For Connor Hill, winner of the top award at the 2026 , a program of �鶹����, that question centered on a class of geometric objects known as noble polyhedra. These shapes are defined by symmetry and structure and rooted in mathematical traditions that trace back to Plato and the early study of geometry. What began as an open-ended geometric question ultimately led to a complete classification of noble polyhedra, identifying two infinite families along with 146 isolated examples.

At first glance, this kind of research may feel far removed from the work of developing new medicines. To explore how abstract mathematics connects to real-world discovery, Connor recently spoke with, Executive Director, Development Innovation at Regeneron who is a physician-scientist working at the intersection of biology and medicine. As Connor looks ahead to attending MIT this fall, an opportunity supported partly through his winnings at Regeneron �鶹���� this year, their conversation brought a clearer connection into focus.

What links a centuries-old geometry problem to modern medicine is not the shape itself, but the mindset behind it. In both fields, researchers must turn complexity into something finite and solvable. That same approach underpins discovery in biology, medicine and beyond. Dr. Wei and Connor discuss how abstract mathematical ideas can drive real-world breakthroughs, and why curiosity-driven research continues to unlock what’s possible.

Q&A: Where Foundational Math Meets Clinical Science

Dr. Wei: Connor, what first sparked your interest in mathematics, and how did this research take shape?

Connor: I’ve been interested in math for as long as I can remember. A big part of that is patterns—once you start noticing them, you realize they show up everywhere. Math gives you a way to understand those patterns more deeply.

My Regeneron Science Talent Search project didn’t start as one big breakthrough. I was part of an online community exploring geometry, and I came across this question about noble polyhedra. At first, I thought I might find a few new examples, but over time, step by step, it grew into a full proof.

That’s how math usually works. It builds on what others have done, or what Newton described as “standing on the shoulders of giants.”

Dr. Wei: For those less familiar, what are noble polyhedra? Why have mathematicians been interested in them for so long?

Connor: They’re geometric shapes defined by symmetry. All the faces are identical, and all the vertices are identical.  A cube is a simple example since every face, and every corner is the same. Noble polyhedra extend that idea, but they relax some of the stricter rules found in classical shapes like the Platonic solids.

What makes them interesting is this question of how much can you loosen the constraints while still preserving the structure.

Dr. Wei: Your work introduces the powerful idea of turning an “infinite” problem into a finite one. What does that mean in practice?

Connor: In geometry, there are often many possibilities. For example, there are infinitely many ways to arrange points in space. The challenge is figuring out how to reduce that to something manageable. I connected the geometric problem to algebra—specifically, to polynomials. By translating the problem into a different mathematical framework, I could narrow it down to a finite set that could actually be solved.

Dr. Wei, that idea of reduction feels central to scientific discovery. How do you see it show up in your work?

Dr. Wei: In biology and medicine, we’re constantly working with incredibly complex systems such as how proteins fold, how diseases progress, or how treatments interact with the body.

The challenge is making those systems understandable. When you can reduce complexity in a meaningful way, you move from approximation to something more precise. That’s where mathematics becomes essential. It gives us a way to focus on what actually matters.

Connor, you’ve said the methods behind your work may be more important than the result itself. Why is that?

Connor: A lot of mathematics ends up being useful in ways you can’t predict at the time. For this project, the key idea is connecting different areas of math like discrete geometry and algebraic geometry and using that connection to solve problems more effectively.

That kind of approach could apply to many different problems, anywhere you have structure, symmetry, or a large number of possibilities that need to be narrowed down.

Dr. Wei, can you share an example of how that kind of thinking applies to biomedical science?

Dr. Wei: One example is protein structure. Proteins can take on an enormous number of possible configurations, but only a small number are stable or biologically meaningful. The challenge is figuring out which ones matter.

Mathematics helps us reduce that complexity. Instead of trying everything, we can focus on a much smaller set of possibilities. That’s critical in areas like drug discovery.

Connor: Your conversation also touched on the idea of moving from approximation to exact solutions. Why does that matter?

Dr. Wei: In many areas of science today, especially with machine learning, we rely on approximation through models that can be very good, but never exact. Mathematics gives us another pathway. When you can describe a system precisely, you can sometimes solve it directly rather than estimate it.

That shift—from approximation to deeper understanding—is where breakthroughs can happen.

How do you think about the role of mathematics in solving larger challenges?

Connor: Math is the language that makes scientific ideas usable.

Science gives us the concepts, but math allows us to formalize them and apply them. When we’re solving big problems, the key is breaking them into smaller pieces that math can address.

Often, breakthroughs happen when someone connects ideas across disciplines.

Dr. Wei: What advice would you give to future scientists?

Connor: Follow what you’re genuinely interested in. The most meaningful work comes from curiosity, not outcomes. Find people who share your interests and focus on small contributions—they build into something bigger over time.

Why Foundational Math Matters

Connor Hill’s work reflects a broader truth: scientific progress depends on simplifying complexity and connecting disciplines.

