned, evaluated, and compared multiple machine learning models in Python (scikit-learn, Keras, XGBoost, CatBoost) and C++ (mlpack).
  • Oversaw the data analysis and communication with stakeholders. Created a reusable Python tool for generating rapid and externally configurable data analysis reports.
  • Implemented custom feature generation algorithms based on expert knowledge based on aggregation, derivatives, TCP/IP conversation delays, products, and fractions.
  • Implemented custom, multi-staged feature selection algorithms that were model-based.
  • Deployed and monitored the project in production in the network. If the tool detects congestion, optimization policies are applied. Customers reported up to a 20% increase in the quality of delivery for video content.
Technologies: C++, Python, Python 3, Concurrent Programming, Agile Software Development, Machine Learning, Deep Learning, Time Series Analysis, Networks, Networking, TCP/IP, TensorFlow, SciPy, Scikit-learn, Pandas, NumPy, mlpack, AutoML, Explainable Artificial Intelligence (XAI), Cloud Infrastructure, SQL, Amazon Web Services (AWS), Git, Linux, Bash, Sublime Text, Vim Text Editor, Classification, Data Pipelines, Predictive Analytics, Jupyter, Predictive Modeling, Machine Learning Automation, Parallel Programming, PyCharm, Data Science, Data Analytics, Algorithms, Docker, Data Analysis, Software Development, AWS Lambda, Artificial Intelligence (AI), Programming, Data Engineering, Analytics, Data Validation, Data Visualization, Neural Networks, Databases, Software Engineering, Linear Regression, Matplotlib, Statistical Modeling, Unit Testing, ETL, Plotly, Jupyter Notebook, Automation

Data Scientist

2015 - 2017
Octetis
  • Developed, deployed, and evaluated a hybrid recommendation engine in Python for an online store.
  • Oversaw customer behavior analysis, visualization, and stakeholder communication.
  • Handled different scenarios of user engagement using a strategy pattern. Contextual recommendations were given based on popularity (general and category-based), item-to-item, and SVD. (Python, scikit-learn, SciPy).
  • Integrated recommendation engine into a Django back end.
  • Conducted multiple A/B tests with random sampling for evaluation of the system. Compared to the most popular items in the category baseline, we achieved up to a 150% boost in purchases per session and increased revenue.
  • Created an image super-resolution module for an online cloud site constructor with Keras.
  • Utilized middle-deep CNN, trained on several blur kernels, and deployed it as a service via REST.
  • Conducted surveys showing an increase of about 5% in satisfaction for users of the platform.
Technologies: TensorFlow, Keras, Python, Pandas, NumPy, Python 3, PostgreSQL, Recommendation Systems, Django, Data Analysis, Data Analytics, Machine Learning, Artificial Intelligence (AI), Cloud Infrastructure, MySQL, SQL, Computer Vision, Deep Learning, Amazon Web Services (AWS), Git, Agile Software Development, Linux, Object Detection, Convolutional Neural Networks (CNN), Bash, Sublime Text, Vim Text Editor, Anomaly Detection, Classification, Data Pipelines, Time Series Analysis, Predictive Analytics, Jupyter, OpenCV, Predictive Modeling, PyCharm, Data Science, REST, Algorithms, Docker, SciPy, Jenkins, Microsoft Power BI, Software Development, AWS Lambda, Programming, Data Engineering, Analytics, API Integration, Data Validation, Data Visualization, Neural Networks, Business Intelligence (BI), Dashboards, Databases, Software Engineering, Linear Regression, Microsoft Excel, Spreadsheets, Scikit-learn, Matplotlib, Statistical Modeling, Unit Testing, ETL, Tableau, Plotly, Jupyter Notebook, REST APIs

Software Engineer Intern

2015 - 2015
Facebook
  • Trained and evaluated AdaBoost models for customer churn prediction using FBLearner Flow.
  • Performed hyper-parameters tuning for optimization.
  • Data-engineered with Hive and processed data using Python.
Technologies: Apache Hive, Python, Python 3, Data Pipelines, FBLearner Flow, Machine Learning, Git, Agile Software Development, Linux, Bash, Sublime Text, Vim Text Editor, Classification, Predictive Analytics, Predictive Modeling, Data Science, Data Analytics, Algorithms, Software Development, Programming, Data Engineering, Analytics, Databases, Software Engineering, ETL

Research Intern

2014 - 2015
Samsung
  • Developed algorithms for smart keyboard functionality (word prediction and spelling correction).
  • Developed Naive Bayes for n-grams and K-nearest neighbors (KNN) for spelling corrections.
  • Created tweaks for better algorithm performance using Laplace smoothing and a custom keyboard distance for KNN.
  • Developed algorithms with C++. Integrated them with a Java to Android keyboard and published them to the App Store.
Technologies: C++, Android, Java, Machine Learning, Artificial Intelligence (AI), Natural Language Processing (NLP), GPT, Generative Pre-trained Transformers (GPT), Android NDK, Git, Agile Software Development, Linux, Bash, Sublime Text, Vim Text Editor, Eclipse, Data Science, Algorithms, Software Development, Programming, Software Engineering

