Many life-threatening conditions go undetected until it’s too late. AI-driven diagnostics and wearable health technologies are becoming ubiquitous in detecting health issues early that enable appropriate treatment.
Sumit Raurale, our next pathbreaker, Scientist at Philips Research (Netherlands), is part of the Mother & Child Care Research Wing which is responsible for the development of AI-driven healthcare solutions specifically for mothers and infants.
Sumit talks to Shyam Krishnamurthy from The Interview Portal about a defining moment in his career when he began researching prosthetic limbs and the challenges in using them which motivated him to work on developing an AI-powered, affordable prosthetic hand that could respond to muscle signals.
For students, find a purpose beyond just a job or degree. Work on something that truly matters to you. If you have a strong “why,” you’ll always find a way forward, no matter how difficult the journey gets.
Can you tell us about your background?
I was born and raised in Amravati, a small town in Maharashtra, India. Unlike many students who excelled through rote learning, I was always more curious about how things worked rather than memorizing textbooks. From a young age, I found myself fascinated by electronics. While other kids played with toys, I spent my time taking apart radios, clocks, and even my father’s mobile phone—not because they were broken, but because I wanted to see what was inside.
My real turning point came when my school introduced computer labs and hands-on science experiments. That was when I realized that I learned best by doing, rather than just reading. This curiosity led me to make an unconventional decision—I skipped the traditional 11th and 12th grades and instead enrolled in a three-year Pre-Engineering Diploma in Electronics Engineering at a polytechnic college in Amravati. It was a risky choice, but it allowed me to directly enter the second year of a Bachelor of Engineering (BE) in Electronics Engineering. Later, I pursued a Master of Technology (MTech) in Electronic Systems & Communication, which helped me build a strong technical foundation.
What did you do for your graduation and post-graduation?
For my graduation, I completed a Bachelor of Engineering (BE) in Electronics Engineering from Shri. Ramdeo Baba College of Engineering & Management, Nagpur, Maharashtra. It gave me strong fundamentals in circuit design, embedded systems, and signal processing. During this time, I realized how powerful electronics could be in shaping the future of technology.
For my post-graduation, I pursued an MTech in Electronic Systems & Communication from Government College of Engineering, Amravati, Maharashtra. This is where I started exploring biomedical applications of electronics. My journey into biomedical technology was quite unexpected but deeply personal. One day, I met a fellow student who had lost his hand in an accident. I saw firsthand how difficult even simple tasks were for him. That experience stayed with me, and I started thinking—what if technology could help restore independence to people like him?
I began researching prosthetic limbs and quickly realized that while bionic hands existed, they were far too expensive for most people. This motivated me to work on developing an AI-powered, affordable prosthetic hand that could respond to muscle signals. That project became a defining moment in my career—it led to a patent, several research awards, and academic recognition. More importantly, it gave me a strong sense of purpose. I realized that I didn’t just want to work with technology—I wanted to create technology that could change lives.
What were some of the key influences that led you to such an offbeat and unconventional career in Biomedical Health Technology?
There were several moments in my life that shaped this career path. The first was my childhood curiosity about electronics, which naturally led me into engineering. The second was my encounter with that student who had lost his hand, which made me realize that technology had the power to make a real impact on people’s lives.
Another major influence was the realization that medical technology was extremely expensive and often out of reach for people in developing countries. I saw a huge gap—there was advanced medical technology available, but it wasn’t accessible to those who needed it the most. This drove me to explore how artificial intelligence and biomedical engineering could create affordable, high-impact solutions for healthcare.
And then, of course, there was my growing passion for artificial intelligence. I realized that AI could do things that were once considered impossible, especially in biomedical signal processing, prosthetics, and wearable health technology. The idea that AI could help a disabled person move a robotic limb just by thinking about it—that fascinated me. Over time, these influences combined and led me to take an unconventional path into biomedical technology.
How did you plan your career steps to enter this field? Or how did you transition into biomedical technology?
My career path wasn’t straightforward, but it was always driven by my passion for solving real-world problems. I started with electronics engineering, which gave me a strong technical foundation. But during my MTech, my focus shifted when I saw how electronics could be applied to healthcare. That’s when I started working on prosthetic hands and biomedical signal processing.