Interested in competing? Learn more about applying to the Regeneron Science Talent Search:

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This past month, Maya Ajmera, President and CEO of �鶹���� and Executive Publisher of Science News, spoke with Shantanu Gaur (ISEF 2003, 2004), co-founder and CEO of , a company developing non-surgical weight-loss technology to address obesity.

Maya began the conversation by asking Shantanu how his experience at ISEF has continued to shape his career more than 20 years later.

“ISEF was really the first time where I saw what exceptional science and engineering look like,” Shantanu said.

Shantanu’s two ISEF projects were both biomedical research. In one project, he studied a rare genetic mutation in the Afro-Caribbean population of Trinidad and Tobago that is associated with prostate cancer, with the goal of developing a screening tool to identify individuals at greater risk for the disease. For his senior-year project, he investigated a protein involved in the retinal development of chick embryos. While the results weren’t as positive as Shantanu hoped, he says the work taught him a great deal.

Years later, while attending medical school, a class project evolved into what would become Allurion. “We got some traction from people around us—faculty members who said, ‘This is a really good idea. You should pursue it,’” Shantanu said. Maya asked what came next since Shantanu was reaching a pivotal point in his career where he could pursue this business idea or continue the path of being a practicing doctor. After a conversation with his father, he gained some clarity.

“He sat me down and told me I have two choices,” Shantanu says. “You can become a doctor and that’ll be a very fulfilling career, a very noble career. Or if you go out and build a business around this idea, you have the potential to touch the lives of millions of people.”

He left a lasting question to Shantanu: “Do you want to maximize your life for impact or not?”

“At the end of the day, that’s what really drove me toward Allurion,” Shantanu said. “I felt like this was an opportunity for me to work on a problem that’s really pervasive and really important for the world.”

“Obesity is the health issue of our generation,” Shantanu says. “When you have a chronic disease like obesity, it affects nearly every aspect of your health. A lot of what we’re seeing now in obesity has already happened with things like heart disease and cardiovascular disease; it used to be that if you had a heart attack, you needed surgery.”

Allurion is a non-surgical, less invasive medical device patients use for four months to feel fuller. Like bariatric surgery, the device is a biodegradable polymer balloon patients take in a capsule form and rests in the stomach until it’s naturally passed by the patient after four months.

“It’s almost like we’re implanting a meal inside the stomach that stays there,” Shantanu says. “You feel hungry, you eat a meal, and you feel full very fast. We train patients to live life on smaller portions. We don’t kill or suppress the drive to eat. That’s something medications do. We’re really focused on the stomach and helping you feel full.”

While GLP-1s could be deemed as competition for Allurion, Shantanu says it is not.

“We’re certainly complementary,” Shantanu says. “GLP-1s are quite effective and safe. When the patient remains on these medications, they will keep the weight off. One issue people are having, though, is that they stop taking these medications.” Shantanu says Allurion can be an alternative, especially if a patient doesn’t want to be on a medication their entire life.

and is now approved in over 80 countries. Looking ahead, Shantanu envisions future versions of the device that could remain in the stomach for up to 12 months or deliver medications such as vitamins or GLP-1 therapies.

“There are going to be all sorts of permutations and combinations that people are going to be using to treat obesity,” Shantanu says. “I really want Allurion to be at the forefront of that.”

Watch the full Tech Series conversation .

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The fulfilled President John F. Kennedy’s goal of landing humans on the moon and returning them safely to Earth. Neil Armstrong and Buzz Aldrin became the first people to walk on the lunar surface while Michael Collins remained in lunar orbit aboard the command module. While on the moon, the astronauts conducted scientific experiments, collected lunar samples to bring back to Earth and photographed the moon’s terrain.

As we reflect on this historic achievement, International Moon Day is also an opportunity to consider how much scientific progress has been made over the past 57 years, from returning astronauts to the moon to preparing for future space exploration. Science Talent Search alum (1999), , a former SpaceX flight surgeon, is currently aboard the (ISS) on his first spaceflight. During his eight-month mission, he will conduct scientific research and technology demonstrations aimed at advancing human space exploration and benefiting life on Earth. Menon will also perform ultrasound using augmented reality and artificial intelligence methods that could eliminate the need for medical support from Earth on future space missions, such as to the moon and Mars.

Take a dive into research projects from this year’s Regeneron International Science & Engineering Fair finalists that are inspired by the moon, spanning categories from Materials Science and Engineering to Astronomy and Software Design.

Springville High School, Springville, Utah
Age 16, junior

Since future space exploration may one day involve human beings inhabiting the moon, manufacturing materials from the moon would be beneficial. Clara researched the possibility of using moon dust or basaltic volcanic ash (BVA) for her Regeneron ISEF project. Using a 3D printer with a BVA-loaded polymer, Clara tested how materials withstood the wide range of lunar temperatures. The tests showed that the 3D-printed materials couldn’t handle the moon’s extreme daytime heat. The materials softened at high temperatures, and the moon dust prints became brittle and crumbly when heated in conditions like those on the moon. These results seek to aid our knowledge for future lunar missions and potential long-term habitation.

