

JourMate is a AI-Powered Travel Social Media Platform designed to help travelers connect with like-minded individuals from around the world. Thanks to advanced AI algorithms, users can find travel companions who share the same hobbies and interests.

For the seventeenth year, in the spring for students of the bachelor study programmes “Artificial Intelligence Systems” NURE (AI Dep) together with French colleagues from ECAM-EPMI Graduate School of engineering (Cergy-Pontoise) are launching an entrepreneurship training course in the IT field. Over the course of a month, Ukrainian and French students will work together in an interactive mode to generate innovative ideas, to develop business plans for them, and defend their plans before a professional international jury.
Travelers often struggle to find companions who share the same hobbies and interests, making their travel experiences less enjoyable and fulfilling.
JourMate is an AI-Powered Travel Social Media Platform designed to help travelers connect with like-minded individuals from around the world. Thanks to advanced AI algorithms, users can find travel companions who share the same hobbies and interests.










A Computer Science graduate from Ukraine with a strong academic background, proficient in using various programming languages. Skilled in web application development through coursework projects. Actively engaged in international activities to enhance knowledge.
Find out moreExplore a collection of my diverse projects ranging. Each project showcases my skills and creativity in different areas. Click on any project to learn more about the technologies used, the development process, and the final outcome.

Connectify is an innovative project aimed at revolutionizing the way people discover and engage with events. The idea for Connectify emerged from the need to create a more personalized and efficient platform that connects users with events that truly interest them. With the increasing volume of events and activities available, users often struggle to find those that match their preferences. Connectify addresses this challenge by leveraging advanced technologies to offer a seamless and tailored user experience.









The primary objective of Connectify is to develop an intelligent interface that enhances the convenience and effectiveness of user interactions.
This involves:
Implementing a recommendation system that provides personalized event suggestions.
Integrating intelligent search capabilities to help users find relevant events quickly and easily.
To achieve these objectives, the project sets out the following goals:
Profile Personalization: Allow users to create and customize their profiles, providing a more tailored experience based on their interests and activities.
Integration of Collaborative Filtering and Intelligent Search: Utilize advanced algorithms to analyze user behavior and preferences, ensuring accurate and relevant event recommendations.
The development of an intelligent interface for Connectify is crucial as it represents a significant advancement in the field of event-based platforms. By utilizing artificial intelligence and focusing on personalized recommendations, Connectify aims to:
Enhance user satisfaction by providing a more intuitive and user-friendly experience.
Increase engagement by connecting users with events that match their interests.
Foster a sense of community by facilitating meaningful interactions between users and event organizers.
Take a look at the Connectify mobile version prototype, which was a key part of the development process:
Now the interaction process of the user who is already using the application will be demonstrated.
The application is intuitive and pleasing to the eye, all categories have their own color that can be set. After logging into the system, the user passes the quiz and selects the categories he likes, then returns to the main screen where he already sees event recommendations. The user can like and add to the cart and only then buy flowers for the event. Then the user returns to the main screen and we can also see that we have all the selected categories in the quiz prioritized for convenience and adaptability
I also want to demonstrate the operation of intelligent search using the request: where to go with a child?
I want to emphasize the advantages of working with the developed model, compared to manual search. As if the user wanted to go somewhere with a child, he would have chosen the category with children, but our system considered other events from other categories that fit the request. The user receives a wider set of events in a shorter time.
If this piques your interest, feel free to explore the code on GitHub