After completing my MTech, I knew I wanted to take my research further. I joined Visvesvaraya National Institute of Technology (VNIT), Nagpur as a Junior Research Fellow (JRF), where I worked on AI-based biomedical signal analysis for knee surgery patients. This was my first experience in medical research, and it reinforced my belief that AI could revolutionize healthcare.
At that point, I wanted to pursue a PhD in Biomedical & AI, but I had no guidance on how to apply. Coming from a small town, I had to figure everything out on my own. I applied to over 30 universities abroad—and faced rejection after rejection. It was one of the most challenging times of my life, and I often questioned whether I had made the right choice.
But I didn’t give up. Instead, I worked on improving my profile—I published more research papers, collaborated with international students, and deepened my knowledge of AI. Finally, my persistence paid off—I received two fully funded PhD offers, one from Greece (Erasmus Mundus program) and another from a top 100 university in the Queen’s University Belfast, UK. I chose the UK because their research focus on AI, robotics, and biomedical signals was a perfect match for my goals.
During my PhD, I focused on decoding muscle signals to control AI-powered prosthetic limbs. The goal was to create a bionic hand that could be controlled just by thinking about it, without complex surgeries. After my PhD, I took a Postdoctoral Research position at the Infant Research Centre, University College Cork, Ireland, where I worked on AI-driven neonatal healthcare. That experience helped me transition into the MedTech industry, where I now develop AI-driven healthcare solutions.
So in short, my journey was step by step—from electronics to biomedical research, from academia to industry—but at every stage, my focus was always on creating technology that improves lives.
How did you get your first break?
My first real break came when I started working on AI-powered prosthetic hands during my MTech. It wasn’t just an academic project—it had real-world implications. When my prototype worked, and I saw the potential impact it could have, I knew I was onto something meaningful. This project led to a patent, multiple awards, and research recognition, which helped open doors for me.
But my career truly took off when I got into PhD research in the UK. It was a major breakthrough because it gave me the opportunity to work on cutting-edge AI-driven prosthetics. The recognition I gained from publishing research in top international journals made it easier to establish myself in the field.
After my PhD, transitioning to industry was challenging because most MedTech companies preferred candidates with prior industry experience. That’s when I decided to take a Postdoctoral Researcher position at the Infant Research Centre in Ireland, where I worked on AI-based neonatal healthcare. One of the most rewarding moments was when our AI system detected an early-stage neurological disorder in a newborn, allowing doctors to intervene in time. That moment made me realize the true power of technology in saving lives.
This experience ultimately helped me transition into the MedTech industry. I first joined IMEC, Netherlands, where I worked on AI-powered healthcare devices, and later moved to Philips Research, Netherlands, where I now develop AI-driven solutions for maternal and infant healthcare.
So, if I had to define my “first break,” it wasn’t one moment—it was a series of small victories, fuelled by persistence, passion, and the desire to create meaningful change.
What were some of the challenges you faced? How did you address them?
There were many challenges throughout my journey, both academic and personal. One of the biggest challenges was breaking into biomedical research. My background was in electronics engineering, so when I became interested in biomedical technology, I had to teach myself a lot about biomedical signals, AI, and medical applications. There was no clear roadmap, and I had to navigate this path on my own.
Another major challenge was getting into a PhD program abroad. Coming from a small town, I had no mentors or seniors who had applied to universities overseas, so I had to figure out everything—from writing research proposals to securing scholarships—by myself. I applied to over 30 universities and faced multiple rejections. It was a mentally exhausting phase, and there were moments when I doubted myself. But instead of giving up, I focused on strengthening my profile. I published more research papers, collaborated on international projects, and developed expertise in AI. Eventually, my persistence paid off, and I received fully funded PhD offers.
The PhD itself was another challenge. My research involved decoding muscle signals using AI for prosthetic limbs, but working with biomedical signals is extremely complex. Unlike structured AI datasets, human muscle signals vary from person to person, making it difficult to create a universal AI model. There were times when my experiments failed for months, and I had to go back to the drawing board repeatedly. But I kept pushing forward, collaborating with neuroscientists, clinicians, and engineers to refine my approach.
Another challenge was transitioning from academia to industry. Many companies preferred candidates with industry experience rather than a purely academic background. Despite my strong research experience, I faced multiple job rejections. To bridge this gap, I took a Postdoctoral Researcher position at the Infant Research Centre in Ireland, which allowed me to apply my AI expertise in clinical settings. This helped me gain industry-relevant skills, which eventually led to my current role in MedTech research.
