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Software engineer and AI researcher Tianyang Chen is working to make healthcare more intelligent, proactive, and accessible. With deep experience in artificial intelligence and a history of building large-scale software systems, he is now applying his technical expertise to address one of the most pressing challenges in modern medicine: the burden of chronic diseases such as diabetes.
Tianyang Chen’s interest in healthcare began with projects focused on medical imaging and non-invasive monitoring. “One of our studies aimed to improve how computers interpret eye scans by learning from multiple medical experts. This approach helps reduce diagnostic inconsistencies and accelerates the evaluation process,” he explains. In another project, he investigated a non-invasive technique to estimate blood glucose levels by analyzing how light interacts with the skin. This research presents a promising alternative for individuals who currently rely on painful finger-prick tests.
These efforts are highly relevant to the national healthcare landscape. According to the Centers for Disease Control and Prevention, over 38 million people in the United States are living with diabetes. Each year, approximately 1.2 million Americans are newly diagnosed. In 2021 alone, diabetes was the eighth leading cause of death, with more than 103,000 deaths directly attributed to the condition. The financial impact is enormous. The nation spends over 413 billion dollars annually on diabetes-related care and lost productivity, creating a significant economic and social burden.
Currently, Tianyang Chen is leading the development of an AI-based system that processes time-series health data from wearable devices and clinical monitors. His objective is to identify risks early, before symptoms become clinically visible. “We are building a digital health assistant that continuously monitors metrics such as heart rate and oxygen levels. When unusual patterns are detected, the system can notify the patient or their physician to enable timely intervention,” he says. This approach could help detect early signs of sleep disorders, cardiac irregularities, or metabolic changes.
Beyond individual diagnoses, Tianyang Chen’s work has broad implications for healthcare systems. Chronic conditions such as diabetes and hypertension not only endanger patient lives but also place immense pressure on hospitals and insurance providers. “If we can shift the focus from reactive treatment to early detection and prevention, using health data that people are already generating every day, we can enhance public health while significantly reducing long-term healthcare costs,” he explains.
The AI tools Tianyang Chen is building are designed to integrate seamlessly into existing medical infrastructure. Hospitals and digital platforms can adopt these technologies with minimal disruption, gaining powerful tools to support clinical decision-making. At the same time, patients benefit from increased visibility into their own health, allowing them to make more informed choices.
“What drives me is the potential to help people in real, tangible ways,” Tianyang Chen says. “Technology should serve humanity. Knowing that my work might help someone avoid a health crisis or support a doctor in making a life-saving decision is what inspires me every day.”
In a healthcare landscape increasingly shaped by data and digital tools, Tianyang Chen’s work stands out as a timely and impactful contribution. By translating complex health signals into actionable insights, he is helping to create a future where medical care is not just reactive but preventive, precise, and personal.
