University of Texas at Austin
Center for Advanced Heart Failure, Memorial Hermann Hospital
Jan 2015 – Feb 2016
March 2016 – March 2022
Surgalign Spine Technologies
March 2022 – Present
June 2022 – August 2022
As part of my involvement across the machine learning teams and productization/analytics, I played a key role in the development of a PDF report for evaluating images of spinal stenosis and disc degeneration. This project aimed to provide a quantitative approach for analyzing lumbar spine MRI images, with the goal of reducing inter-reader variability among radiologists.
The PDF report prototype showcases a fully automated software solution that simplifies the workflow for clinicians, reducing their workload and improving throughput in repetitive routines and labor-intensive tasks. By adopting the latest AI software, we aimed to enhance the services provided by medical practices, differentiating them in the market and potentially attracting additional business from clients.
July 2022 – Present
Cloud-Based AI Web Product
In this project, I led the implementation of a web-based user interface that enabled users to upload their data and conveniently download their results. The user interface was designed to provide a seamless and intuitive experience, allowing clinicians and healthcare professionals to easily access and interact with the data generated by our software solutions.
May 2023 – Present
DICOM Visual Method
In this design project, I was responsible for creating a visually captivating and user-friendly method to display AI-generated insights within DICOM medical imaging. Leveraging my expertise in product management and UX design, I ensured a seamless integration of these insights into physicians’ workflows, providing them with valuable information at a glance.
Working closely with the DICOM standard and immersing myself in physician workflows, I gained a deep understanding of the field’s intricacies. My goal was to bridge the gap between machine learning input/outputs, customer requirements, and business inputs, ultimately delivering a harmonious and effective solution.
Taking full ownership of the visual method, I meticulously crafted prototypes specifically tailored for spine and brain applications. These prototypes included enhanced MR series and innovative summary series, carefully designed to present all the necessary information in a concise manner.
An important aspect of my solution was its compatibility with physicians’ preferred viewers. I ensured that my DICOM series seamlessly integrated with their existing tools, reducing any friction in the adoption process and allowing for a smooth transition into their established workflows.
By combining my skills in product management and UX design, I successfully enhanced the efficiency and effectiveness of physicians’ daily work. My intuitive and valuable tool seamlessly integrated AI-generated insights into their current practices, empowering them to make informed decisions.
This project showcases my ability to deliver impactful solutions in the healthcare industry, leveraging my expertise in product management and UX design to create a user-centric experience that meets both technical and user requirements.