Selected Passage (Genesis 6:2–3, KJV): “That the sons of God saw the daughters of men that they were fair; and they took them wives of all which they chose. And the Lord said, My spirit shall not always strive with man, for that he also is flesh: yet his days shall be an hundred and twenty years.” Essay Thesis: In Genesis 6:2–3, the writer is not merely describing marriages but exposing a moment when human desire and power overstepped moral boundaries, prompting God to impose limits; the passage ultimately warns that when people treat others as objects of possession rather than as persons with dignity, society begins to decay from the inside. At first glance, these verses appear to be a simple narrative transition before the story of the Flood. Yet the language is deliberate and unsettling. The phrase “they took them wives of all which they chose” does not suggest mutual covenant or careful discernment. It suggests selection without restraint, desire without responsibility. The writer highlights not romance, but imbalance. A group described as “sons of God,” whether understood as powerful rulers or a privileged lineage, acts from appetite and status rather than moral accountability. Marriage, which in the biblical worldview is meant to reflect commitment and order, becomes an arena where power overrides reverence. This misuse of power is the real crisis. The problem is not attraction itself, but the reduction of other human beings to objects that can be claimed. The structure of the sentence centers the will of the takers, not the humanity of those taken. By presenting the act this way, the text subtly critiques a culture in which strength, status, or perceived divine favor justifies taking what one desires. The writer is exposing a social shift where might defines right, and where relationships are shaped more by dominance than by covenant. Such a society may still function on the surface, but morally it has begun to unravel. Verse 3 is God’s response to this unraveling. “My spirit shall not always strive with man” expresses divine patience reaching its limit. The word “strive” suggests an ongoing moral tension, as though God’s presence has been restraining humanity from fully descending into chaos. When human beings persist in treating others as means rather than as ends, even divine forbearance has a boundary. The declaration that humanity is “flesh” is not an insult but a reminder of limitation. Humans are mortal, fragile, and prone to self-deception. When they act as though their desires are absolute, they forget their own finitude. The statement about “an hundred and twenty years” functions as a boundary marker. Whether it refers to a countdown before the Flood or a limitation on human lifespan, the meaning is the same: time is not endless, and consequences are real. The writer portrays God not as impulsive, but as setting a measured limit after extended tolerance. This introduces a moral law woven into the structure of reality. When people consistently cross relational and ethical boundaries, the damage accumulates until a point of reckoning arrives. The passage suggests that moral disorder is not sustainable forever. This reading carries a deeply personal implication about belonging and responsibility. It is easy for people to believe that they can step into any place, claim any relationship, or pursue any desire without considering history, community, or the well-being of others. Genesis 6 challenges that mindset. It presents a world where desire detached from responsibility leads to collective decline. The passage does not say that love or marriage across boundaries is wrong; rather, it condemns the attitude that treats people as rewards to be taken rather than persons to be honored. The core issue is not nationality, lineage, or inheritance, but whether relationships are grounded in humility and mutual dignity. In this light, the verses become less about ancient mystery and more about enduring human tendencies. Whenever power, status, or personal longing overshadows respect for another’s agency, the same pattern repeats. The writer of Genesis sees this pattern as a signal that humanity is forgetting its place and its limits. God’s response is not arbitrary punishment but the setting of boundaries to prevent total moral collapse. Limits, in this sense, are an act of preservation. Ultimately, Genesis 6:2–3 teaches that desire without reverence becomes destructive, and power without restraint invites judgment. The passage calls readers to recognize that human relationships are sacred spaces, not territories for conquest. When people approach others with humility instead of entitlement, they align themselves with the order the text implies God intended. When they do not, they participate in the same unraveling that, in Genesis, leads to the Flood.

