Oleh Boloban PhD of Computer Science
AI & microservices for sleep‑apnea diagnosis. I build real‑world impact from peer‑reviewed research and apply it in Auri, an AI assistant for mental health.
Research Highlights
End‑to‑end tracking & prediction outside clinics
A fully integrated system for tracking and predicting respiratory pathologies in home environments, built on microservices for easy sensor/model integration and scalability across user groups.
Continuous monitoring, trend analysis & risk alerts
Home‑use AI system that monitors respiratory parameters during sleep, analyzes trends, and predicts potential risks so patients can seek timely medical attention.
Remote access & decision support for doctors
Secure physician dashboards integrate with medical platforms to review longitudinal data and support informed diagnosis and treatment while reducing clinic workload.
Publications
- Scientific article Boloban, O., Pysmennyi, I., Kyslyi, R., & Kyriusha, B. (2024). Development of a patient health monitoring system based on a service-oriented architecture using artificial intelligence. Technology Audit and Production Reserves, 3(2(77)), P. 23-29.
- Scientific article Petrenko, A. I., Boloban, O. A. (2025). Development of infrastructure for the integration of artificial intelligence into telemedicine systems using microservice architecture. Tavrian Scientific Bulletin. Series: Technical Sciences, (1), P. 148-158.
- Scientific article Boloban O.A., Petrenko A.I. Features of the EMD algorithm application for estimation of blood oxygen level. Scientific notes of Vernadsky TNU. Series: Technical sciences. Vol. 34 (73). № 2. 2023. P. 125-130.
- Scientific article Petrenko, A., Boloban, O. (2023). Generalization of information with examples on the possibilities of using a service-oriented approach and artificial intelligence technologies in the field of e-health. Technological audit and production reserves, 4 (2 (72)), P. 10-17.
- Scientific article Petrenko, A., Boloban, O. (2024). Investigation of the effectiveness of real-time filtering algorithms for biomedical signals. Infocommunication and computer technologies, 2(08), P. 53-61.
- See all publications on ORCID →
Auri
AI assistance for mental health. Auri creates personalized recommendations from your physiological & activity records (sleep, HR, SpO₂, HRV, work time, mood, steps, etc.), classifies disorder risk/type, and drafts guidance with an LLM.
The Problem
- Limited access to timely mental‑health evaluation.
- Wearable data is fragmented and under‑used.
- Lack of continuous, personalized monitoring and feedback.
Our Solution
- Unified pipeline for multi‑modal signals (sleep, HR/HRV, SpO₂, activity, mood).
- AI models to detect patterns and classify likely disorder categories.
- LLM‑generated, clinician‑informed recommendations and next steps.
Who we serve
Individuals tracking well‑being, clinicians needing longitudinal data, and research teams running digital‑health studies.
Traction
About
Bio
Oleh Boloban is a software engineer and researcher (PhD in Computer Science) focusing on AI and microservice architectures for healthcare. His recent work builds home‑use systems for monitoring and predicting respiratory disorders during sleep, and remote‑care workflows for clinicians. He is the founder of Auri, bringing these capabilities to mental‑health support.
Keywords: machine learning, neural networks, classification, Internet of Things (IoT), energy-efficient computing, formal specification, distributed systems, sleep apnea and hypopnea, microservices, COVID-19, modeling, execution time reduction, Temporal Logic of Actions (TLA).
Open to
- Research collaborations
- Industry pilots / partnerships
- Speaking & mentoring