I'm a machine learning engineer and a full-stack web developer. I believe that technology should serve humans and not the other way around. I want to use machine learning to improve quality of life and solve important problems of today.
Predicting the tertiary (3-dimensional) structure of a folded protein given its primary structure (sequence of amino acids).
A product recommendation system and churn model for insurance companies.
CNN's attention compared to human attention based of eye-tracking data.
Software that created a real time map for assesing quality of a colonoscopy exam. The project was developed as a desktop app based on gastroentherologist's expertise.
Real-time detection of parking space occupancy. The project was a POC that aimed to replace expensive sensors. I used traditional computer vision techniques.
An app that uses sentiment analysis to estimate current mood in European countries based on twitter data and recommended travel destinations together with flight prices fetched from Skyscanner api.
A novel technique for visualizing emotion recognition results including the temporal dimension. An "emotion space" is created using parametric t-SNE, where machine learning models can be visually compared with respect to modalities, models, and hyperparameters used.
A web app that allows its user to set rules that get evaluated based on input features. Its primary goal was to create a universal way of deciding which insurance products should be displayed depending on the user's information.