Legacy, to me, isn’t a statue or a last name on a wall. It’s what changes because you existed. It’s what becomes easier for the next person because you decided not to repeat the same pattern. When I moved to the U.S. as an international student, I felt what a “cycle” looks like up close: pressure without a safety net, loneliness you don’t want to admit, and the habit of telling yourself, “Just handle it.” In the beginning, that cycle hit me hard. Some days I was productive and confident. Other days I couldn’t focus, and I felt depressed in a way I didn’t know how to explain to anyone. Being far from family made everything heavier, and college doesn’t slow down just because your mind is tired. What changed my path wasn’t one big breakthrough. It was structure. I started protecting my sleep. I trained consistently. I studied even on days when motivation was dead. Weighted calisthenics became more than exercise for me—it became proof that progress is real when you stop relying on your feelings and start relying on your habits. Little by little, I felt more stable. I wasn’t “fixed,” but I was moving forward again, and that mattered. That’s the legacy I want to build: breaking cycles by building systems that help people keep going. I’m studying AI, and I want to become both a scientist and an entrepreneur. My biggest vision is humanoid robotics—building embodied AI that can move, sense, and work in the real world. Long-term, I want to contribute to making the first sustainable civilization on Mars possible. It sounds ambitious, but I don’t treat it like a fantasy. I treat it like a direction. Every skill I learn is a step toward it. And I don’t want the impact to stay “up in space.” If we can create robots reliable enough for harsh environments, we can also help people on Earth—search-and-rescue technology, safer construction, and assistive robotics for the elderly and disabled. On campus and in my community, I also want to be the person I needed when I first arrived: someone who mentors students who feel alone, who shows them how to build structure, and who tells them it’s okay to ask for help. Legacy is the future you leave behind in people—confidence, access, and possibility. My upbringing gave me the urgency. STEM gives me the tools. And I plan to use both to break cycles, not repeat them.

I’ve had a lot of “normal” goals—good grades, a good internship, a stable life. But the thing I keep coming back to is bigger and honestly a little crazy: I want to help build the kind of humanoid robots that could make a civilization on Mars possible. I know that sounds like science fiction. But for me it’s not about a fantasy—it’s about building something real, step by step, until it stops being a dream and starts being a plan. I’m studying AI at Illinois Institute of Technology, and every time I learn a new concept—algorithms, data structures, math for machine learning—I see it as another brick in the foundation. I’m also interested in physiology and neuroscience because intelligence isn’t just “thinking.” It’s sensing, moving, adapting, and staying stable when the environment is unpredictable. If a robot is going to walk, use tools, and survive harsh conditions, it needs both a brain and a body that works. The project I want to build long-term is a pathway into embodied AI: robots that can operate in the real world, not just on a screen. Mars is the extreme challenge—dust, distance, limited resources, risk everywhere. If we can build systems that can construct habitats, repair equipment, and assist humans there, we’ll also create technology that helps people on Earth. The same kind of robotics could support search-and-rescue teams, reduce dangerous labor, and improve independence for people with disabilities or the elderly. This goal is personal for me too. When I first came to the U.S. as an international student, I went through a period where everything felt unstable—being far from family, adapting to a new place, and trying to prove I belonged here. I didn’t fix that overnight. What helped was building structure: training consistently, studying with discipline, and setting goals that gave me direction even on hard days. I want to build a future where my education turns into impact—where my work helps people live safer, longer, and with more possibility. Mars might be far away, but the skills and the mindset needed to reach it can improve lives right now. That’s what I’m building.

When I first came to the United States, I realized how deeply language is tied to identity—not just what people say, but how we recognize them. Back home, I could tell who was speaking almost instantly from their voice and rhythm, even before I processed the words. In the U.S., that instinct kept glitching. I would hear a familiar tone that reminded me of Azerbaijani or Turkish, and my brain would expect my native language—then the person would continue in English. It sounds small, but it was one of my first real challenges: retraining my ear, my confidence, and the way I connected to people. That experience taught me that being bilingual isn’t just speaking multiple languages; it’s learning multiple ways of listening, thinking, and belonging. My first language is Azerbaijani, and I also speak Turkish and English. Each language carries its own “dictionary,” but not just of words—of history. Language is a bridge to a nation’s culture, literature, and habits built over centuries. Azerbaijani connects me to family stories, humor, and the emotional warmth of home. Turkish connects me to a wider world of shared roots, expressions, and media, and it taught me how similar ideas can be shaped differently across cultures. English, especially in the U.S., has become the language of my education and future career, and it pushes me to be clear, direct, and confident even when I’m still translating thoughts in my head. The benefits of being bilingual (and in my case, trilingual) show up in daily life. I can switch perspectives quickly because I’m used to switching frameworks. Even simple concepts—respect, ambition, pride, hospitality—can feel different depending on the language you’re thinking in. That flexibility has made me more open-minded and better at communication. When you learn multiple languages, you also learn that people don’t just “say” things; they mean things in ways shaped by their background. Being multilingual trained me to listen for meaning, not just vocabulary, and that skill helps me connect with people from different cultures without assuming my way is the only way. There are challenges too. The biggest one has been recognition and confidence in social settings. In English, voices can blend together for me in a way they never did back home, especially in busy classrooms or group conversations. I had to rebuild a skill I used to rely on automatically. Another challenge is expressing emotion. In Azerbaijani and Turkish, I can communicate feelings naturally, with the exact phrases that match the moment. In English, I sometimes feel like I’m choosing words more carefully, like my personality has to take a second to “load.” But over time, I’ve learned that this isn’t a weakness—it’s a form of growth. It has made me patient with myself and more thoughtful when I speak. Post-graduation, I plan to work in technology, specifically AI, because I want to build systems that understand humans better. Language shaped my curiosity about how people think, and AI is the field where that curiosity becomes practical. Long term, I hope to become both a scientist and an entrepreneur: someone who builds technology and also builds opportunities for others. Being trilingual has shown me that bridges matter. I want my future work to do the same—connect people, cultures, and ideas that might otherwise stay separate.

