Current student, Ronan Hwang, shared the following about being a Summer Intern at Ganance …

What did you do as an intern at this organization?
As a Software Engineering Intern at Ganance, I focused on developing a predictive model using motion sensor data to classify physical activities. These activities include walking, biking, driving, or sitting. I worked with Ganance Heir sensors and iterated through multiple versions of the model until I achieved accurate predictions. Alongside technical development, I contributed to team operations remotely and participated in an in-person showcase event in Chicago, which deepened my understanding of the company’s mission and culture.
How did you find this internship?
I found Ganance through a professor at Tufts, Phillip Ellison, and a friends mom from High School, Rehana Farrell
What did you enjoy most about your internship?
The highlight was meeting the team in person during the EDC and Watches Showcase in Chicago. After working remotely for most of the internship, spending time with the team in person helped me connect more deeply with the people behind the product and understand how decisions are made within a startup environment. That weekend was both energizing and inspiring.
What did you find challenging?
One of the biggest challenges was navigating unfamiliar software and sensor technologies with limited guidance. Since the team had minimal experience with the predictive modeling tools I was using, I had to independently research solutions, think critically, and balance technical decisions with team expectations. This pushed me to become more resourceful and confident in my problem-solving abilities.
What advice would you offer to someone who wants to make the most of an internship like yours?
Advice I would offer someone would be to set clear goals early on and hold yourself accountable, especially in remote environments. Daily standups helped me stay focused, but self-discipline was key. Be ready to learn independently, ask thoughtful questions, and embrace the steep learning curve.
