Introduction
At just 17 years old, Anshul Bhatt is leveraging artificial intelligence to revolutionize animal healthcare and assist medical professionals. Motivated by personal experience and driven by innovation, Anshul’s projects demonstrate how accessible AI technology can transform diagnostic processes for both animals and humans.
A Teen’s Personal Experience Sparks Innovation
For many teenagers, technology is mainly about making life easier. But for 17-year-old Anshul Bhatt, technology became a tool to solve a personal problem.
When Anshul’s family dog, Max, was diagnosed with advanced arthritis, he realized how limited and expensive diagnostic tools for animals were. By the time the vets found out what was wrong, the damage was already too severe to fix.
“That experience showed me how early signs of disease in animals can go unnoticed,” Anshul explains. “If we could detect problems earlier, the results would be much better.”
Creating PawPath: AI Detecting Animal Mobility Problems
Driven by curiosity and using OpenAI’s tools to learn, Anshul started looking into how artificial intelligence might spot movement problems in animals.
What began as a personal project developed into PawPath. This system uses AI along with motion sensors to find early signs of orthopedic and neurological issues in dogs.
PawPath uses four small, light sensors attached to a dog’s legs. These sensors record movement hundreds of times each second. Then, a machine learning model analyzes the data, looking for patterns linked to conditions like arthritis, ligament injuries, or ataxia.
Unlike expensive lab machines, PawPath is portable and affordable. This makes it practical for animal shelters and small veterinary clinics. Currently, Anshul is testing it at large animal welfare centers. It has already helped detect mobility issues in rescued dogs.
“This tool is not to replace vets,” Anshul says. “Instead, it gives vets faster, data-based help to decide which animals need care first.”
Learning with OpenAI Rather Than Just Using It
Since traditional resources could not fully support him, Anshul relied on OpenAI’s tools as his main research aid. He used ChatGPT to understand tough topics like sensor fusion, motion tracking, and Kalman filters — subjects usually studied at graduate level.
“I used OpenAI tools to learn and fix problems,” he says. “They helped me understand hard ideas quickly, especially when no one else was around to ask.”
OpenAI did not replace the effort needed for research. Instead, it sped it up. It acted as a teacher, partner, and coding helper that allowed him to move from reading about ideas to actually building the system.
Expanding into AI for Medical Imaging
PawPath was not the end of Anshul’s AI work. During a summer research program at MIT, he joined a team at Harvard Medical School to study how AI could reduce repetitive tasks in radiology.
He developed voice-operated AI agents powered by OpenAI models. These agents could navigate radiology software, automate simple image checks, and help reduce stress and fatigue for clinicians.
“The goal was to make AI helpful for the people doing the work, not to replace them,” he explains.
Both projects, though very different, are based on the belief that AI can boost human abilities in important ways — for doctors and animals alike.
Driven by Impact More Than Recognition
Anshul’s focus has never been on awards, though he has earned several. These include winning the Grand Award at the Regeneron International Science and Engineering Fair and being named one of the top 100 young researchers worldwide.
His true reward comes from using AI to create real change. “I’ve learned that you don’t need a big lab or a team of experts to get started,” he says. “What you need is curiosity and the willingness to build.”
From diagnosing movement problems in dogs to helping automate radiology work, Anshul’s projects show how OpenAI is supporting a new generation of young researchers to learn independently, explore deeply, and create meaningful solutions.
