Bio-Rad Irvine/Santa Ana Scholarship

My passion for science began not in a lab, but on a playground I climbed alone. When I was a child, my father was unable to join my brother and me on the jungle gym; a deer tick had sapped his strength. At the time, I didn’t understand why he stayed inside, but years later, learning about the molecular mechanics of Lyme disease transformed that childhood confusion into a drive for discovery. This personal history is why my first hero in science is Dr. Katalin Karikó, a woman whose tenacity fundamentally reshaped modern medicine. Dr. Karikó is now globally celebrated for her Nobel Prize-winning work on nucleoside-based modifications, a breakthrough that suppressed the inflammatory response to synthetic mRNA. This discovery was the reason for the potential for mRNA vaccines, including those for COVID-19. However, I am most moved by the decades she spent in academic obscurity. I first discovered her memoir, Breaking Through: My Life in Science, while visiting the Apollo Cancer Institute in Chennai, India. I was there to coordinate a letter-writing program for pediatric patients, and finding her book felt like a providential encounter. Reading about her childhood in rural Hungary and her struggles as an immigrant, facing demotions and a lack of funding because her ideas were deemed too radical, resonated with my own experiences in the Pearlman Lab at UC Irvine. While investigating how bacteriophages degrade biofilms to disrupt Pseudomonas aeruginosa growth, my project was nearly derailed when my PhD student mentor left the lab. Like Dr. Karikó, I realized that progress is rarely a straight line. Her story gave me the strength to see logistical hurdles not as endings, but as puzzles. Today, I am fortunate to be connected with her on LinkedIn, where her advocacy for basic research serves as a daily reminder to remain resilient in the face of academic skepticism. This same spirit of persistence led me to my second hero, Dr. Mitchell Brin, a pioneer in the therapeutic use of botulinum toxin. During my internship at AbbVie last summer, I sought out scientists to help me unpack my stalled experiments at UCI. Meeting the man who revolutionized the treatment of movement disorders was intimidating, yet Dr. Brin’s humility was immediate. I explained my research journey to him, how I had pivoted toward bioinformatics and computational modeling under Dr. Christopher Negron to keep my phage research alive. What struck me most wasn't just Dr. Brin's expertise, but his genuine curiosity. He wasn’t merely "taking a meeting"; he was actively engaging with my data on viral-bacterial interactions. He listened to a student intern with the same intensity he might bring to a clinical trial. Dr. Brin and Dr. Karikó represent the two pillars of the scientist I hope to become. From Dr. Karikó, I learned that molecular insight can translate into profound human impact if one has the grit to defend their ideas. From Dr. Brin, I learned that a great researcher never loses respect for the next generation. I strive to emulate both, remaining as entranced by the "why" of science decades from now as I am today. As Dr. Brin reminds his audience, “chance prepares the prepared mind”, and I’m excited to prepare for my next few years as an undergraduate.

Some lessons are taught with whiteboards and worksheets. Others begin with a riot over Minecraft. When I launched a free coding class at the Orange County Rescue Mission, I expected to teach structured lessons on Scratch. Instead, I was met with twenty students chanting for Minecraft, my carefully planned curriculum dissolving within minutes. But in that chaos, I began to see something larger than a single class: a glimpse into how access to technology can reshape opportunity. Rather than forcing structure, I adapted. A simple game became the foundation for exploration, and soon students were not just playing, but building. Concepts like loops and variables transformed from abstract terms into tools for creativity. What mattered wasn’t mastery of syntax, but the confidence to create. Experiences like this reflect a broader truth: science and engineering are improving lives not only through breakthrough discoveries but through expanding access. Technology has the power to close gaps: giving individuals the tools to learn, solve problems, and make informed decisions in ways that were once out of reach. I saw this same principle from a different angle through my work in machine learning. Using public heart disease datasets, I developed a classifier that translated inputs like blood pressure, activity level, and age into simple risk estimates. The goal was not technical complexity, but usability; creating an interface that made health data understandable and actionable. While the model faced limitations, including bias in datasets and imperfect accuracy, it reinforced an important idea: innovation is most impactful when it meets people where they are. Across both experiences, the common thread is not the technology itself, but how it is used. A coding platform becomes powerful when it empowers a student to create. A machine learning model becomes meaningful when it helps someone better understand their health. Science and engineering improve lives when they are designed with accessibility, clarity, and real human needs in mind. Around the world, this approach is already reshaping how people interact with complex systems. From digital education platforms to predictive healthcare tools, engineering is no longer confined to specialized spaces. It is becoming more integrated into everyday life, equipping individuals with knowledge and agency. In my classroom, that impact was immediate. Students who had never considered themselves “technical” began teaching one another, debugging code, and sharing ideas. They were no longer just learning technology; they were using it to express themselves. That shift, from passive consumption to active creation, is where real change begins. Science and engineering make life better not only by advancing what is possible, but by expanding who gets to participate. Whether through a simple coding lesson or a data-driven health tool, their true power lies in their ability to turn curiosity into capability and uncertainty into understanding.

