I like building things, including rockets, drones, and laboratory equipment. Part of the enjoyment is figuring out what a design will do before I can hold it in my hands. Math lets me begin that work with a sketch, a few assumptions, and a question. During an internship at Oak Ridge National Laboratory, I developed MATLAB models of liquid pistons for compressed-air energy storage. The mechanism is easy to picture: liquid enters a chamber and compresses gas. But pressure, temperature, and heat transfer all change together. I enjoyed working through those relationships because each equation had something physical behind it. A derivative described how quickly the gas heated; an integral accounted for work as its volume changed. The mathematics gave me a way to follow a process I could not understand from a single measurement. What I love most is discovering that a method I learned for one problem can help with another. In chemical engineering, heat moving through a material and molecules diffusing toward an electrode can be described by closely related mathematics. The equipment looks different, but recognizing the shared structure gives me somewhere to start. There is satisfaction in finding that an unfamiliar problem contains something I already understand. I also appreciate that math gives my ideas something to push against. I am beginning doctoral research on flow batteries at Georgia Tech, investigating whether circulating electrolyte could carry away equipment heat while supplying electrical energy. I like the possibility of making one system perform both jobs. Yet faster circulation also requires more pumping power. Working through that tradeoff is part of what interests me: I want to know how far the idea can go and what would make it worth building. There is room for creativity in choosing a model and discipline in checking it against the world. I enjoy moving between those tasks—simplifying enough to understand something, then asking what the simplification left out. Math keeps my curiosity productive. It lets me pursue a “what if” far enough to decide what to try next. For someone who likes making things, that is a powerful reason to keep learning it.

Our Phi Sigma Pi chapter at Georgia Tech organized a Gift of Life stem-cell registry drive that resulted in at least one confirmed match. I still think about that result. We had brought students together for an event; someone elsewhere might now have another possibility for treatment. We could not know how that possibility would unfold, but helping create it made the work worthwhile. As chapter president, and later vice president and treasurer, I also spent time on responsibilities with less obvious rewards. Our chapter had inherited more than $1,000 in debt. I helped raise the funds to repay it while keeping meetings, recruitment, and chapter activities moving. Paying down debt was hardly the reason I had joined a service organization, but it became part of taking care of one. Future members deserved a chapter they could build on without first repairing our finances. That experience shaped how I think about contributing. I like work where I can take responsibility for something concrete and leave it in better condition. Through volunteer chemistry tutoring, that has meant helping another student work through material I once had to learn myself. In a student organization, it meant attending to the practical details that allowed people to keep serving together. As I begin doctoral study, I want to retain that willingness to be useful wherever the work needs doing. My technical interests have also become more attentive to whose needs I am actually addressing. In a chemical product design course, my team developed an energy-storage concept for communities with unreliable solar power. I initially focused on energy density, a familiar measure of battery performance. A teammate from Kenya explained the expense and difficulty of transporting batteries in his community. His contribution redirected our design toward a dry-shipped gel battery, with transport and distribution receiving much greater attention. I knew more about batteries than I knew about the circumstances in which we were proposing to use them. Recognizing that gap improved our project. It also gave me a question I want to keep asking: what would I learn about this design by listening to someone who would have to live with it? I am now beginning doctoral research on thermally and mechanically coupled flow batteries at Georgia Tech, building on earlier battery and energy-storage work at Oak Ridge National Laboratory. I enjoy designing equipment and working through the physical reasons a system behaves as it does. Over my career, I hope to turn that interest into energy technologies that justify their cost, can be maintained, and serve the people expected to use them. I also want to lead a research group where students receive patient guidance and have room to develop their own judgment. Teaching and mentorship would let me give back throughout the long intervals between research results. I intend to continue volunteering alongside that work, rather than postponing service until I have a more senior title. The registry drive remains a useful reference point for me. Our contribution was limited, but it connected someone willing to help with someone who might need them. I want to keep making those connections—through a student’s education, a community effort, or a technology developed with its users in mind.

