Today we’d like to introduce you to Jay Shah.
Hi Jay, thanks for joining us today. We’d love for you to start by introducing yourself.
I grew up fascinated by both technology and healthcare, and that curiosity eventually led me into AI research. I earned my Ph.D. in Computer Science from Arizona State University, where I focused on applying deep learning to medical imaging for the early detection of neurological diseases. Along the way, I had the opportunity to collaborate with leading medical institutions, publish research, and develop new methods that improved the accuracy and reliability of AI systems in healthcare.
Today, I work as a Machine Learning Engineer at PathAI, building AI solutions that support precision medicine and digital pathology. Beyond my day job, I enjoy mentoring researchers, reviewing scientific work, and sharing what I’ve learned with the broader AI community. My goal has always been to use AI not just to push the boundaries of research, but to create technologies that make a meaningful difference in people’s lives.
We all face challenges, but looking back would you describe it as a relatively smooth road?
It definitely hasn’t been a completely smooth road. Like many researchers, I experienced plenty of setbacks: experiments that didn’t work, papers that were rejected, and months spent debugging models that didn’t perform as expected. But I guess research teaches you that progress is rarely linear, and to embrace failure as part of the process.
Being an international student in the U.S. added another layer of challenges. I had to adapt to a new academic culture, build a support network from scratch, and navigate the uncertainties of visas and career planning while keeping up with the demands of graduate research. It wasn’t always easy balancing those responsibilities, but the experience made me more resilient, adaptable, and appreciative of every opportunity to learn and grow.
Another challenge was working at the intersection of AI and healthcare, where success isn’t just about building an accurate model. It requires understanding clinical workflows, collaborating across disciplines, and ensuring that the solutions are interpretable and genuinely useful in practice.
Alright, so let’s switch gears a bit and talk business. What should we know about your work?
I’m a Machine Learning Engineer at PathAI, where I build AI solutions for digital pathology and precision medicine. Before that, I earned my Ph.D. in Computer Science from Arizona State University, where my research focused on deep learning and medical imaging for the early detection of neurological disorders.
Outside of work, I host the Jay Shah Podcast, where I talk with researchers, engineers, founders, and AI leaders about technology and innovation. It’s been exciting to grow the podcast to over 7,000 subscribers and 400,000+ downloads, and I enjoy making AI more accessible to a broader audience.
Outside of AI, I’m also a licensed private pilot with ratings in both gliders and single-engine airplanes. Flying has taught me discipline and decision-making, skills that translate well into engineering and research.
I’m most proud of being able to contribute to AI in different ways: through research, building real-world products, and sharing knowledge with the community. I think what sets me apart is that I enjoy not only solving technical problems but also helping others learn and stay curious.
Any big plans?
My long-term goal is to bridge cutting-edge AI research with practical applications that improve people’s lives. I’m excited to take on larger technical leadership opportunities, contribute to impactful research, and (maybe) am seriously considering building a startup based on my Ph.D. research. I also want to keep growing my podcast into a platform where people can learn directly from leaders across AI, science, and technology.
Contact Info:
- Website: https://jaygshah.github.io/
- LinkedIn: https://www.linkedin.com/in/shahjay22/
- Twitter: https://twitter.com/jaygshah22
- Youtube: https://www.youtube.com/c/JayShahml
