Alio is developing a remote monitoring platform for multiple diseases. The platform includes wearable sensors, telemetry, and cloud-based data processing. Initial products include a wearable for dialysis patients that enable improved outcomes in maintaining healthy AV fistulas. We are building wearable and implantable devices with an integrated sensor platform and leveraging our proprietary cloud software to change patient lives.At Alio I work across disease states to improve our sensor and algorithm platform. I have helped build and validate the company's sensor hardware, benchtop testing infrastructure and REST API software system. My current focus is on the cloud-based signal processing and machine learning backend systems that allow us to convert raw signals into healthcare intelligence that clinicians can use to deliver better care.

Total joint arthroplasty (TJA) is the replacement of damaged bone and tissue with a biocompatible prosthesis made of metal and polyethylene. The leading cause of revision is periprosthetic joint infection (PJI), a bacterial infection at the site of the implant that occurs in roughly 2% of all TJAs. At a cost of over $110,000 per revision, the annual cost of PJI to the United States healthcare system is $4 billion. Synotrac provides a solution that acts to identify infection at the source and alert the patient in real time. By catching infection in its early stages the device enables treatment with antibiotics, which has a success rate of over 90%.

Worked in a cross-functional team as an engineer, scientist and salesman. Developed instrument platforms for high throughput pathogen identification. Deployed pathogen detection systems for biosecurity, food and agriculture applications. Obtained grant funding for development of advanced pathogen sensing instrument systems. Developed market strategy for food and agriculture disease diagnosis and control. Redesigned company website and marketing materials. Led development of new biological assays in collaboration with scientific team.

Worked with a graduate student to develop novel reverse engineering techniques for the quantification of wear in explanted joint prostheses. Quantified wear of explanted metal hip prostheses using a coordinate measuring machine. Used molding and rapid prototyping techniques to model explanted devices for destructive imaging. Developed algorithms in Matlab to generate and analyze 3D models of explanted devices. Analyzed the models using CAD programs to produce wear measurements of the explanted prostheses.

As part of a small team of college students, built and alpha-tested functional prototypes of a self-contained AV system for schools in developing countries, including battery power, 3G internet connection, and motion control wand. Constructed circuitry that enabled the device to be powered solely by a 12 volt car battery. Oversaw initial alpha testing and implemented revisions to prepare for field testing in Nepal's Kathmandu Valley.