Planting 200,000 trees. That's the impact I made by coding a program. With all my devices running Ecosia (a search engine that funds tree planting through ad revenue), my program constantly refreshed search queries that maximized ad revenue. The result? Enough money for two hundred thousand trees to be planted. This experience taught me how engineering is making life better across the globe right now: it is an equalizer. Despite my family's low income and my socioeconomically disadvantaged school, math and code are accessible tools that have allowed me to create massive impact from my bedroom in Lakeland Village. I want to study engineering because I am drawn to solving "impossible" problems with what I am given, solutions people wouldn't have otherwise considered. However, to continue protecting our planet, we need massive advancements in sustainable materials processing. One of the biggest threats to our globe is plastic waste. Traditional recycling is failing, with current methods of recycling polystyrene producing harmful byproducts, leading to under 10% of it being recycled. Every year, the world produces 24 million tonnes of non-dyed polystyrene: plastics used in everyday consumer products. Most of it ends up in landfills. Recently, scientists discovered that black plastics can be recycled cleanly by using light; the dark dyes absorb the light, converting it into heat to break down the plastic at a molecular level. The only caveat is this photothermal process doesn't work on non-dyed plastics because they lack those heat-absorbing dyes, meaning 85% of plastics can't be recycled with this highly efficient method. I believe the next big scientific advancement will be scaling this photothermal process for all mixed-waste streams. I developed a novel, accessible method to fix this gap. Using a process called solvent casting, I dissolved non-dyed polystyrene and infused it with a 5% concentration of Carbon Black. This essentially made the formerly non-dyed plastic able to absorb the light. When exposed to the right wavelength, it successfully triggered photothermal depolymerization, breaking the plastic down into styrene in a cleaner manner. I validated this success through GC-MS analysis at UC Irvine. This advancement will affect society globally because it offers a cheap, accessible recycling solution for clear plastics that could be easily deployed in developing nations. I built this entirely without high school funding, relying on my summer job and a scrappy mindset. That resourceful mindset is exactly why my heroes in engineering are the team behind the Apollo 13 "Mailbox" fix. When an oxygen tank exploded, they didn't have access to state-of-the-art replacement parts. Using only materials already on the spacecraft: plastic bags, cardboard, spacesuit hoses, and lots of duct tape, with only that they created a contraption to fit the Command Module filters, saving the astronauts' lives. They are my heroes because they exemplify the ultimate form of engineering: finding solutions only with what is available. Engineering isn't just about building things; for me, it’s applying science to ensure that a student's access doesn't limit their ability to change the world. My goal now is to scale my recycling processes at Stanford, holding the door open for the next generation of resourceful problem solvers.

