CuesHub delivers real-time calmness scores to Apple Watch and iPhone, built on 15+ years of NIH-funded biosignal research. Using heart rate variability and validated biomarkers, it gives people insight into their stress state before critical moments — helping them make better decisions, preserve mental energy, and reduce the long-term health impact of chronic stress.
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NIH-funded center transforming health via temporally-precise mobile interventions. Led software architecture across three R&D tracks: identifying critical moments of elevated health risk, applying reinforcement learning to optimize intervention timing, and expanding access to emerging biosignal biomarkers for remote patient care.
NIH Big Data to Knowledge Center of Excellence advancing biomedical discovery through mobile sensor data. Built end-to-end open-source infrastructure — from embedded sensor collection to population-scale analytics — enabling the P5 medicine vision (predictive, preventive, personalized, participatory, precision) across 20+ deployed clinical studies generating trillions of data points.
Flexible smartphone platform for mobile and wearable sensor data collection and real-time processing. Acts as the on-device OS for mobile health research — handling reliable high-frequency sensor management, data quality assurance, and intervention delivery. Funded by NIH, NSF, and IARPA; used across clinical deployments worldwide.
The big-data cloud companion to mCerebrum. A Python-based framework for population-scale analysis of mobile sensor data — parallelizing computation across machines, providing pre-trained ML markers for stress detection and ECG quality, and supporting flexible storage backends. Bridges raw wearable data to actionable clinical insights.
Ph.D. dissertation research at the University of Virginia: a system for tracking people in homes using ambient sensor fusion — no cameras, no wearables. Foundational work enabling occupancy-aware smart homes and in-home health monitoring. Laid the groundwork for subsequent mobile health sensing research.
I'm a software engineer and co-founder who has spent two decades building systems at the intersection of embedded hardware, cloud platforms, and mobile health. From the firmware layer up to population-scale analytics, I've shipped software that runs in real clinical deployments at 20+ research institutions.
Today I'm CTO and co-founder of CuesHub — translating 15+ years of NIH-funded biosignal research into a consumer product that gives people a real-time window into their stress state on Apple Watch and iPhone. It's the kind of work that only happens when you've spent years in the lab and can finally build the thing you always wished existed.
Before CuesHub I led software architecture for two NIH centers (MD2K and mDOT), building the open-source infrastructure that made wearable sensor research at scale possible. I still believe the most interesting problems are the ones that sit between disciplines.
My surname's origin traces back to a small farming town in Poland.
