Q&A with Saanvi Mehra (M&T’27)

Saanvi Mehra (M&T’27) is in her first year as an M&T and was recently awarded the Rise Global Scholarship Award for her work on Down Syndrome detection. We recently sat down with her talk about how her first year of college is going, her work that contributed to her award recognition, and how her time in the M&TSI program as a high school student served as the inspiration for her project.

Q: How did you decide to apply for the M&T Program?

SM: I’ve always enjoyed working at the intersection of technology and medical science, as both areas have tremendous potential for societal impact. I’m most excited to see what I build or code being applied in real life. To do that, I believe I need management, entrepreneurship, and finance skills. While I was still in high school, I attended M&TSI, which is a three-week summer program for college credit, and I was immediately hooked. The product-prototyping style design of the classes, venture ideation, and creation was an exact translation of my academic interests. It gave me a taste of what being an M&T student was like and cemented my belief in the fact that M&T was the way to go for me. M&T will equip me with the ability to do exactly what I want – to not just learn theoretical computer science, but also to implement and it work in real life, scale it to a venture, and see it impact people.

  1. What is the Rise Global Award?

SM: The Rise Global Award is an annual, global contest that involves developing and incubating a social welfare project that impacts your community positively. I decide to apply to tap into a network of brilliant young leaders from across the world. This year, out of more than 8,000 applicants, Rise chose 100 winners to be inducted into its network, receive financial backing from the Eric Schmidt and Rhodes Foundation, be invited to a fully funded leadership retreat in Oxford, and receive a scholarship for higher education and entrepreneurial ventures.

Q: Why were you chosen as a recipient of the 2023 award?

SM: For my Rise project, I chose to work on Down Syndrome detection using machine learning. I helped develop a mobile app; obtained approval from the ethics committee; undertook clinical research and validation with leading geneticists and pediatricians in India; published my research on ethnicity-specific results for Down Syndrome in an acclaimed peer-reviewed medical journal; presented and won awards at various national and international medical conferences; established a nonprofit foundation and trust to reimburse diagnostic testing costs for children with Down Syndrome; worked with the Indian government to implement the app across India; and even patented a method and device to enhance model accuracy further. I also won the National Google Code-to-Learn Contest and the Technovation (India) challenge for this project.

I really grew as a person as result of this work. This has been an exciting journey and I’ve learned a lot and acquired new skills. The experience of interacting with so many groups of people – the children with Down Syndrome, doctors, government officials – it was surreal.

Q: Why did you choose to focus on Down Syndrome for your project?

SM: I chose to focus on Down Syndrome due to a personal experience that impacted my family during my mother’s second pregnancy. In India, the prevalence of Down Syndrome is estimated at roughly one out of every thousand children, leading to more than 30,000 children born annually with the genetic disorder. Though in the developed world, children with Down Syndrome mostly survive, in India, the disease is associated with a high mortality rate, with a survival rate of barely 44%. The primary reason for this high mortality in India is non-diagnosis/late diagnosis due to a lack of access to medical and diagnostic facilities and/or unaffordability of medical facilities.

The primary of markers of a Down Syndrome baby can be established before birth through an ultrasound scan, but that is unaffordable for more than 90% of Indian parents. A simple, inexpensive, conclusive, non-invasive test for Down Syndrome, followed by timely treatment, can save tens of thousands of lives in India and other developing countries.

Machine learning models can help in not just reducing deaths caused by medical conditions in kids with Down Syndrome but also enable these kids with a better lifestyle by early detection. Down syndrome is one of the most common genetic disorders caused by chromosome abnormalities in humans. There have been studies and investigations done for Down Syndrome detection by studying the facial features associated with this disorder. Some common characteristics present in people with the disorder include distinctive facial features, such as slanting eyes, small chin, round face, flat nasal bridge, Brushfield spots in the iris, abnormal outer ears, and flattened nose. Hence, using machine learning techniques can facilitate the recognition of facial dysmorphic features associated with genetic syndromes. A few tools have been used for extracting facial points and computing measurements from images and through machine learning such structural malformations can be automatically identified.

My application is based on analyzing images of newborn babies to check for Down’s Syndrome. Parents can click photos of their newborn baby and upload to an app that can, with a high degree of accuracy, advise them regarding chances of affliction with Down Syndrome, and need to seek specialized healthcare.

This method has the following advantages:

  • Universal access/inexpensive – even the most disadvantaged sections of Indian society have access to mobile phones and the Internet
  • Easy to use – clicking and uploading a photograph is a common skill today
  • Quick results – rather than waiting for weeks, a preliminary diagnosis is handed out
  • immediately
  • Timely treatment – within a day of being born, a child can be recommended for specialized healthcare, significantly improving probability of survival
  • Second opinion – for parents who already have access to medical facilities, this app can provide a secondary confirmation for physicians’ advice
  • Resource optimization – rather than universal testing, resources can be deployed to confirm the diagnosis of and treat high risk children

Q: How has your time in the M&T Program inspired you to develop this project?

SM: My time in M&T – and more specifically M&TSI – changed the way I approach and tackle problems. This is something I wrote in my M&T application essay as well – but I truly believe that M&T equips you with the ability to not just envision the big picture, but also play an active role in painting it. Any successful venture requires an ideal blend of both management and technology. Having that principle and analytical thinking ability guide me throughout my projects thus far, has been an amazing experience.

Q: Do you have a piece of advice for future M&T students?

SM: Through the college application process, you will learn a lot about yourself, you’ll make big decisions, and you’ll grow as a person. It’s important to remember that you will end up where you are supposed to end up. You have to keep putting in the work, remember what it is you want, and ensure you remain authentic. Everything will work out – have faith in your ability to represent your identity and know who you are.