Oviedo High School, Oviedo, Florida
Age 15, sophomore

In his Regeneron ISEF project, Ankan developed a compact robot with a flexible frame that can absorb impacts, change shape, and move through tight spaces. He designed the robot so multiple units could eventually work together as a swarm to explore challenging environments. The autonomous mobile robot successfully traversed across a variety of surfaces, including simulated lunar soil (known as regolith), concrete and pavement. It is now being tested in extremely hot and cold temperatures, as well as in a chamber filled with simulated lunar soil, to see how well it could perform in conditions like those on the Moon.

,
Spruce Creek High School, Port Orange, Florida
Age 17, junior

For her Regeneron ISEF project, Reagan used a trained machine learning model and physical models to identify lunar lava flows. This research could be used by scientists to find the most promising landing sites on the moon and learn more about its geological history. Using images of the lunar surface captured by NASA’s Lunar Reconnaissance Orbiter, Reagan identified surface features with more than 94% accuracy. She also learned that thicker lava flows took longer to cool than thinner ones, providing new insights into how the moon’s surface formed.

Colegio Rosa-Bell, Guaynabo, Puerto Rico
Age 15, freshman

Eduardo’s research introduces RegoCrete-BGX, a fiber-reinforced, multi-aggregate concrete made with lunar regolith, basaltic rock and waste glass for future space construction. If we plan on landing on the moon, Eduardo’s research explores how structures could be built using materials available on the lunar surface. He created concrete blocks using different combinations of these materials and tested how much weight they could withstand after curing for one and two weeks. His findings suggest that simulated lunar soil can be combined with chosen Earth-based materials to produce concrete with strength comparable to traditional concrete. This could help limit the amount of building material that future space missions may need to transport from Earth.

Dr. Pedro Albizu Campus, Ponce, Puerto Rico
Age 17, senior

Jacob researched how farmers can adapt to climate change by using the moon as a point of reference. As climate change makes weather more unpredictable, many farmers can no longer rely on traditional planting calendars. Using his software development system, AgroLunas, Jacob combined modern weather data with insights from lunar cycles to help farmers make more informed planting decisions. Delivered through an interactive platform, the system helps farmers combine ancestral knowledge with modern atmospheric

For more from the fair, watch the !

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Stefan did not set out to write a memoir. In 2020, during the height of the pandemic, he welcomed his second child and, just days later, lost his mother. Unable to travel and forced to say goodbye over FaceTime, he began writing as a way to preserve his memories. Those pages weren’t structured or polished, Stefan explained. They were fragments of recollection. But when he later shaped them into chapters, something shifted. Reading his own story from a distance allowed him to feel compassion for his younger self. For the first time, he found himself rooting for that isolated child on the page.

That realization gave him a purpose: to give that child the voice and witness he never had. Stefan described being homeschooled for four and a half years in near-total isolation with a mother who used her silence as a punishment and had extremely nontraditional teaching methods.

Yet amid that isolation, science became an unexpected path to connection. One of the brightest spots in the memoir came during Stefan’s high school years when he participated in science competitions, including ISEF. He shared, “It seemed like such a fluke that as a freshman I won the regional science fair and was given a gift of time away from a high school experience that had been a catastrophic year.” For the first time, Stefan had found “his people”: curious, driven students who shared his passions.

During his conversation with Science News Publisher Michael Voss, Stefan acknowledged that his nuanced portrayal of his mother was central to his memoir. Rather than casting her as a villain, he chose to present her with full emotional complexity—both loving and harmful, protective and imprisoning. Stefan shared that he’s heard back from readers who expressed a great deal of anger on his behalf, but that was never his intention. “I think at the heart of this book is a profound ambivalence. And it felt good to me to arrive, almost healing, to make peace with that ambivalence,” he said.

Sharing the manuscript with his family was the most frightening step. For years, his family had unspoken rules about not discussing his mother critically. But when his father finally read the book, his response was unexpectedly tender. Instead of anger, he offered understanding, and it opened the door to deeper conversations and a closer relationship.

Returning to school as a teenager was initially very difficult for Stefan. He was academically behind and socially disconnected. Teachers who believed in him and led him to science fair helped him regain confidence and opened doors to opportunity. He now sees them as pivotal figures; people who quietly pulled him into a larger world when he needed it most.

His ISEF and �鶹���� experiences planted the seeds for both his scientific and creative pursuits. Even though Stefan ultimately chose writing over lab research, he credits science with shaping his mindset. The patience, rigor and tolerance for failure required in research, he said, are identical to what it takes to write a novel. “Writing a book is like running an experiment,” he explained. “You test a hypothesis. Sometimes you spend years discovering you were wrong. Then you start again.”

Stefan’s path has been anything but linear. After working in research labs at institutions like Yale University, he gradually realized he was sneaking off to write fiction instead of preparing for graduate school applications. Eventually, he committed fully to writing and sold his first novel in his early twenties. Today, in addition to publishing books, he co-owns a community roller skating rink in upstate New York, a joyful, social space that feels like a small corrective to the isolation of his childhood.