I love math because it rewards the way my brain naturally works: pattern recognition. When I look at a problem, I’m not just trying to grind through steps—I’m searching for structure. Symmetry, hidden constraints, a repeated idea under a different disguise. A lot of the time, I’ll spot a shortcut that turns a long solution into something clean and simple. Sometimes I’ll even bring it up in class and realize my professor hadn’t noticed that specific path. That feeling is discovery,rather than ego. It feels like finding a secret door in a maze. What I enjoy most is that math teaches you to trust logic over noise. If an answer is right, it’s right for a reason, and you can trace that reason clearly. That clarity matters to me, especially as someone studying AI. The more I learn about linear algebra, probability, and optimization, the more I see that “smart thinking” in AI is really mathematical thinking: finding the simplest explanation, the best direction, the most efficient solution. Math also taught me persistence. I’ve had problems where my first instinct was wrong, but instead of giving up, I learned to reframe the question and hunt for the pattern I missed. Over time, that built confidence: not the loud kind, but the steady kind that comes from knowing I can sit with something difficult until it opens up. To me, math is more than numbers. It’s a way of seeing—finding order inside complexity—and I love it because it makes hard challenges feel solvable, one elegant insight at a time.

I’m going into the field of Artificial Intelligence with a focus on robotics, because I’m drawn to one question that sits at the edge of astronomy and engineering: how do we turn other planets from distant objects in the sky into places humans can actually live? When I look at Mars, I don’t only see a red dot or a set of photos from rovers. I see an environment with harsh physics—radiation, dust, low gravity, temperature extremes—and I think about the tools we would need to build a civilization there. That is why I’m interested in a career connected to astronomy: space is not only something to observe; it’s something we’re beginning to explore, map, and eventually inhabit. My specific goal is to help develop humanoid robots for Mars that can build infrastructure before humans arrive and support humans once they do. To me, the most exciting part is autonomy. A robot on Mars can’t rely on constant instructions from Earth, because communication delays and mission risk make “remote control” unrealistic for complex construction. The intelligence has to live inside the machine—perceiving the world, making decisions, correcting mistakes, and adapting to conditions that are unpredictable. That idea of embodied intelligence—the “brain” living in the robot’s own body—feels like the natural next step in space exploration. This is also why I find astronomy inspiring. Astronomy teaches humility: the universe is huge, and our planet is small. But it also teaches curiosity and patience, because progress in space has always been built through careful measurement and long-term thinking. Mars research combines both: we study it through data, images, and models, then convert that knowledge into missions, machines, and real-world systems that survive outside Earth. In ten years, my ideal job is to be both a scientist and an entrepreneur working on space robotics. I want to be in a role where I’m doing real research—improving perception, planning, and decision-making for robots in extreme environments—while also building a company that turns those breakthroughs into products. I imagine leading a small team that develops construction-capable robotic systems and tests them in Earth analog environments (deserts, volcanic terrain, cold regions) before scaling toward partnerships in the space industry. I want my work to live in both worlds: the scientific world of experiments, papers, and validation, and the entrepreneurial world of building something that can actually deploy and solve problems. Ultimately, my interest in astronomy is tied to impact. Space exploration has always pushed humanity’s limits, but the next era will require more than rockets and cameras—it will require autonomous builders. If I can contribute to that future—robots that help create safe habitats, repair systems, and build the first foundations of off-world civilization—then I’ll feel like I didn’t just study the universe. I helped humanity step into it.