I think the next major scientific advancement will be the ability to identify and interpret the atmospheres of potentially habitable exoplanets at scale using machine learning. Over the past few decades, astronomy has moved from asking whether planets exist beyond our solar system to confirming thousands of them. The next leap will be more difficult and more profound: determining what those planets are like, what molecules exist in their atmospheres, and whether any show conditions that could support life. My interest in this question began with a grainy black-and-white image of the HR 8799 system on a Science Olympiad test. Four faint dots circled a young star about 133 light-years away. I remember wondering how those gray blobs could be planets at all. That question eventually grew into a deeper one: how can scientists responsibly infer entire worlds from limited, noisy, indirect evidence? I explored this question by studying exoplanet atmospheric characterization. When a planet passes in front of its star, some starlight filters through the planet’s atmosphere. Different molecules absorb different wavelengths, leaving tiny patterns in the light. From those patterns, scientists can search for a plethora of compounds including water vapor, carbon dioxide, methane, and other molecules that may reveal a planet’s climate, chemistry, or habitability. The challenge is that these signals are extremely small and often buried beneath instrument noise, stellar activity, and complex atmospheric degeneracies. The future breakthrough will not come from telescopes alone, but from combining powerful observatories with machine learning, physics-based models, and careful statistical interpretation. During my NASA SEES internship and AGU Bright STaRS research, I explored this intersection by working on machine learning approaches for accelerating transmission spectroscopy. I studied how JWST data moves through the Eureka! pipeline, from raw detector files to light curves and transmission spectra. I also worked with synthetic spectra generated through atmospheric modeling tools and trained a dual-region convolutional neural network to identify molecules such as H2O, CO2, and CH4. What excited me was not just that a model could classify spectral features, but that it could help scientists search more efficiently through faint, complex data while still requiring careful validation. Globally, this advancement would affect society in a way that is both scientific and philosophical. The discovery of a strong biosignature candidate would not immediately answer whether we are alone, but it would change the scale of the question. It would require international collaboration, open data, public communication, and humility about uncertainty. Scientists would need to explain not only what was found, but how confident we should be, what alternative explanations remain, and what observations should come next. That is why I see this advancement as more than a technical milestone. AI-enabled exoplanet atmospheric characterization could help humanity move from planet detection to planetary understanding. It could teach us how common Earth-like conditions are, how atmospheres evolve, and whether life’s ingredients appear elsewhere in the galaxy. Most importantly, it would show how science progresses at its best: not by turning faint signals into easy certainty, but by turning them into better questions, better methods, and a more careful understanding of our place in the universe.

One of my greatest heroes in science is Marie Curie. I admire her incredible scientific achievements, but also because she was a woman who succeeded in a field that was dominated by men. As a woman myself, I find her story especially inspiring because she proved that determination, intelligence, and hard work can overcome barriers and change the world. I also feel a personal connection to her because I have Polish ancestry, just as Marie Curie was originally from Poland. Knowing that we share this heritage makes her accomplishments even more meaningful to me. Marie Curie was born in Warsaw, Poland, in 1867 and later moved to France to continue her education. At a time when women had very limited opportunities in higher education and scientific research, she pursued her passion for science despite many obstacles. Her dedication eventually led her to become one of the most important scientists in history. Marie Curie's most significant contribution was her pioneering research on radioactivity, a term that she actually coined. Working alongside her husband, Pierre Curie, she discovered two new elements: polonium and radium. She named polonium after her homeland, Poland, which demonstrates the pride she had in her heritage. These discoveries greatly expanded scientists' understanding of atoms and the nature of matter. Her work laid the foundation for the field of nuclear physics and opened new possibilities for scientific research. One reason Marie Curie is so important is that her discoveries led to major advances in medicine. Radioactive materials are now used in medical imaging and cancer treatments, helping doctors diagnose and treat diseases more effectively. During World War I, Curie also helped develop mobile X-ray units that were used to treat wounded soldiers on the battlefield. Her efforts saved countless lives and demonstrated how scientific knowledge could be applied to solve real-world problems. Marie Curie's achievements were recognized around the world. She became the first woman to win a Nobel Prize and remains the only person to win Nobel Prizes in two different scientific fields: Physics and Chemistry. These accomplishments were extraordinary, especially considering the challenges women faced during her lifetime. Her success helped pave the way for future generations of women scientists and engineers. What I admire most about Marie Curie is her perseverance. She faced discrimination, financial difficulties, and the dangers of working with radioactive materials, yet she never gave up on her research. Her commitment to learning and discovery shows the importance of curiosity, courage, and resilience. Marie Curie is my hero because she transformed science through her groundbreaking discoveries and used her knowledge to help others. Her legacy demonstrates that people from all backgrounds can make extraordinary contributions to science and engineering. She continues to inspire me to work hard, pursue knowledge, and make a positive impact on the world.