OfferingTree simplifies website management, scheduling, and payment processing so that wellness professionals including coaches, yoga teachers, personal trainers, mindfulness instructors, and others can focus on their clients and students. OfferingTree is a Public Benefit Corporation, registered in Minnesota, committed to wellness education and access.

Acquired by Omada Health in May of 2020

• Lead Android developer on SportsEngine’s flagship team management app and other mobile products.• Responsible for the mobile team's build automation and continuous deployment tools.• Software architecture representative for SportsEngine’s team management products.• DevOps representative for the mobile team.

• Designed and developed an Android-app based data acquisition system for a Teen Driver Support System research study that monitors and records teen driving behavior. The app integrated with a custom-built in-vehicle DAQ via Bluetooth, and synced data with a web app built using the Django framework.• Built the EZ Thanks Android app used to provide employee recognition through BI Worldwide’s suite of products.• Built the Bluetooth vehicle sync app module for Polaris Industries mobile apps• Developed MePlus - an Android app for HealthPartners to allow their insurance clients to track their daily habits including exercise, smoking, stress, and sleep.• Developed an Android tablet application for inventory control for Menards, a large national hardware retail store. The application replaces dedicated scanner hardware for inventory control and audits.• The founding team was acquired by SportsEngine in 2014

• Developed a smartphone-based Teen Driver Support System that warns teen drivers of bad driving behavior such as speeding and excessive accelerations.• Developed an ARM-based data acquisition system with integrated sensors, internal storage, wireless data streaming and graphical display capabilities• Developed a Cooperative Intersection Collision Avoidance System that incorporates vehicle-infrastructure communication for collision avoidance at rural expressway intersections. The system is currently being tested at three intersections in Minnesota and another in Wisconsin. A comprehensive usability study is currently being performed to validate the system before a wide-scale, nationwide deployment.• Developed a portable intersection surveillance system to study driver gap acceptance/rejection behavior at rural expressway intersections. The system, developed as part of the Intersection Pooled Fund Study, was transported and deployed at eight intersections across the USA. The data collected is being used in the development of a national intersection collision avoidance system for rural expressway intersections.• Developed automated test protocols for studies involving test subjects driving instrumented vehicles through a research intersection. • Assisted in the development of a driver-assistive system for transit buses. The system includes a lane-assist system to keep the bus in its lane, as well as collision warning systems in front of, and on the sides of the bus. As part of the Urban Partnership Agreement, ten buses in the Minnesota Twin-Cities area have been instrumented and are being tested in real-world transit operations.• Developed an automated, repeatable test protocol on an instrumented motorcycle. The study, funded by the National Traffic Highway Safety Administration, was used to determine the effects of alcohol on motorcycle riders.

• Developed a radar-based vehicle detection system and mainline system state estimator.• Developed a lidar-based vehicle detection and classification system that provides system state and vehicle type information about slow moving vehicles approaching an intersection.• Developed a vision-based vehicle detection system that provides system state in the cross-roads of an intersection. The system works with both visible-light cameras as well as infra-red cameras and adapts to provide data in all lighting conditions.• Developed a sensor-based, real-time vehicle sensing and sensor fusion algorithm for an Intersection Decision Support System. System state estimators and sensor fusion (radar, lidar and vision-based systems) determine the intersection state (vehicle positions, trajectory, gaps, etc.) at 10Hz.