When people my age talk about mental health, it’s usually because we’ve seen how quickly life can go from “I’m fine” to “I can’t keep up.” Between academic pressure, social media comparison, financial stress, and constant uncertainty about the future, a lot of students carry heavy feelings in silence. Suicide prevention matters because those silent moments are often the most dangerous—when someone looks “normal” on the outside but feels completely disconnected on the inside. I understood that personally when I first arrived in the U.S. Coming from Azerbaijan, I was excited to study and build a new life, but the emotional reality hit hard. I was far from my family, far from my familiar routines, and suddenly everything required extra effort—language, culture, friendships, even simple daily tasks. I went through a period of heavy depression. It wasn’t dramatic in a movie way. It was more like waking up tired, losing motivation, and feeling alone even in a crowded campus. The hardest part was that I didn’t want to worry my family back home, so I kept a lot to myself. Looking back, that’s one reason suicide prevention is so important: isolation can make people feel like they’re a burden, when the truth is they’re just overwhelmed and need support. That experience reshaped my beliefs. I used to think mental health was mostly about mindset—“be strong, push through.” Now I see it more like physiology: your brain and body are systems, and systems can get overloaded. That’s part of why I take physiology courses at IIT. I want to understand humans better, not just as emotions, but as biology—sleep, stress hormones, nutrition, nervous system regulation, and how environment affects behavior. Learning the science doesn’t remove the pain, but it gives it context. It helps me treat mental health with respect instead of judgment. It also changed my relationships. I became more intentional about checking on people, especially the quiet ones who always say “I’m good.” I learned that supporting someone doesn’t require perfect advice—sometimes it’s consistency: showing up, listening without trying to “fix” them, and encouraging them to use real resources when things get heavy. I also learned to be more honest myself. Depression taught me that acting tough doesn’t solve anything if you’re collapsing privately. My hobbies reinforced that lesson. I train weighted calisthenics (streetlifting), and the gym taught me a simple truth: progress requires recovery. If you overload your body with no rest, you get injured. The mind works similarly. Discipline matters, but so does sleep, routine, community, and asking for help early—before you hit a breaking point. Finally, this experience influenced my career aspirations. I study AI because I’m drawn to building intelligent systems, but I’m also aware of how technology affects mental health—attention, comparison, loneliness, and algorithm-driven stress. I want to build tools responsibly, with empathy. Whether I’m working on robotics, intelligent assistants, or future systems that interact with humans, I want mental health to be part of the design conversation, not an afterthought. Mental health and suicide prevention matter because people my age are often high-functioning on the outside while struggling inside. My own experience taught me that support works, science helps, and silence is not strength. If we treat mental health seriously—like we treat physical health—we can save lives and build a generation that doesn’t have to suffer alone.

I’m an international student from Azerbaijan studying at Illinois Institute of Technology, and technology has been my main way of turning ambition into something real. Moving to the U.S. for college taught me quickly that success isn’t only about having a dream—it’s about building systems: learning fundamentals, creating projects, and improving through feedback. I started in Computer Science and later shifted into Artificial Intelligence because AI made the “why” behind technology feel stronger to me. I’m fascinated by how machines can learn patterns, make decisions, and adapt—not as a magic trick, but as engineering. The part of the field I find most interesting is where software meets the real world: machine learning, computer vision, and ultimately embodied intelligence. Long-term, I’m drawn to robotics and autonomous systems—technology that can perceive an environment and act safely inside it. Outside of classes, I spend most of my time building. One of my main personal projects is an AI-driven “vision board” concept (DaydreamForge), where the goal is to generate personalized images and plans that help users stay consistent with long-term goals. It pushed me to think like both an engineer and a product builder: collecting user inputs through online forms, connecting back-end logic through Python/Flask webhooks, organizing assets through image hosting, and integrating AI image generation tools into a pipeline that produces consistent results. I enjoy the process of taking an idea from “concept” to something usable, then iterating when the first version breaks. My coursework has also strengthened my foundation in object-oriented design and data structures, which I consider essential. AI projects look exciting, but they only scale when the engineering underneath is clean. Learning how to structure code, debug, and design systems that are maintainable is what makes bigger goals possible. As an extracurricular, I train weighted calisthenics (streetlifting). Even though it’s a sport, I approach it like an engineering problem: track performance, analyze trends, adjust variables, and improve through consistency. I log my lifts, experiment with programming, and treat progress as a long-term system rather than random effort. That mindset carries into technology—both require patience, measurement, and iteration. I’m not currently part of formal clubs, but I constantly look for ways to learn through projects and community—online spaces, feedback from classmates, and self-directed building. Technology interests me because it rewards curiosity and persistence. My goal is to keep strengthening my fundamentals, keep shipping real projects, and eventually contribute to intelligent systems that make a meaningful impact in the real world.