When asked what advice he’d give students navigating uncertain or nonlinear paths, Stefan didn’t hesitate: persistence. Both science and writing demand faith through failure. “Relentless persistence is everything.”

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What are your favorite memories from ISEF?

One of the things I really enjoyed about ISEF was talking to the judges about my work. It was great to talk to people who knew something about what I was doing, were enthusiastic and wanted to hear more.

Was your ISEF project a project in mathematics?

Yes. I participated in a summer program called the Research Science Institute (RSI) at MIT, which is where I began my research. After RSI concluded, my RSI mentor Satomi Okazaki connected me to Doug Jungreis, who was then a postdoc at UCLA near my home in Los Angeles, and he continued to mentor me. This enabled me to continue working on the research that became my ISEF project.

How would you describe the central ideas that drive your research?

My research is in algebraic combinatorics. Algebra is the study of things like polynomials, and combinatorics is the study of finite or discrete structures; it often involves counting. As an example, if you give a combinatorialist a cube, they will probably observe that it has six two-dimensional faces, 12 one-dimensional edges, and eight zero-dimensional vertices.

In my Ph.D. thesis, I studied a mathematical object called the positive Grassmannian. There are actually infinitely many positive Grassmannians, and they can have arbitrarily high dimensions, but just like a cube, each one can be decomposed into pieces of different dimensions. My first graduate school theorem was an explicit formula for the number of pieces of each dimension in each positive Grassmannian.

Your work lies at the intersection of algebra, combinatorics and geometry. What happens when those fields collide?

One thing that is useful about being at the intersection of several mathematical fields is that you’ve got a larger set of tools to draw from and a larger set of problems. My work has had unexpected connections to fields even outside of math. A year after I wrote my first paper on the positive Grassmannian, another mathematician named Sylvie Corteel wrote a paper proving that my formulas enumerating could be interpreted as probabilities explaining what happens in a model called the asymmetric simple exclusion process. This model was introduced by biologists to study translation in protein synthesis, and it has also been used as a model for traffic on a one-way street.

At that point I had never heard of the asymmetric simple exclusion process, but all of a sudden I was learning that my polynomials were computing probabilities related to traffic flow and protein synthesis. It was extremely intriguing.

Congratulations on being named a 2025 MacArthur Fellow. How did you feel when you learned you received the award? 

I’ll preface my answer by saying that in May 2025, essentially all of the federal science grants at Harvard were canceled by the government. I had an individual National Science Foundation (NSF) grant for my research, and two NSF conference grants. The grants were all canceled in May — and I was supposed to use one of them to organize a conference at Harvard in June! It was an incredibly disruptive, stressful and discouraging experience. Since last spring, it has felt like higher education, and the field of science, was having an existential crisis.

Then in the fall I got a phone call from the MacArthur Foundation telling me I had won one of their awards. This was quite a wonderful shock. It was a real gift to be told that somebody still cares about my research and to be given the resources I needed. The award couldn’t have come at a better time.

Who inspired you when you were younger and who inspires you today?

When I was younger, I had many wonderful teachers who encouraged me in writing, math and music. I also grew up with three younger sisters, who like me loved math and science. Then when I was a senior in college at Harvard, I met Maryam Mirzakhani, who had just started graduate school at Harvard. We took a class together, and while she was quiet and a bit shy, she was clearly very intelligent and asked penetrating questions. She went on to become the first woman to win a Fields Medal, though tragically she passed away from cancer a few years later.

Today, I have a number of friends who inspire me, many of whom are women. Many are juggling careers with parenting. It’s inspiring to see women doing amazing work while juggling whatever else is going on in their lives.

What were your favorite books growing up and what are you reading today?

In elementary school my favorite books were the Narnia chronicles, starting with The Lion, the Witch and the Wardrobe, as well as the Lord of the Rings trilogy.

More recently, I’ve read several inspiring memoirs by female scientists. I read Sara Seager’s memoir The Smallest Lights in the Universe, about her work as an astrophysicist as well as her life. I also enjoyed Hope Jahren’s memoir Lab Girl, which discusses her life and work as a geochemist.

You recently coauthored a paper called First Proof, which examined the ability of large language models to solve complex mathematical questions. What prompted this investigation? What did you learn? 

We initiated this project in part because the media surrounding AI and math is so extreme. There are articles saying AI is going to “solve math,” as well as articles saying that AI is useless. We wanted to develop an objective test to see how good AI is at proving mathematical statements.

We had to design this test very carefully because if you ask an AI model a math question, and the answer is on the internet somewhere, the model is going to find that solution. We had to identify problems that did not have solutions online. We also didn’t want to use famous unsolved conjectures, because that wouldn’t tell us anything. We needed to develop solvable open questions whose solutions were not on the internet: We concluded that we should use research questions from our own work that we had recently solved but not yet published. Our initial paper First Proof consisted of 10 problems from different areas of math. We made this paper public on February 6, and revealed the solutions on February 14, to allow for a “community experiment” during the eight days in between. During this time many companies and individuals took on the challenge and tried to solve our problems.