I like building things. I have spent years assembling rockets, working on drones, and, more recently, designing laboratory equipment. In one research project at Georgia Tech, I built and programmed a robot to spray catalyst onto electrodes. I could design a holder, print it, and check whether it fit. But many of the questions I want to answer as a chemical engineer are harder to settle by looking at a finished part. How much energy will a system waste? Where will heat accumulate? Will a design still work when its operating conditions change? Calculus gives me a way to work through those questions. During my 2025 internship at Oak Ridge National Laboratory, I developed MATLAB models of liquid pistons for compressed-air energy storage. The basic idea is easy to picture: liquid moves into a chamber and compresses gas, storing energy that can be recovered later. Describing what happens inside that chamber is more complicated. The gas heats as it is compressed, exchanges heat with its surroundings, and changes pressure as its volume decreases. All of those processes affect one another. This was a particularly tangible use of the mathematics I had studied at Georgia Tech. A rate of heat transfer becomes part of an equation for how temperature changes with time. Integrating pressure over a change in volume gives the compression work. Following those changes through a cycle helps answer the question that motivated the project: how efficiently can this system store energy? The derivatives and integrals have a physical meaning, and the answer matters to someone deciding whether to develop the technology. I think that is what makes calculus important across STEM. It lets us take something we can describe in words and make a prediction precise enough to test. The same idea applies when a researcher tracks a drug's concentration in the body, an engineer calculates a rocket's changing velocity, or a chemical engineer studies molecules moving toward an electrode. The details differ, but each problem requires accounting for quantities that change. Calculus also helps me see the limits of an attractive idea, including my own. I am beginning doctoral research on flow batteries in Dr. Nian Liu's group at Georgia Tech. One question I want to investigate is whether the liquid electrolyte circulating through a battery could also carry away equipment heat. Combining those functions sounds appealing. Yet moving more liquid requires more pumping power, and better cooling alone would not establish that the overall system is better. I will need to account for both effects before I can defend the design. That is a responsibility I want to take seriously as a researcher. I enjoy making an apparatus work, but I also want to understand why it works and when it will stop working. Software can help solve the equations; understanding the calculus helps me decide whether I have asked it to solve the right ones. My goal is to keep building energy technologies and eventually lead research that brings them into practical use. Calculus will remain part of that work, from estimating a design's performance before construction to explaining an unexpected experimental result. I want to build things that earn the time, materials, and energy we put into them. Calculus helps me judge whether they do.

When I joined Phi Sigma Pi at Georgia Tech in December 2022, our chapter had five active members. The service-based honor fraternity had lost momentum after COVID, and was in danger of folding. I had not expected to lead it, but I could see that preserving the chapter meant preserving what its members could do for others. Three months later, I ran for president and was elected. At first, serving others meant keeping the chapter alive. When I returned from Georgia Tech-Europe the following summer, our recruitment officer vanished without notice. I organized a week of events that nearly doubled our membership. The work taught me that leadership was less about being indispensable than about drawing people in. Every new member gave the chapter more capacity to serve, and every person who stayed helped ensure its work would continue after my term. After serving as president, I became vice president and treasurer. The chapter had inherited more than $1,000 in debt from the pandemic, and I worked to repay it through fundraising, negotiation, and careful bookkeeping. It was quiet, unglamorous work, but it mattered to the students who would inherit the chapter. During that period, I also organized a stem-cell donor drive with the Gift of Life Marrow Registry. The drive required more than choosing a date: I corresponded with Gift of Life, selected strategic collection points, and delegated tasks to fraternity members. Having rebuilt the chapter, I now had a team that could carry out a project larger than any one of us, and we collected dozens of donations. Later, we learned that one participant had been confirmed as a lifesaving match for a 50-year-old man with myelodysplastic leukemia. I consider this our chapter's crowning achievement, because it gave concrete meaning to our work: a man was given a second chance against cancer because our chapter had made it easier for students to step forward. This arc, from five struggling members to a man's life saved, changed how I understand selflessness and philanthropy alike. The most consequential part of service may happen long before anyone sees its result: welcoming a new member, managing finances responsibly, or finding the right street corner to set up a donor drive. I learned to lead by creating conditions in which other people could help, then following through on the details that made their help possible. That is the kind of servant leadership I hope to continue, as I return to the Georgia Tech community to pursue a PhD. Michael Rudometkin is remembered for making time for people in need. Phi Sigma Pi taught me how much that time can accomplish when people commit it together. With the help of his scholarship, I intend to honor his memory by redoubling my commitment to excellence, servant leadership, and altruism as I begin my PhD.