Software Engineer Intern

2013 - 2014
Engage Point
  • Developed a Content Management Interoperability System in Jakarta EE. I used the Model-view-controller framework for the application.
  • Developed Enterprise JavaBeans for the business logic of the application.
  • Developed JavaServer Pages for the presentation level.
Technologies: Java EE, Java, Linux, Git, Bash, Sublime Text, Vim Text Editor, Eclipse, Software Development, Programming, Software Engineering

Web Scraping Mapillary

This is a code sample for downloading images at specific locations using the Mapillary API. It searches for specific locations on the map, identifies the car's angle, and scrapes only side-view photos with nearly 90-degree angles of the road.

Languages

Python, SQL, Python 3, Bash, R, Snowflake, Fortran, Java, C++

Frameworks

Django, Flask, Web Frameworks, Selenium

Libraries/APIs

Scikit-learn, Keras, TensorFlow, PyTorch, Pandas, NumPy, SciPy, Beautiful Soup, Dask, Natural Language Toolkit (NLTK), Matplotlib, REST APIs, OpenCV, React Redux, PySpark, React

Tools

Jupyter, PyCharm, IPython Notebook, Amazon SageMaker, Geocoding, GIS, Vim Text Editor, Sublime Text, Plotly, Apache Airflow, Git, Celery, Jenkins, AWS CloudFormation, Grafana, Looker, Microsoft Power BI, AutoML, RabbitMQ, BigQuery, Microsoft Excel, Spreadsheets, Tableau, Notion, Android NDK, OpenAI Gym

Paradigms

Data Science, Agile Software Development, REST, Unit Testing, ETL, Parallel Programming, DevOps, Concurrent Programming, Anomaly Detection, Business Intelligence (BI), Automation, Management

Platforms

Docker, AWS Lambda, Seldon, Jupyter Notebook, MacOS, Amazon Web Services (AWS), Linux, Apache Kafka, Kubernetes, Visual Studio Code (VS Code), HubSpot, Eclipse, Android, Java EE, Google Cloud Platform (GCP), Azure

Storage

MySQL, PostgreSQL, Data Pipelines, Data Validation, MongoDB, Elasticsearch, Datadog, Databases, Apache Hive, Cassandra, Google Cloud

Other

Predictive Analytics, Predictive Modeling, Machine Learning Automation, Computer Vision, Data Analytics, Deep Learning, Machine Learning, Mathematics, Applied Mathematics, Statistics, Algorithms, Data Analysis, Dagster, Machine Learning Operations (MLOps), Prefect, Computer Science, Web Scraping, Data Scraping, Software Development, Artificial Intelligence (AI), Programming, Computational Science, Time Series Analysis, Convolutional Neural Networks (CNN), Object Detection, Feast, Data Visualization, Data Engineering, Analytics, Neural Networks, Software Engineering, Linear Regression, Statistical Modeling, GeoPandas, APIs, Generative Pre-trained Transformers (GPT), ChatGPT, OpenAI GPT-3 API, OpenAI GPT-4 API, OpenAI, Large Language Models (LLMs), Language Models, Recommendation Systems, Natural Language Processing (NLP), Science, Scientific Computing, DataOps, Physical Science, Networking, Physics, Applied Physics, Transformers, TCP/IP, mlpack, Explainable Artificial Intelligence (XAI), Cloud Infrastructure, Google BigQuery, API Integration, Dashboards, Quality Assurance (QA), GPT, Internet of Things (IoT), HubSpot CRM, LangChain, Generative Adversarial Networks (GANs), Networks, FBLearner Flow, Classification, Apache Cassandra, Sports, Software Architecture, Sentiment Analysis, DVC

2019 - 2021

Master's Degree in Theoretical Physics (Quantum Field Theory)

Kyiv National University - Kyiv, Ukraine

2018 - 2020

Master's Degree in Computer Mathematics and Algebra

Kyiv National University - Kyiv, Ukraine

2010 - 2014

Bachelor's Degree in Computer Science and Applied Statistics

Kyiv National University - Kyiv, Ukraine

JULY 2023 - JULY 2026

AWS Machine Learning Specialty

Amazon Web Services

JANUARY 2023 - JANUARY 2026

AWS Solutions Architect Associate

Amazon Web Services

OCTOBER 2022 - OCTOBER 2025

AWS Certified Developer Associate

Amazon Web Services

MAY 2017 - PRESENT

Data Science: Data to Insights

MITProfessionalX DSx | edX

JANUARY 2017 - PRESENT

Artificial Intelligence (AI)

ColumbiaX CSMM.101x | edX

MAY 2011 - PRESENT

Second Place

ACM-ICPC, Country level

JULY 2010 - PRESENT

Bronze Medal

International Mathematical Olympiad (IMO)

MAY 2009 - PRESENT

Second Place

Kyiv International Physics Festival

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