Throughout my journey, the key to overcoming challenges was persistence, adaptability, and continuous learning. Whenever I faced setbacks, I focused on improving my skills and finding new opportunities.
Where do you work now?
I currently work as a Scientist at Philips Research, Netherlands, in the Mother & Child Care Research Wing. My work focuses on developing AI-driven healthcare solutions specifically for mothers and infants. Philips is a global leader in healthcare innovation, and my role allows me to work on cutting-edge technologies that can improve maternal and neonatal health outcomes.
Before joining Philips, I worked as a Research Scientist at IMEC (OnePlanet Research Centre, Netherlands), where I developed AI-powered digital health solutions, such as smart health patches and AI-driven diagnostic tools. These experiences have given me the opportunity to contribute to real-world medical innovations that can make healthcare more efficient and accessible.
What problems do you solve?
The main problems I work on are related to maternal and infant healthcare. One of the biggest challenges in neonatal care is that early signs of health problems in newborns are often missed. Many life-threatening conditions, like brain abnormalities or respiratory issues, can go undetected until it’s too late. My work focuses on using AI and biomedical signal processing to detect these problems early, so that doctors can intervene in time and potentially save lives.
For example, one of the projects I worked on involved developing an AI system that analyzes brain signals from newborns in Neonatal Intensive Care Units (NICUs). During testing, our AI detected an early-stage neurological disorder in a baby—something that traditional methods had missed. Because of this early detection, doctors were able to treat the baby before the condition worsened. That was a deeply fulfilling moment because it showed the real impact of AI in saving lives.
At Philips, I am also working on AI-powered monitoring solutions for mothers during pregnancy and childbirth. Many pregnancy-related complications can be prevented if we can track vital health indicators in real time. My goal is to make maternal and infant healthcare more proactive, personalized, and accessible, especially for underserved communities.
What skills are needed for this role? How did you acquire them?
This role requires a combination of technical, medical, and problem-solving skills. One of the most important skills is AI and machine learning, especially in biomedical signal processing. Since I came from an electronics background, I had to teach myself AI and data science through online courses, hands-on projects, and research collaborations.
Another critical skill is biomedical signal analysis—understanding how to work with complex data like electromyography (EMG), electroencephalography (EEG), and heart rate signals. I developed this expertise during my PhD, where I worked on decoding muscle signals for AI-powered prosthetics.
Beyond technical skills, this role also requires interdisciplinary collaboration. In healthcare innovation, you have to work closely with doctors, engineers, policymakers, and patients. My experiences in academia and industry helped me develop strong communication and teamwork skills, which are crucial for translating research into real-world medical applications.
Additionally, problem-solving and resilience are essential. In biomedical AI, things rarely work on the first try. Experiments fail, data is messy, and models don’t always behave as expected. The key is to stay patient, keep refining your approach, and never stop learning.
What’s a typical day like?
Every day is different, but it usually involves a mix of research, development, and collaboration. In the morning, I often start by analyzing biomedical data—this could be neonatal brain signals, maternal health monitoring data, or wearable sensor outputs. I work on developing and testing AI algorithms to detect health patterns that doctors might miss.
A large part of my day is spent collaborating with doctors and engineers. Since my work involves both medical research and AI development, I often have meetings with clinicians, data scientists, and hardware engineers to discuss how we can refine our models and integrate them into real-world healthcare devices.
I also spend time reading scientific literature to stay updated on the latest advancements in biomedical AI. Since the field is evolving rapidly, continuous learning is essential.
In the afternoon, I typically focus on coding, debugging AI models, and running experiments. Some days involve working with real patient data, testing our algorithms on medical datasets, and ensuring our AI models are both accurate and clinically useful.
Occasionally, I also get to present my research at conferences, attend innovation workshops, or work on writing research papers. It’s exciting because it allows me to share my findings with the global scientific community and get feedback from experts.
While the work is challenging, it’s also incredibly rewarding. Every experiment, every dataset, and every breakthrough brings us one step closer to creating technology that can save lives. That’s what keeps me motivated every day.
What do you love about this job?
What I love most about this job is the real-world impact it has on people’s lives. Every day, I work on cutting-edge healthcare innovations that can potentially save lives, improve patient care, and make medical technology more accessible. Knowing that my work contributes to helping newborns, mothers, and patients receive better medical treatment is incredibly fulfilling.