In sixth grade in Azerbaijan, I said something out loud that sounded unrealistic even to me: I wanted to study in the United States. I didn’t have a clear map for how to get there, and my family didn’t have the kind of money that makes big dreams feel “safe.” What I did have was a belief that education could be a compass—if I learned enough, I could earn a different future. In Azerbaijan, school ends at 11th grade. When I graduated and started preparing seriously for U.S. admissions, the first thing I felt was time pressure. Many universities had deadlines only a few months away. I didn’t have a year to prepare with a strong system behind me. I had roughly two months to prepare for the SAT/TOEFL and about a month to apply, send scores, and deal with evaluation timelines. It wasn’t just “study hard.” It was “study smart, fast, and consistently.” The hardest part wasn’t motivation. The hardest part was support—especially for English. My school had close to no English classes that could actually prepare me for standardized tests or college-level reading and writing. There wasn’t meaningful government guidance for students like me. So I built my own structure. I self-studied daily and treated practice tests like training. I used tests from one year prior and sometimes from as far as ten years back. I would take a full test, review every mistake, and then redo similar questions until I could explain the logic instead of guessing. Math was the most efficient section for me because it rewarded method and repetition: if you understand the structure, improvement shows quickly. English required a different kind of training, and that’s where my tutor changed everything. From our first meeting, she told me something I didn’t expect: I didn’t need more time—I needed direction. She could see that I had the ability, but I needed the right strategy and practice format. She was a beast. She took old materials with massive 2000-word passages and tailored them into sharp 150-word extracts, then wrote her own questions. That sounds small, but it mattered a lot. It made practice realistic for exam conditions, helped me build speed, and kept me from getting lost in length while I was still strengthening comprehension. That work turned into measurable results: a 1510 SAT and a 102 TOEFL, plus other proficiency tests. But scores were only half the battle. My household income was low, and I never forgot that every application fee and deadline carried real risk. I couldn’t treat this like a “try again next year” plan. If I chased this dream and came back with nothing, it would be a disaster for my family. So I made decisions that were realistic as well as ambitious—decisions that kept the dream alive without gambling our future. When I was admitted to Illinois Institute of Technology, I accepted with mixed feelings. It wasn’t my dream university, and I won’t pretend it was. But it was a real door into the U.S. education system—and for someone from my background, a real door matters more than a perfect one. It meant momentum. It meant I wasn’t wasting all the sacrifice already being poured into this goal. The person I think about most when I talk about sacrifice is my father. People love the phrase “self-made,” but I don’t believe in it. I did the studying, but my father carried a pressure I didn’t fully understand at the time: money, uncertainty, and the fear of making one wrong move. While I was taking practice tests and rewriting mistakes, he was working, worrying, and staying up late. My knowledge plus his sleepless nights added up to my chance to be here. He used his effort like a bridge—helping me climb from a low place in society toward a future he believed I could reach. Coming to the U.S. didn’t remove difficulty; it changed it. I had to adjust to a new culture, a new academic environment, and the reality of being an international student who can’t waste time or resources. But education gave me what I wanted since sixth grade: direction. It taught me that big goals aren’t reached through one perfect moment; they’re built through structure, consistency, and learning through pressure. Now I’m an AI student (I originally started in CS), and my goals have become more ambitious and more specific. I’m drawn to embodied intelligence—systems that can perceive, reason, and act in the real world. Long term, I want to work on humanoid robotics for extreme environments, including off-world construction. I imagine robots that can build and maintain infrastructure when humans can’t be there, with intelligence that works on-board instead of relying on constant connection. That dream forces me to take fundamentals seriously: algorithms, software engineering, perception, safety, and decision-making under uncertainty. I also want my education to create a better future for others. I know what it feels like to be talented but under-supported. In the future, I want to mentor students from backgrounds like mine—sharing resources, strategies, and honest guidance about tests and applications—so the path is clearer for someone else than it was for me. Education has shaped my goals, but it has also shaped my responsibility. My father didn’t sacrifice for me to treat college casually. I want to make my parents proud through consistency: learning deeply, building skills that matter, and turning opportunity into impact. I started with a dream in sixth grade. Now I’m turning that dream into work, one step at a time.

