Responsibilities include:

• Created a PoC for a national sports team that analyzes and recognizes athletes’ moves from video.
• Developed a tool to annotate data and guided a team of annotators throughout the project.
• Built a tool to detect athletes in images along with their body part positions.
• Created a tool to classify movements based on sequences of frames with detected athlete positions.
• Developed a simple React app to demonstrate the PoC.
• Key technologies used:
  • Python: Sklearn, FastAPI, React, PostgreSQL, MinIO
  • AWS: EC2, S3

Responsibilities include:

• Worked on liveness detection as part of the team.
• Designed and implemented a tool to detect deepfake videos.
• Developed a tool to detect rPPG signals (pulse) in videos for printed mask detection.
• Key technologies used:
  • Python: PyTorch, Hydra, MLflow, Neptune, FastAPI
  • AWS: EC2, S3

Responsibilities include:

• Led a team in developing an AI system to suggest rehabilitation methods for stroke patients.
• Managed the project using SCRUM methodology.
• Created the architecture and data pipelines.
• Directed the programming efforts of the team.
• Collaborated with doctors, developers, and UX designers.
• Key technologies used:
  • Python: Sklearn, DVC, MLflow, FastAPI
  • AWS: EC2, S3, Fargate
  • DevOps: Terraform
  • Project Management: Jira, Confluence, Bitbucket

Responsibilities include:

• Led a team in an AI project involving chess piece detection for an AR application.
  • Conducted the project using SCRUM methodology.
  • Created architecture and data pipelines.
  • Led programming efforts.
• Constructed data pipelines and AI architecture for a large marketing company.
• Key technologies used:
  • Python: Sklearn, MLflow, FastAPI
  • AWS: EC2, S3, Fargate

Responsibilities include:

• Created an end-to-end podcast segmentation model for a media company.
• Developed classifiers for podcast text data (type and topic).
• Organized and supervised annotation processes.
• Prepared pipelines for medicine and drug demand prediction.
• Built AI systems for scraping and processing startup data.
• Developed AI models for website content classification.
• Created predictive models and pre-processing for a taxi company.
• Conceptualized pipelines for improved delivery processes.
• Developed models to detect and extract high-voltage lines.
• Built machine learning models for stock utilization prediction and assembly line error detection.
• Implemented object detection algorithms for a martech company.
• Analyzed logistics and predicted demand for manufacturing companies.
• Key technologies used:
  • Python: TensorFlow, Django, Keras, PyTorch, Gensim, Transformers, spaCy, NLTK, LightGBM, FuzzyWuzzy, Imgaug, OpenCV, XGBoost, scikit-learn, Celery, Flask, RabbitMQ
  • AWS: EC2, S3

Responsibilities include:

• Developed an algorithm to detect text in images and transcribe it digitally.
• Prepared frameworks to detect cancer cells in images.
• Created frameworks for improved credit scoring models in banking.
• Developed an e-commerce application to manage marketing expenses.
• Key technologies used:
  • Python: LightGBM, PyTorch, OpenCV, XGBoost, scikit-learn, Flask
  • R: Shiny, DT, ShinyDashboard, Tidyverse, ShinyJS, Dygraphs, HTMLWidgets, Plotly, caret

Responsibilities include:

• Worked in a research team focusing on stochastic processes and their applications.
• Advanced state-of-the-art research in stochastic processes.
• Performed scientific hypothesis testing using analytical approaches.
• Taught international student groups and prepared examinations.
• Developed programming skills in R and MATLAB.
• Presented research at numerous conferences, including SPA Oxford, SPA Gothenburg, and others.