The magnetic dartboard in my freshman dorm was the last thing I expected to draw inspiration from when I began my final semester as an undergraduate. But when Dr. David Flaherty challenged me to design and build a robot for applying a consistent catalyst coating to an electrode, I found myself thinking about it again. Coating electrodes with a catalyst by hand takes months of practice and is highly prone to inconsistency, but Dr. Flaherty had hired me to make this all-important step more repeatable without sacrificing the flexibility our experiments required. Consistency matters because the coating on an electrode can influence its behavior: if the preparation varies, it becomes harder to tell whether a change in performance comes from the catalyst or from the way the sample was made. A dependable automated spray-coater would give the lab a more reliable starting point for researching eco-friendly, next-generation electrocatalytic processes—as long as motion patterns, electrode mounts, and aerosol shields all worked together precisely and efficiently. So, I began casting about for creative solutions, and landed on two interesting but unlikely domains. For the moving stage, I drew inspiration from aerial photography, a hobby of mine. Years of adjusting drone gimbals and flight paths by hand had given me a physical intuition for spatial motion and coordinate systems, and I drew on that experience to develop the spray device's control sequences. The dartboard answered a different part of the problem: I adapted its simple magnetic mounting principle to design and build interchangeable electrode holders and aerosol shields. Instead of rebuilding the setup each time an experiment required a different configuration, the user could swap those parts in seconds. By the end of that semester, I had built a fully functional robot that automated in-situ catalyst spray coating, and saved Dr. Flaherty's lab an estimated $70,000. Neither the drone nor the dartboard could tell me whether the system would be consistent. However, when I tested coated electrodes using membrane-electrode assemblies, potentiostats, and gas chromatography, the results demonstrated the system was seven times more consistent than a human. That November, I presented the work at the 2025 AIChE Annual National Student Conference in Boston, where my poster received third prize in catalysis. This experience taught me the importance of putting an unlikely idea through the demands of an actual experiment. The drone and dartboard helped me get past a difficult starting point, while careful measurement told me whether the result deserved to be used. That balance between creative instinct and empirical evidence is what I want to bring to my doctoral work. When I see a better way to do something, I want to build it carefully enough that someone else can rely on it too. For a video of a test-run of my invention, using a blue tracer dye instead of a catalyst suspension, please visit: https://youtu.be/zddfDDMpafM

The honest answer is that calculus is the language dynamic systems speak, and nearly everything in science and engineering is a dynamic system. I say this as a chemical engineer, where the pattern is impossible to miss. Almost any system we care about—a reactor heating up, a battery discharging, a drug diffusing through tissue—can be described by one or more differential equations, statements about how quantities change from moment to moment. That is calculus's real gift to STEM. Algebra describes the world standing still. Calculus describes the world in motion, and the world refuses to stand still. I have watched this play out in my own hands. As an undergraduate researcher, I helped build an electrochemical cell that converts captured carbon dioxide into useful chemicals, and the reaction's behavior at the copper surface came down to rates: how fast charge transfers, how fast ions diffuse, how the two compete. At Oak Ridge National Laboratory, I spent a summer writing MATLAB scripts to model compressed-air energy storage, and the entire model was a set of differential equations describing heat flowing in and out of a column of liquid. The code was new. The mathematics underneath was three centuries old. What convinces me of calculus's importance, though, isn't that it appears everywhere. It's that specific revolutionary technologies simply don't exist without it. GPS satellites correct their clocks using equations from relativity, which is differential geometry—calculus grown up. Medical imaging reconstructs the inside of your body by integrating X-ray measurements