When I switched from Computer Science to Artificial Intelligence, it wasn’t because I stopped liking CS—it was because I found a goal big enough to organize everything around it. My computer science and AI goal is simple to say but hard to build: I want humanoid robots on Mars that can create civilization for us—structures, habitats, cities, and the systems that keep them running. Not just remote-controlled machines, but robots with real autonomy and intelligence. What excites me most is the idea that intelligence shouldn’t only live “in a headquarters.” I imagine a robot that carries its own brain the way humans do—on-board, embodied, and capable of reasoning in real time. A mind that doesn’t depend on constant connection, because on Mars latency and communication limits are real. In my head, it’s like moving from “a model in the cloud” to “a brain in a body.” That’s what makes the problem feel alive: perception, movement, decision-making, failure recovery, and learning from messy environments where the rules aren’t clean. To get there, my CS/AI goals are practical. I want a deep foundation in algorithms and data structures so I can build systems that don’t fall apart under pressure. I want strong software engineering skills so I can ship reliable code, not just prototypes. And I want to specialize in AI areas that matter for robots: computer vision to understand terrain and objects, reinforcement learning to improve behavior through experience, and robotics fundamentals like control and planning so the robot can move and build safely. On Mars, “close enough” isn’t enough—mistakes break hardware, waste resources, and can cost years of work. That forces you to be serious. My non-computer science goal sounds completely different, but it comes from the same mindset: I want to become a professional streetlifter. Streetlifting is a sport built around weighted calisthenics—pull-ups, dips, and raw strength with your body as the base. I train because it teaches me discipline when motivation disappears. It also teaches me something I think engineers forget: your body is a system too. Progress requires consistency, recovery, and respecting constraints. If you ignore physics, your shoulders remind you. If you rush progress, your tendons complain. Strength is earned through small reps, not fantasies. In the future, I want to combine these goals by bringing an athlete’s discipline into my engineering life—and by using my technical skills to improve performance and robotics at the same time. I’m interested in building tools that track training, analyze movement, and reduce injury through feedback—computer vision for form analysis, data-driven programming, and eventually biomechanics-aware systems. The same logic that helps a robot plan safe movement could help a person train smarter. And the consistency I build through streetlifting is the same consistency I’ll need to solve a problem as huge as building autonomous humanoids for Mars. To me, AI is not just a major. It’s a direction: build embodied intelligence, build durable systems, and become the kind of person who can handle long projects—whether that’s adding weight to a dip belt, or helping humanity build a future off Earth.