Another thing I love is the intersection of technology and healthcare. My work combines artificial intelligence, biomedical engineering, and medical research, which keeps it exciting and intellectually stimulating. Every day brings a new challenge, a new problem to solve, and an opportunity to push the boundaries of what technology can do for healthcare.
I also enjoy working in an interdisciplinary environment. In this role, I get to collaborate with doctors, engineers, AI specialists, and industry leaders. It’s fascinating to bring together different perspectives to develop solutions that are both scientifically advanced and practically useful in real-world medical settings.
How does your work benefit society?
The biggest way my work benefits society is by making healthcare smarter, more efficient, and more accessible. Many life-threatening conditions in newborns and pregnant mothers go undetected until it’s too late. By using AI-driven diagnostics and wearable health technology, we can detect health issues early and provide doctors with the insights they need to intervene in time.
For example, many hospitals, especially in developing countries, lack advanced neonatal care units. My research in AI-driven neonatal monitoring helps identify potential health risks in newborns without requiring expensive medical tests. This can be a game-changer for healthcare in rural areas, where access to specialized doctors is limited.
Beyond maternal and infant healthcare, my work also contributes to prosthetics and rehabilitation. My PhD research focused on AI-powered prosthetic hands that respond to muscle signals, which can help amputees regain their independence. These kinds of innovations have the potential to improve the quality of life for millions of peopleworldwide.
Ultimately, I see technology as a tool that should serve humanity. My goal is to use AI and biomedical engineering to create solutions that are affordable, effective, and accessible to everyone—not just a privileged few.
Tell us an example of a specific memorable work you did that is very close to you.
One of the most memorable moments in my career happened during my postdoctoral research at the Infant Research Centre in Ireland. Our team was working on an AI system that analyzed brain signals in newborns to detect early signs of neurological disorders.
One day, while testing the system in a hospital’s Neonatal Intensive Care Unit (NICU), our AI model detected an unusual abnormality in a newborn’s brain activity. At first, we thought it might be a false alarm, but after validating the data, we realized that the system had correctly identified an early-stage neurological disorder that had gone unnoticed by traditional methods.
Thanks to this early detection, the doctors were able to intervene immediately and start treatment before the condition worsened. That baby survived, and knowing that my work directly contributed to saving a life was an unforgettable moment.
This experience reaffirmed my belief in the power of AI-driven healthcare. It was a moment that reminded me why I chose this field—because technology, when used right, has the power to save lives and bring hope to families.
What advice would you give to students based on your experience?
If I had to give one piece of advice to students, it would be this: Stay curious and never stop learning. The world of technology is evolving at an incredible pace, and the best way to stay ahead is to keep exploring new skills, new fields, and new opportunities.
Failures and rejections are part of the journey. I faced 30+ rejections before I got my fully funded PhD. Every rejection taught me something new and pushed me to improve. So, don’t be afraid of failure—it’s just a stepping stone to success.
Also, don’t limit yourself to just one field. The most exciting innovations happen at the intersection of different disciplines. I started as an electronics engineer, then moved into AI and biomedical research, and now I work in healthcare innovation. Be open to learning from different domains, because that’s where real breakthroughs happen.
Lastly, find a purpose beyond just a job or degree. Work on something that truly matters to you. If you have a strong “why,” you’ll always find a way forward, no matter how difficult the journey gets.
What are your future plans?
Looking ahead, my goal is to continue pushing the boundaries of AI-driven healthcare innovation. I want to work on developing affordable, AI-powered healthcare solutions that can be scaled globally, especially in underserved regions.
I am particularly interested in AI-driven wearable health monitoring systems. Imagine a future where a simple wearable device could track your health in real time, predict potential health issues, and alert doctors before a problem even occurs. That’s the kind of technology I want to develop—one that makes healthcare predictive, rather than reactive.
I also plan to mentor and support young researchers and students who want to enter the field of biomedical AI and healthcare innovation. I know how challenging it can be to navigate this path, especially without proper guidance. I want to help the next generation of scientists and engineers find their way and contribute to meaningful innovations.
Ultimately, my vision is to make advanced healthcare technology accessible to everyone, not just a privileged few. Because at the end of the day, technology should serve humanity—and I want to be at the forefront of that transformation.