What did you learn from this experiment?

In our testing of a few publicly available AI models, before we publicly released the problems, we found that if we gave the model one shot to answer each question, as opposed to interacting with the model and giving feedback on intermediate solutions, the model could solve two of our 10 problems. During the community experiment, several companies shared more impressive results using their internal, but not publicly available, models. We didn’t specify any strict protocols for the community to follow, like the one shot rule, making it difficult to come to any definitive conclusions or compare the outcomes. We are now busy preparing to release a second more formal round of problems.

There are many challenges facing the world today. What keeps you up at night?

I would say one of the things keeping me up at night is worrying about the state of higher education and funding for science research in general. Recently, the government has been trying to cut as much funding as possible for basic scientific research, including graduate and postdoctoral fellowships.

Another thing I’m thinking about is how we, as mathematicians, can best use tools such as AI. While AI models can be very helpful, when it comes to math research, the models often output a wrong answer with a great deal of confidence. We need better tools for determining whether an AI-generated solution is correct.

What gives you hope for the future?

My students give me hope. I teach a freshman seminar every year, and it’s always a wonderful experience for me to get to know these very bright 18-year-olds who are arriving at Harvard full of hope and dreams. Their excitement and enthusiasm keep me feeling young and optimistic.

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Their promise as scientific leaders is reflected not only by the quality of their research and their unquestionable ability. But their potential is also written in the stories of the finalists who have stood in their shoes over the last 84 years.

This year,  finalists heard from one such �鶹���� alum, Marcian “Ted” Hoff (�鶹���� 1954),  the twelfth employee at Intel and inventor of the microprocessor.  He is a member of the National Inventors Hall of Fame and a recipient of the National Medal of Technology and Innovation.

Ted sat down with the finalists for a fireside chat, where he shared his journey and answered finalists’ questions. Below are some excerpts from the conversation.

When you began at Intel, what problem were you trying to solve that led to the invention of the microprocessor?

“When I first got involved with that project, we had agreed to build a set of custom chips for a calculator company. Three engineers came from Japan with a design they wanted built, and the more I looked at it, the more concerned I became. They had separate control chips for the keyboard, display, printer, memory and arithmetic.

“The idea I came up with was that instead of building all these different chips, we could make a general-purpose processor and put the complexity into memory, instead of wiring it into the chip itself. You can write the code for that memory on a piece of paper, and then there’s a standard way of putting it into the memory, so you don’t need a new chip layout every time.

“That meant the same hardware could be used for many different applications. What started as a solution to designing the calculator turned out to have many other uses. One thing I learned is that ideas often come from things you did earlier that didn’t seem connected at the time. Some of these disconnected experiences can turn out to be very useful in the long run.”

As someone who laid the foundation for modern computing, what questions and considerations do you think are most urgent as we advance AI systems today?

“We’re building more powerful processors, smarter processors, where the artificial intelligence can get well beyond the typical human intelligence. An important question becomes, ‘What is the role of the human in that society?’

“I think one of the things future generations really have to think about is not just what we can do, but the impact of what we do. There are many problems in the world, and it isn’t always obvious what the best solution is. You have to be careful about putting technology into use before it’s ready. It may be a great development eventually, but when something is introduced before all the details are worked out, that can be hazardous.

“When I went to engineering school, Rensselaer, was an all-male school. I think the year I graduated, there were only two women in the entire school body,” Ted said. “Well, our youngest granddaughter is now at Cal Poly, studying mechanical engineering.”

He pointed to that contrast with today, where far more women are entering and leading in �鶹����. For Ted, that shift underscores the importance of “broadening the view,” and bringing more perspectives to not just what we build, but how we think about its impact.

How did it feel to join Intel when it was still a very young company, and what advice do you have for navigating risk or the unfamiliar?

“When I joined Intel, there was definitely some risk. I was at Stanford at the time in what looked like a very secure position, supported by government research contracts, and things seemed to be going well. Leaving that to go to a brand-new company was not an obvious decision. Sometimes you have to make your best guess and accept that there are no guarantees.

“Interestingly, not long after I left, there were protests at Stanford about government-supported research, and the university decided to move a lot of that work off campus. If I had stayed, I might have been looking for a job anyway.

“That was eye-opening. Things that seem secure may not be, and things that seem risky can work out very well. My advice is to make the best decision you can with the information you have, and don’t be afraid of something simply because it’s new or uncertain. That’s often where the most interesting opportunities are.”

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This Women’s History Month, �鶹���� is applauding the women who have pushed the barriers open in �鶹���� and helped inspire today’s young scientists. We spoke with several top winners in the Society’s flagship competitions. They reflect on their research, the women who inspire them, and the role they hope to play in encouraging the next generation of women in �鶹����.

We had a chance to hear from the winners in the 2025 Thermo Fisher JIC, including Camila, Pranshi, Christine and Alice who were recognized for their innovative research and teamwork during a week of rigorous challenges.

