Responsibilities include:

• Developed a highlights extraction method for the video preview (Pytorch, OpenCV, ffmpeg)
• Designed and built a movie recommendation system and short video recommendation system (GoLang, Python, PostgreSQL, Redis, XGBoost, Pytorch, AirFlow)
• FaceSwap for changing actors in the movie (Python, Deepfake)
• Personalized Avatar generation (Python, Segmentation tools, StableDiffusion)
• Semantic search engine (Python, ElasticSearch, BERT)

Responsibilities include:

• Created a data science competition pipeline for evaluating solutions in a Docker environment (Python, Docker)
• Coordinated machine learning competitions in different domains such as NLP, CV, and Recommender Systems (Kaggle, Codalab, ods.ai)

Responsibilities include:

• Developed a comprehensive MRI image analysis tool composed of multiple models for explaining images and providing doctors with a second opinion (Python, BLIP, Segment Anything)
• Developed a tool for predicting the risk of stroke in patients recovering from a stroke (Python, XGBoost)

Responsibilities include:

• Developed a recommendation system pipeline for suggesting medical articles (Python, Spark, Pytorch, BERT)
• Speech-to-text model to aid doctors in taking notes during patient consultations (Python, Kaldi, DeepSpeech)
• Utilized uplift modeling techniques to optimize marketing strategies and maximize user engagement (Python, Scikit-learn, XGBoost)
• Implemented multi-armed bandits algorithms for efficient exploration and exploitation of recommendation strategies (Python, Thompson Sampling, UCB)

Responsibilities include:

• Teaching a course on Robust Machine Learning
• Supervising students’ research projects