Imagine a future where healthcare consists of engineers working alongside medical researchers and clinicians to build better ways to measure the body, model disease, predict risk and design more effective diagnostics and treatments. That's what Dr. Kristin Myers is doing in the field of women's health.
Digital twins have transformed manufacturing by allowing engineers to simulate systems, predict failures and optimize performance before making changes in the real world. Dr. Kristin Myers believes those same engineering principles could fundamentally reshape healthcare. As a mechanical engineering professor at Columbia University, Myers is applying computational modeling, AI and biomechanics to one of medicine’s most complex frontiers.
In this episode, Myers explains why women’s health has historically been difficult to study, how engineering disciplines are beginning to fill decades-long research gaps, and why technologies like digital twins, wearable sensors, machine learning and computational models may dramatically improve diagnosis, treatment and long-term patient outcomes. She also explores what this emerging field means for engineers, educators and the next generation of healthcare innovation.
In this episode:
- Why digital twins could become as important in healthcare as they already are in manufacturing.
- The engineering challenges that have slowed progress in women’s health research for decades.
- How AI, wearable devices and longitudinal patient data could transform diagnosis and personalized medicine.
- Why mechanical, electrical and software engineers all have a role to play in the future of healthcare.
- What engineering educators should teach today to prepare students for tomorrow’s biomedical breakthroughs.
3 Big Takeaways from this Episode:
1. Engineering is becoming a core driver of healthcare innovation. The future of medicine won’t be built by clinicians alone. Myers explains how mechanical engineers, computational modelers, AI researchers and device designers are bringing new tools and ways of thinking to problems that traditional medical research has struggled to solve.
2. Digital twins are moving from factories to patients. The same technologies manufacturers use to simulate equipment and optimize production are beginning to model organs, pregnancies and disease progression. While clinical implementation remains years away in many applications, digital twins are already accelerating biomedical research and medical device development.
3. Tomorrow’s engineers will need both technical fundamentals and AI fluency. As AI reshapes engineering education, Myers argues that foundational engineering principles remain essential. Students must still learn how systems work from first principles while using AI to accelerate analysis, design and innovation rather than replace critical thinking.
Resources in this Episode:
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More notes & resources on the episode page: https://techedpodcast.com/columbia/
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