“To me, being a woman in �鶹���� means being confident, determined and having the courage to pursue �鶹���� fields with curiosity. It also means inspiring other women and encouraging people to believe in their abilities and pursue their dreams with confidence.”

“My woman in �鶹���� inspiration is my mother, Kenira Thompson. She taught me the basics of research and showed me what science truly is. Since I was young, all I can remember is her hard work and dedication toward her pursuit of science, and how much she pushed herself to achieve her goals. In turn, she inspired me to try my hardest to achieve my own goals, whether it be in �鶹���� or in life.”

Pranshi Mehta
“Women’s History Month is a powerful reminder that progress in �鶹���� has always been fueled by persistence, resilience and the courage to challenge the status quo. I am deeply grateful to the mentors, teachers and peers who have encouraged me to pursue ambitious research questions and to never shrink from the challenges along the way. As we celebrate this month, I hope that more young girls begin to see themselves not merely as participants in science, but as the innovators, leaders and changemakers actively shaping its future. The next great breakthrough could come from any one of them.”

Christine Wang
“My woman in �鶹���� inspiration is Fei-Fei Li, whose groundbreaking work in AI has transformed computer vision. She inspires me not only through her intellect but also through her dedication to expanding opportunity and representation in AI. As I pursue �鶹����, I hope to follow her example and help shape a future in technology that is both innovative and open to everyone.”

Abigail Qi and Siyaa Poddar, participants in the 2025 Regeneron International Science & Engineering Fair in Columbus, Ohio, reflect on overcoming adversity in science.   

“So many women have worked to pave the way for me to be afforded the opportunities I have now. It is our responsibility as women in �鶹���� to keep that momentum up! There are too many creative minds and too many problems to be solved for us to limit ideas purely based on whose mouth they come out of. I am so grateful to be a part of such a strong community and am excited to continue perpetuating the innovative, creative and determined mindset of the women before me.”

“When it comes to �鶹����, I’ve never thought of myself as different from any guy. I’ve never thought something would be harder to achieve because I’m a girl, and I’ve never limited myself because of my gender. At their core, science and mathematics don’t depend on gender. For example, bacteria don’t grow differently depending on who inoculates them. That mindset has allowed me to approach challenges as just challenges, not as proof that I didn’t belong.

I think this perspective is incredibly important for girls in any subject, especially in �鶹����. If you internalize the idea that you’re at a disadvantage before you even begin, you’re fighting two battles: the material itself and your own doubt. But if you see yourself first and foremost as a capable learner, it’s amazing what you can achieve.

This doesn’t mean barriers and bias don’t exist. However, you can acknowledge challenges without letting them define your limits. In �鶹����, where confidence often determines who speaks up and who takes on leadership roles, refusing to self-limit is essential. In my opinion, the most important mindset is realizing you don’t need to prove you deserve your seat at the table more than anyone else. You belong because you’re willing to learn, to do the work and love what you do.”

Around this time last year, Rivka Lipkovitz and Ava Grace Cummings won top awards in the Regeneron Science Talent Search for their research in mathematics and health.

Ava Grace Cummings
“One of my women in �鶹���� inspirations is Mary Golda Ross. She was the first Native American female engineer and spent time working in statistics for the Bureau of Indian Affairs before working as an engineer for Lockheed Martin in the 1940s. As an Indigenous woman pursuing engineering, I find her story and resilience very inspiring. She also spent much of her career educating and giving back to her community, which I believe is one of the most important aspects of breaking barriers within �鶹���� fields. In 2019, she was also featured on the $1 coin!”

Rivka Lipkovitz
“Although most universities today have a roughly even gender split in enrollment, I still sometimes walk into a classroom and see only one or two other women. I’m glad that we’ve made so much progress over the past century, especially in K–12 education, but I still think there’s room to improve. I hope that one day it feels completely normal to see women everywhere in �鶹����. I don’t feel threatened being one of a handful of women, but I do think there are many women who would enjoy math if they had more opportunities to be exposed to it and encouraged early on. I want to study mathematics and conduct research in economics. At my university, only about 10% of the economics faculty are women. I hope that having one more woman in the room can make it easier for others to enter and feel that they belong.”

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Now a freshman at MIT, Rivka is continuing to pursue the kinds of quantitative questions that first drew her to research. Outside the classroom, she’s also a competitive speedcuber who can solve a Rubik’s Cube in under 10 seconds.

We asked Rivka about her advice for this year’s finalists, what she learned through her research, and what she’s been exploring during her first year at MIT.

What advice would you give this year’s �鶹���� finalists about exploring new topics or trying unconventional approaches in their research?

“My advice to this year’s finalists would be to stay curious throughout your time in college. Even if your academic focus stays mostly the same, go to seminars outside your niche and explore adjacent fields.” Rivka says that approach has already shaped her own academic interests. “I stayed in quantitative social science, but branching out a bit made me realize that I’m increasingly interested in labor economics.”

Your project analyzed trends in voter turnout using statistical modeling. What did you find most interesting about the patterns you discovered?

