At first glance, Mansi Sood is the epitome of an MIT researcher—deeply engaged in mathematical modeling, computational methods, and decision-making frameworks. But as soon as she starts talking, her passion for mentorship, teaching, and even watercolor painting emerges just as strongly as her love for data.
Mansi, a postdoctoral researcher at MIT’s Laboratory for Information and Decision Systems (LIDS) and a Schmidt Science Fellow, welcomed me warmly. Wearing a pink button-up sweater and hexagon glasses, she was animated, expressive, and full of energy. Her words carried the confidence of someone who had traveled a long way—both geographically and intellectually—to reach this point in her career.
I spoke to several of them. It's worth listening to what they have to say.
Mansi’s academic path started in India, where she completed her undergraduate and master's degrees at the Indian Institute of Technology (IIT).
"I was always drawn to math-heavy problems, particularly in electrical engineering, signal processing, and probability," she explained.
But her focus quickly shifted toward network models—mathematical frameworks that help analyze complex systems like social media platforms, biological networks, or even economic structures.
For her PhD, she moved to the U.S. to Carnegie Mellon University (CMU), where she specialized in applying network theory to real-world problems.
"Networks are everywhere—whether it’s people interacting on social media or cells responding to a medical treatment," she said enthusiastically. "My PhD focused on understanding these interactions mathematically and optimizing decision-making processes."
It was during this time that she applied for the Schmidt Science Fellowship, a prestigious postdoctoral program that allows researchers to work anywhere in the world.
"When I got the fellowship, I had the freedom to choose where I wanted to go next. I had considered a few schools, but when I visited MIT and met with Professor Devavrat Shah and the team at LIDS, it felt like the right fit."
Now, at MIT, her work continues to explore mathematical models for decision-making, using structured data to guide choices in biological research and social platforms.
One of the biggest influences in Mansi’s career has been her mentors and professors—a fact she credits as the main reason she remains in academia.
"I had so many incredible mentors, especially women in STEM, who encouraged me at every stage," she reflected. "I wouldn’t be here without them."
That influence has driven her love for teaching and mentorship.
"One of the best parts of academia is being able to guide younger students. It’s not just about technical knowledge—it’s about encouragement, confidence, and learning how to navigate research."
During her time at CMU, she actively participated in teaching programs, designed new curricula, and even mentored undergraduate and master’s students.
"It’s amazing to see students go from being unsure of themselves to presenting real research," she said, beaming.
Even at MIT, she continues to attend lectures and engage in mentoring students, even though she’s still settling into her new role.
Moving from India to the U.S. was not just an academic shift—it was a personal one.
"The hardest part was being far from family. In India, everything was structured—meals, schedules, community support. Here, suddenly, I had to manage everything on my own."
The physical distance—a 25-hour flight from home—was daunting. But the freedom to explore diverse fields at CMU helped her adjust.
"One thing I loved about CMU was the ability to take classes across disciplines," she said. "I was in the business school one semester, then taking design courses, then back in math. That kind of academic freedom really shaped my approach to research."
Now at MIT, she finds herself in another uniquely interdisciplinary environment.
"MIT has so many departments—statistics, economics, management, applied math—all working on connected problems. The density of research here is incredible."
Despite her love for math, Mansi is not content with theory alone.
"I like math that has a real-world impact," she said. "If I see a problem where existing computational methods aren’t enough, I want to build new tools to solve it."
Her postdoctoral work is currently focused on biological systems, particularly helping scientists make better decisions about medical experiments.
"In biology, you’re dealing with massive amounts of structured data—genes, cells, treatments. Scientists have to run costly experiments, and they need to know which ones will give them the most useful information."
By applying statistical modeling and decision science, her work helps optimize these experiments, making research more efficient and cost-effective.
"It’s about using computation to make better choices in high-stakes environments—whether that’s in science, policy, or even social media moderation."
One of the most unexpected aspects of Mansi’s life is her love for watercolor painting.
"I’ve been painting for as long as I can remember," she said, smiling. "Even during my PhD, I would teach art classes and participate in exhibitions."
For her, art is not just a hobby—it’s a way to process emotions, express ideas, and even improve her research.
"Art teaches you how to communicate visually. That skill is incredibly useful in research—especially when you’re dealing with abstract mathematical models."
She has also started exploring ways to bridge the gap between artists and scientists.
"Artists working with traditional crafts have generational knowledge about materials, sustainability, and processes. Scientists have data and modern techniques. If we connect those two worlds, we could create innovative, sustainable solutions."
She recently completed an artist residency focused on connecting science and art and hopes to build more interdisciplinary collaborations in the future.
As we wrapped up, I asked Mansi what advice she would give to students exploring research careers.
Mansi’s journey is a testament to the power of interdisciplinary learning, resilience, and the importance of mentorship.
She is a mathematician, a researcher, an artist, a teacher—and refuses to be confined to just one identity.
As I left MIT’s LIDS lab, I couldn’t help but feel inspired by her approach—one that values both analytical rigor and creative expression, both structured research and free exploration.
In academia and beyond, Mansi Sood is proving that science and art, structure and creativity, can thrive together.
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