Hi! I Am Harshini

Born and raised in Merrimack, New Hampshire, my journey into healthcare began at the age of six when I was diagnosed with Type 1 diabetes at the Joslin Diabetes Center, a Harvard-affiliated leader in diabetes care. At the time, Type 1 was rare, and managing it meant constant finger pricks, insulin shots, and calculations—CGMs and automated insulin delivery didn’t exist. Sitting in those hospital rooms, surrounded by doctors discussing blood sugar levels and long-term complications, I didn’t fully understand what was happening. But I did understand one thing: this was going to be my lifelong fight. My first glimpse of health technology came through Rufus, the JDRF teddy bear, who helped me learn how to take insulin shots. That bear, combined with Joslin’s world-class care, planted the first seed—one day, I would find a way to make diabetes easier to manage, or maybe even cure it.

When I moved to Visakhapatnam, India, I was struck by the stark contrast in healthcare access. While I had grown up with advanced diabetes care, I saw children struggling with limited resources and stigma. At 15, I volunteered with the Diabetic Child Society, developing digital tools for diabetes management, and later worked with Lions Club International’s cancer initiative, creating hospital information systems during COVID-19. These experiences showed me that technology wasn’t just a tool—it was a lifeline. While studying Computer Science and Engineering, I merged my love for coding and AI with my passion for healthcare innovation. Though I came from a pure tech background, I knew my purpose was in bridging medicine and technology to make healthcare smarter, more accessible, and patient-focused.

Returning to the U.S., I expanded my focus beyond diabetes and delved into AI-driven healthcare solutions. My goal was clear: to leverage machine learning and predictive analytics to transform chronic disease management, food analysis, and personalized medicine. This was also when I began working on Insulocarb, a project aimed at optimizing nutrition and metabolic health for individuals with diabetes. Recognizing that food plays a critical role in glucose management, I explored AI-powered food recognition models, automated insulin delivery optimizations, and predictive algorithms for glycemic response. The goal was to move beyond the trial-and-error approach of diabetes management, creating data-driven solutions for personalized nutrition and insulin adjustments to eliminate the guessing game and enter the startup world.

Growing up, Mayo Clinic felt larger than life. When my sister worked there as a research assistant, I heard firsthand about groundbreaking discoveries that shaped patient care. Inspired by its impact, I dreamed of contributing to research that could change lives. That opportunity came when I joined Mayo Clinic, working on AI-driven predictive models for Alzheimer’s, diabetes, and medical imaging applications.

One of my most impactful projects was studying the link between Alzheimer’s and diabetes, exploring how metabolic health affects neurological decline. I developed AI models to detect early cognitive decline in diabetic patients, reinforcing the role of predictive analytics in disease prevention. Collaborating with radiologists, I built a breast cancer imaging model to improve early detection using AI. This introduced me to OMICs—integrating genomics, proteomics, and metabolomics into AI-driven healthcare. I also worked on multi-modal disease prediction models, combining medical imaging, lab results, and genetic data to advance precision medicine. This experience expanded my focus beyond diabetes, highlighting the need for AI-driven diagnostics across multiple diseases.

At Cornell Tech, I’ve had the opportunity to explore the many pillars of health tech, extending beyond AI and machine learning into medical devices, digital therapeutics, clinical operations, and health policy. Each experience has shaped my understanding of how technology can transform healthcare from multiple angles. I’ve worked with Quest Diagnostics, GE Healthcare, and Johnson & Johnson, applying predictive analytics, diagnostics, and AI-powered solutions to improve patient outcomes. At Weill Cornell Medicine, I contributed to the Donor AI project, optimizing organ donation systems with AI, and worked on AI-driven emergency medicine services, enhancing response times and triage efficiency. Alongside this, I'm Building Juggl, a startup focused on balancing work productivity and well-being, tackling mental health challenges through AI-driven insights. Being part of these different facets of health tech has given me a holistic view of the industry, from research and development to real-world clinical applications and startup innovation. Here I am today, doing a master's in Health tech from Cornell, pushing boundaries at the intersection of AI, clinical care, and healthcare innovation—excited to see where my story takes me next..