“This project made me appreciate how rarely policy impacts are clear-cut,” Rivka said. Turnout appeared to increase in midterm elections after voter ID laws were implemented, “but only in some models.”

Because of that complexity, she focused on what the data could reliably support rather than drawing sweeping conclusions.

“I didn’t conclude that voter ID laws increase turnout. Instead, I used this information to conclude that it’s very unlikely they decrease turnout in midterms.”

She was also surprised by how much the timing of the laws mattered.

“I was surprised by how much the effects seemed to depend on when a state adopted the laws, which suggested that context matters a lot. More broadly, when the results aren’t definitive, the best we can do is weigh the evidence carefully and make the most reasonable decision based on what we know.”

Rivka continued refining the project after the competition and submitted it to a journal, where it was published this past December.

What was your most memorable experience from the Regeneron Science Talent Search?

“One of my most memorable moments was the very first day, when the finalists from my region arrived and we all met in person,” Rivka recalled. “It felt surreal to be in D.C. with people I’d only known online before the competition.”

She also remembers how quickly the finalists fell into deep conversations.

“The dinner conversation was really lively,” she said. “We were debating big questions, like whether AI could create bioweapons and what a workable regulatory framework would be if that scenario became plausible.”

You moved from San Francisco to Cambridge to attend MIT. What has the transition been like, and what have you been exploring so far?

“The transition was easier than I expected,” Rivka said. “Boston is similar to San Francisco in that both are large cities on the water.”

She quickly built a community with classmates and dormmates.

“I’ve been fortunate to make friends in my dorm and classes, and we’ve spent some weekends exploring Boston.”

The biggest adjustment has been the weather. Like fellow �鶹���� 2025 top ten winner, Logan Lee, Rivka is “…still getting used to needing a heavy jacket and gloves,” she said. “At the same time, playing in the snow is fun, and we even had a blizzard last week that was severe enough that we built a huge igloo and hung out together inside for an hour.”

Academically, she has been taking both core requirements and more advanced courses. “I’ve been taking some of my graduation requirements, such as chemistry and physics, along with more specialized electives, including graduate probability and labor economics.” The probability class in particular pushed her mathematically. “Probability was one of the most abstract and challenging classes I’ve taken, and it linked together almost all of the math I had learned previously. At the same time, completing the problem sets was very rewarding, and I feel the class helped me grow into a more capable mathematician.”

She has also begun assisting with research on applying machine learning to causal inference with MIT econometrician Whitney K. Newey.

If you could have dinner with any �鶹���� professional, living or past, who would it be and what would you want to ask them?

Rivka says she would choose American economist Thomas Schelling, whose work she encountered in an class during her first semester at MIT. Schelling, who was awarded the Nobel Prize in Economic Sciences for his work applying game theory to understand conflict and cooperation, stood out to her for the way he approached economics almost like a natural science.

“What I found so compelling about Schelling is how he explained complex social outcomes using really simple assumptions about human behavior,” Rivka says. “For example, small preferences, like not wanting to be in the minority, can end up producing large patterns such as segregation and often inefficient equilibria.”

If she had the chance to speak with him, Rivka says she would want to explore how those ideas apply today. “I’d want to ask what modern problems he thinks are still driven by these kinds of population dynamics,” she says, “and then brainstorm what it would look like to design policies that could shift systems toward better equilibria.”

To learn more about this year’s incredible finalists and their hard work, join us on Sunday, March 8, at the Conrad Hotel from 1:30 p.m. to 3:30 p.m. for the Public Exhibition of Projects during �鶹���� Finals Week.  More information about the students can also be found here.

The post Rivka Lipkovitz, �鶹���� 2025 fifth place winner, is still following the numbers appeared first on �鶹����.

Featured in , as well as , Logan came in fourth place overall during the 2025 competition, winning $100,000 that is to be used towards education. For his project, Logan studied ways to better control invasive mosquitoes in Hawaii, where avian malaria has led to the extinction of more than 30 native bird species. Current efforts release reproductively incompatible male mosquitoes that produce nonviable eggs, but these sterile males often struggle to survive in the wild. Logan boosted their survival by inoculating them with beneficial bacteria from wild mosquitoes, helping them grow faster and withstand colder conditions. In the process, he also identified a potentially novel bacterium adapted to the mosquito midgut in Hawaii.

Below, let’s hear more from Logan and his reflections on college life and scientific discovery.

Looking back on your Regeneron �鶹���� experience, what advice would you give to this year’s finalists?

Logan encourages this year’s finalists to approach the week with openness. “I would tell this year’s finalists to frame finalist week as one of growth, both individually and as a collective,” he says. “Each new day is one of transformation as you explore new areas of science, conversations with your fellow finalists, and discussions with professional scientists.”

For Logan, the impact of �鶹���� did not end when the week was over. The relationships he built continue to shape his life in college and beyond. “In particular, the connections that I formed with finalists are ones that I continue to cherish to this day,” he adds. At Yale, he often spends time in the Native American Cultural Center with fellow finalist Ava Cummings and he has also reunited with Melody Hong and in Boston and New York City.