The first time I noticed my uncle’s war was not in a speech or a medal—it was in the way he moved his wrist. If you didn’t know what to look for, you’d miss it. But when he reaches for a glass or turns a key, there’s a small stiffness, like his body is remembering something his face refuses to dramatize. During the First Nagorno-Karabakh War, a mortar shell exploded near him. He survived, but shrapnel lodged in his wrist and calf. Doctors warned about possible nerve damage. Somehow, he kept going. Thirty years later, those fragments are still there, like tiny pieces of history he carries quietly. And the wild part is: if you met him today, you’d call him fully healthy—strong, active, and strangely calm. That calm is what I’ve always associated with him. He doesn’t talk about the war like a movie scene. He talks about it the way people talk about weather—something that happened, something serious, something you live through. He’ll mention the injuries casually, then immediately ask if I’ve eaten, if I’m studying, if I’m taking care of myself. To him, survival isn’t something to brag about; it’s something to honor by living well. Watching him has taught me that resilience isn’t loud. It’s consistency. It’s waking up, doing your job, caring for your family, and refusing to let the worst day of your life become your entire identity. But my uncle also has a sense of humor that catches you off guard. One of my favorite stories—because it sounds unbelievable until you realize it’s exactly his personality—happened long after the war. He was with a friend who started teasing him in a dark way, blaming him for “all the consequences” since the war was lost. The joke wasn’t just annoying—it hit a nerve. My uncle was holding a firework at the time, and in a moment of pure anger (and honestly, probably a flash of old trauma too), he launched it straight toward his friend. Before anyone imagines something dangerous, I need to say this clearly: nobody was hurt. The story is funny in the way you laugh after your heart stops for a second—like, “Are you serious?” His friend jumped back, everyone shouted, and then the whole group just stood there staring at each other while the flame burned out. It wasn’t a heroic moment. It was a human moment: a reminder that people don’t just “move on” from war because time passes. The body might heal, but the mind keeps its own record. What I learned from my uncle is not how to fight, but how to live with what you’ve survived—and how important it is to handle pain responsibly. He’s proof that you can carry scars and still build a steady life. That lesson matters to me as I pursue higher education, because college isn’t only about intelligence; it’s about pressure, setbacks, and learning to respond without losing yourself. When things get hard, I think of my uncle—calm, stubborn, and still moving forward—and I remind myself that strength is not what happens in one dramatic moment. It’s what you choose every day after.

People usually call me quiet. And sometimes that’s true—I’m naturally observant, and I don’t feel the need to fill silence just to prove I’m present. But there’s another side of it that’s harder to explain: around strangers, my silence can feel less like a choice and more like a barrier. With people I know well, conversation is normal. I can joke, ask questions, and express myself without thinking about it. But with strangers, I often freeze up. My mind starts running fast: what if I say something awkward, what if my accent or wording comes out wrong, what if they misread my tone. In that moment, I’m not lacking thoughts—I’m overloaded by them. So I default into observation. I listen closely, I read the room, and I stay quiet longer than I want to. This has shown up in everyday situations that seem small to most people: introducing myself, starting a conversation in class, asking someone for help, speaking to new teammates, even ordering food when I’m not completely comfortable. There were times I walked away thinking, “Why didn’t I just speak?” The answer isn’t simple. Sometimes it really is anxiety. Sometimes it’s me trying to be careful, trying not to make a mistake with someone I don’t know yet. But either way, it has affected how connected I feel in new environments. At the same time, this experience has shaped strengths I value. Being the person who observes first has made me a better listener and a better thinker. I tend to notice patterns—who’s included in the conversation, what’s left unsaid, how people react to certain topics. That kind of awareness matters, and it’s part of why I’m pursuing my major in Artificial Intelligence. I recently changed my major from Computer Science to AI because I’m drawn to how systems learn, how data becomes decisions, and how technology can be designed to support real human needs. AI isn’t just code to me—it’s a way to solve problems that affect people’s daily lives. Pursuing higher education is important to me because it’s not only about knowledge; it’s about becoming more capable and more confident. College forces you into situations where growth is required: presentations, teamwork, networking, interviews, and asking questions when you don’t feel ready. Those are exactly the environments that challenge me the most, especially with strangers. But I see that as a reason to keep going, not a reason to step back. I’m already working on it in small ways—starting conversations even if it’s just a simple question, pushing myself to speak once in group settings, and reminding myself that I don’t have to sound perfect to be understood. I’m still learning what my quietness means—whether it’s anxiety, caution, or both. What I know for sure is that I’m committed to stepping forward. I want to build a future where I can keep my thoughtful nature while also building the confidence to speak when it matters. Higher education is how I’m doing that, one situation at a time.