from a thousand angles. Every controlled flight, from a Cessna to the rockets I build and launch as a hobby, stays stable because someone solved the equations of motion faster than the vehicle could misbehave. My own flight simulations do the same thing on a laptop before I ever light a motor. And the most contemporary example is hiding in plain sight. The large language models behind modern AI learn through back-propagation, an algorithm that is, at its core, an enormous exercise in derivatives. Training a model means measuring how wrong it is, then computing the gradient — the multivariable derivative — of that error with respect to billions of internal parameters, and nudging each one downhill. The chain rule from freshman calculus, applied at industrial scale, is teaching machines to write and reason. When people ask whether calculus is still relevant, I point out that the most disruptive technology of this decade is a derivative calculation running in a data center. So calculus matters to STEM because change is what STEM studies, and calculus is the only mathematics built for change. It let us describe the world in motion, then predict it, then control it. Every field that has learned to do those three things has calculus somewhere near its foundation.

1. Last fall, I took a chemical product design course, which centered on a group project. My team developed an electrochemical energy storage system to improve power reliability in developing regions, where solar energy is common but inconsistent. Having spent the previous summer in a highly technical electrochemistry internship at Oak Ridge National Laboratory, I initially leaned into my usual strengths: ideation, optimization, and scientific rigor. As the project unfolded, though, I realized the problem I was solving, energy density, wasn’t the one that mattered. One of my teammates, a student from Kenya, described the situation his own community faced: hauling fuel and batteries miles on foot, unreliable power for refrigeration causing food spoilage, and even life-threatening failures in hospitals when solar panels lost power at night. His story entirely reframed the problem. The bottleneck wasn’t energy density at all, but cost, portability, and safe distribution. With his input, we designed a dry-shipped gel battery scheme that reduced transport cost, simplified production, and improved safety. I could never have found such a solution alone—in fact, if I hadn’t opened my mind to his perspective, I would have spent the entire semester solving a problem that effectively didn’t exist. This experience inspired me to pursue research that is technically rigorous, responsive to diverse needs, and accountable to the communities it hopes to serve. My classmate’s story ultimately inspired a central part of my research philosophy—ensuring each project benefits from as many diverse perspectives and lived experiences as possible. 2. Every year in metro Atlanta, roughly 700 people die of leukemias and lymphomas. There are no ribbons on lampposts for them, and most people I talk to have no idea the toll is that high. Fewer still know the strangest part: many of those deaths are preventable without a single new drug, with a transplant of blood stem cells from a genetically-matched stranger. Organizations such as Gift of Life keep registries of willing donors. The problem is that the registries are far too small, and the vast majority of patients who need a match never find one. Here is what I noticed that others walk past: the odds are worse for ethnic minorities, who are badly underrepresented in donor databases, and Atlanta is one of the most diverse cities in the country. Everyone treats that first fact as a tragedy, and it is. But put the two together, and the picture flips completely. A registry drive in Atlanta recruits exactly the donors the databases lack, which means a swab collected here carries more lifesaving potential than one collected almost anywhere else. Our city's demographics are not just a vulnerability—they are an asset nobody is using. As President of Georgia Tech’s chapter Phi Sigma Pi National Honor Fraternity, I tested this theory by spearheading a marrow registry drive with Gift of Life Marrow Registry, which signed up twenty donors. A year later, I was notified that one of our matches went on to save the life of a 50-year-old man with myelodysplastic leukemia. With real resources, I would run drives across the whole city — campuses, churches, festivals — and turn Atlanta into the registry's richest source of matches, saving lives far beyond it.