How has your experience at Yale been so far?

“I have loved my time at Yale,” Logan says. The biggest adjustment has been the weather. In November and December, he watched the temperature drop lower and lower until he could not leave his dorm without a heavy coat and at least two layers underneath. What has made the transition easier, he says, are the people. Through clubs like WYBC, Yale’s college radio station, and time spent in the Native American Cultural Center, he has found community. As he wrote his responses, he was sitting in the radio station beside friends, almost able to forget the blizzard outside.

What have you been studying and working on recently, both academically and in your research?

“Being at Yale has allowed me to expand my wings, both scientifically and otherwise,” he says. Logan will double major in Molecular Biophysics and Biochemistry, and Statistics and Data Science. “Academically, double majoring will let me pursue my scientific interests while also exploring other fields through Yale’s liberal arts curriculum, including classes like Introduction to Native American Studies and Canadian Literature.”

In addition to his coursework, Logan serves on the research and development team at Simplex Sciences, a biotechnology nonprofit that produces single-stranded DNA ladders and organizes educational events in New Haven.

“Exposure to this alternate side of biological research has been particularly enriching to me, as well as the community that comes with it,” he says.

Outside the lab, he remains deeply involved on campus. “Yale has provided me with a place to both re-establish old interests and explore new ones,” Logan says, noting his work in sound engineering for the college radio, weekly SAT tutoring and science lessons for local students, serving as a poetry editor, supporting campus events and productions and acting as treasurer for YAISES, Yale’s Indigenous �鶹���� group.

You played a key role in renaming Discoverers’ Day to Indigenous Peoples’ Day at your high school. What was it like to see that change happen, and what did you learn from being on the planning committee? Why was this important to you?

“Seeing this change happen at my school was incredible,” he says. “There’s a common misconception that administrative changes such as renaming holidays are insignificant in the grand scheme of things, but I view them as a reframing to celebrate underrecognized communities.”

For Logan, the shift was about more than a name. It was about visibility and acknowledgment.

“To see my culture be commemorated in this way, bringing both its rich traditions and modern struggles to light, and knowing that I contributed to the change, brought me immense pride,” he says. “Smaller initial changes are what allow for the biggest transformations later.”

If you could teach a computer to feel one human emotion, which would it be, and why?

When asked what human emotion he would teach a computer, Logan does not hesitate: “I would teach a computer how to feel compassion,” he says.

For him, research is fundamentally about making a tangible change for communities. “If a computer were able to feel compassion, it would understand the why behind what is being done and form an understanding of the broader expanse of the research.” He believes compassion could help address the disconnection that pervades society. “I think that this would address one of the most prevalent issues in the modern landscape of research: a disconnect from the issue being researched,” he explains. Too often, he says, research is conducted without fully grasping its reach or consequences. “To perform meaningful research is to fully understand the significance of it, at all levels.”

To learn more about this year’s incredible finalists and their hard work, join us on Sunday, March 8, at the Conrad Hotel from 1:30 p.m. to 3:30 p.m. for the Public Exhibition of Projects during �鶹���� Finals Week.  More information about the students can also be found here.

The post Five Questions with Logan Lee, the fourth-place winner of Regeneron �鶹���� 2025 appeared first on �鶹����.

The webpage, which can be viewed here, includes individual profiles with contemporary assets, highlighting the lasting contributions these alumni have made to their fields, as well as archival Society content from their competition experience. The list was launched in March 2022, with more than 100 alumni, and the Society plans to add to this list as the organization’s more than 70,000 alumni continue to contribute to their fields.

The additions are:

• Founder and CEO of Entagen and Vyasa, Christopher Bouton, who is a leader in data integration and AI
• Co-Founder of WHOOP John Capodilupo, who continues to make strides in health technology as a founder of Throne, a gut technology startup;
• Retired Vice Admiral Walter “Ted” Carter, who is president of Ohio State University;
• Two-time Olympian and Long Island University Athletic Hall of Famer Maria Coffey, who earned her PhD in biomedical science;
• Major Adam Fuhrmann, who was selected for the 2025 Astronaut Candidate Class;
• Co-Founder of Leap Motion and founder of Midjourney, David Holz, whose company enables users to generate unique artwork through text prompts;
• Zoox Co-Founder Jesse Levinson, who is working towards a future where autonomous vehicles are commonplace;
• The late author Joanna Russ, a celebrated feminist scholar and author who transformed science fiction;
• Venture capitalist Sheel Tyle, who seeks to build companies that matter; and
• MacArthur Fellow Lauren Williams who is the second-ever tenured female math professor at Harvard University

“We are pleased to celebrate and recognize these extraordinary individuals who are innovators, leaders and pioneers,” said Maya Ajmera, President and CEO of the �鶹���� and Executive Publisher of Science News. “The Society is honored to have played a role in supporting these remarkable individuals at the beginning of their scientific journeys.”

Each alumnus was named to the list based on their professional accomplishments and lasting contributions to advancing science and improving the world in which we live.

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