For most of my life, I viewed healthcare as something that reacted to problems rather than prevented them. People went to the doctor when something was already wrong, and treatment focused on managing symptoms instead of addressing underlying risk. As I began studying computer science and exploring health data, I realized how costly and inefficient this reactive model is. This realization is why the Schlosser Healthcare Risk Equilibrium Scholarship is meaningful to me: it aligns with my belief that healthcare should focus on early, measurable risk reduction rather than late-stage intervention. One healthcare challenge I am particularly interested in addressing is the underutilization of cardiorespiratory fitness, specifically VO₂ max, as a core health metric. VO₂ max measures the body’s ability to use oxygen efficiently and is one of the strongest predictors of cardiovascular health and overall mortality. Despite its importance, it is rarely tracked in routine healthcare settings. Instead, providers often rely on indirect or less predictive markers such as BMI or isolated lab values. This creates a gap where individuals may appear “healthy” on paper while silently accumulating long-term cardiovascular risk. From a risk equilibrium perspective, VO₂ max plays a critical role in how health risks propagate through a system. Low VO₂ max increases the likelihood of cardiovascular disease, which in turn raises the probability of hospitalization, medication dependence, and long-term healthcare costs. These risks do not exist in isolation; they influence one another over time. Improving VO₂ max through structured aerobic training can shift this balance. Even modest improvements can reduce downstream risks, creating a stabilizing effect across the broader healthcare system. Using computational methods, this process can be modeled as an interconnected risk network. Physiological indicators such as VO₂ max, resting heart rate, and activity levels can be represented as nodes, with weighted relationships that describe how changes in one metric affect overall health risk. Iterative updates—driven by wearable data and training feedback—allow risk estimates to evolve over time. As VO₂ max improves, predicted cardiovascular risk decreases, which in turn lowers expected long-term healthcare utilization. This type of model reflects the idea of healthcare equilibrium: small, early interventions leading to disproportionately large systemic benefits. What excites me most is the practicality of this approach. Wearable devices already collect the data needed to estimate VO₂ max trends without expensive lab testing. Machine learning models can personalize training recommendations, ensuring individuals improve safely and sustainably. This makes preventive care accessible, scalable, and cost-effective. Instead of waiting for disease to emerge, healthcare systems could identify rising risk early and guide individuals toward meaningful lifestyle interventions. Looking forward, I plan to continue using my technical background to develop tools that connect data, physiology, and preventive healthcare. By treating fitness metrics like VO₂ max as dynamic risk signals rather than optional performance measures, we can move toward a more balanced and proactive healthcare system. This scholarship represents an opportunity to support that vision—one where technology helps maintain health, not just manage illness.

Success didn’t start for me with a perfect plan—it started with a moment of embarrassment. During my first semester in the U.S., I went to office hours with a question I had rehearsed in my head. When it was my turn to speak, my words came out in the wrong order, my pronunciation felt heavy, and I could see the confusion on my face before it reached the professor’s. I left the room thinking, If I can’t explain a simple question, how am I going to succeed here? That experience became one of the most important turning points in my education. Inside the classroom, my success has been built through structure and repetition. As an AI major at Illinois Institute of Technology, I have learned to solve problems by breaking them down into smaller parts—whether it’s debugging a Java program, understanding data structures, or working through a math concept that doesn’t click at first. The classroom taught me how to learn: how to stay calm when I’m stuck, how to test ideas, how to accept feedback, and how to try again without taking mistakes personally. Over time, “failure” stopped feeling like a wall and started feeling like information. Outside the classroom, my growth has been just as intense, but in a different way. Being an international student means you’re constantly translating—language, culture, expectations, humor, even the unspoken rules of how people interact. At first, I felt like I was watching life through glass: I understood enough to function, but not enough to feel fully included. I pushed myself to speak even when I felt awkward, to ask classmates for clarification instead of pretending I understood, and to join conversations instead of staying silent. Those choices were uncomfortable, but they slowly built confidence. Learning a foreign language has also changed how I connect to others. It made me a better listener. When English is not your first language, you pay attention differently—you notice tone, expression, and intention. You learn that communication is not just vocabulary; it’s patience and effort from both sides. Because I’ve been the person searching for the right word, I’ve become more empathetic when others struggle. I’ve also learned to appreciate small moments: a classmate explaining something slowly without judgment, a joke I finally understand, or a conversation where I can be myself without overthinking each sentence. This has made me stronger academically and socially. In group projects, I’ve learned to speak up clearly and ask direct questions. In everyday life, I’ve learned how to build trust across differences. Most importantly, language gave me a bridge to belonging. It helped me move from simply “studying” in a new country to actually living in it—forming friendships, collaborating, and contributing. My experiences inside and outside the classroom work together: school taught me discipline and problem-solving, while life as an international student taught me resilience, humility, and connection. Learning a foreign language didn’t just help me communicate—it helped me grow into someone who can adapt, collaborate, and succeed in any environment.