1. I would describe myself as an explorer who is willing to step into unfamiliar environments, even when I feel uncertain, and keep moving forward one small step at a time. As an immigrant and a woman pursuing a career in technology, my experiences have given me a unique perspective on both my strengths and the areas where I continue to grow. Moving to the United States was one of the most challenging transitions of my life. I had to adapt to a new language and a different educational system. I also had to adjust to an unfamiliar culture while helping my family navigate our new environment. Through this process, I developed resilience, adaptability, and confidence. My interests in research and painting reflect my curiosity and creativity. Most importantly, I have learned that rejection is not failure. It is an opportunity to learn and keep growing. 2. Living and studying in a culture different from the one I grew up in has taught me that “different” does not mean “wrong.” Every culture offers valuable perspectives, and understanding those differences has helped me become more open-minded. In my home culture, humility and attentive listening are highly valued. These principles taught me to respect others’ ideas and perspectives. In the United States, I learned another important lesson: to respect my own voice. I discovered that sharing ideas, asking questions, and speaking confidently are all vital in learning and leadership. One experience that reflects this growth was my decision to become a lab instructor. Teaching technical material in my second language initially felt intimidating. I worried about making mistakes and whether I could communicate effectively. However, remembering the support I had received from my own instructors, I embraced the challenge. What began as a source of anxiety became one of the most rewarding experiences of my academic journey. It strengthened my communication skills and allowed me to help other students succeed. 3. My educational journey has taught me that empathy is important in developing technology. As I moved between cultures and communities, I realized that people’s experiences shape their opportunities and challenges. Technology can only serve society effectively when it is designed with diverse perspectives in mind. One of the most meaningful experiences in my growth was presenting my research at Scientific Research Day. I shared my work on using machine learning to detect AI-generated artwork and discussed its implications for digital authenticity. Several visitors told me that my research was meaningful and encouraged me to continue. Their support gave me the confidence to see the value of my contributions and inspired me to pursue graduate studies. That experience reinforced an important lesson: when we share our work and ideas, we can create impact beyond ourselves. 4. My academic interests in machine learning are closely connected to my goal of creating technology that is fair, trustworthy, and beneficial to diverse communities. Throughout my education, I have faced challenges including limited resources, balancing work and school, and financial constraints. These experiences strengthened my determination and taught me how to seek opportunities, take initiative, and persevere. I plan to pursue a Master’s degree in Machine Learning at Carnegie Mellon University, where I hope to deepen my expertise in equitable and interpretable AI systems. My long-term goal is to develop technologies that address real-world challenges while ensuring underrepresented communities are not overlooked. Receiving this scholarship would reduce the financial burden of my education and allow me to focus more fully on research, leadership, and community impact. It would not only support my academic journey but also help me create positive change through technology.

As a computer science student, I have always been interested in how technology can shape society and influence creative industries. While many people view computer science as purely technical, I see it as a field that combines innovation, problem-solving, and responsibility. My passion for both technology and art inspired me to pursue a research project focused on detecting AI-generated artwork, a topic that became increasingly important with the rapid growth of generative AI tools. When I entered college, I noticed growing concerns among artists whose work and styles were being imitated by AI systems without consent. Generative AI demonstrated incredible technical advancement, but it also raised ethical questions about authenticity and the protection of creative work. Rather than viewing technology as the problem itself, I became interested in how technology could also provide solutions. This motivated me to conduct my first undergraduate research project on identifying AI-generated images using machine learning techniques. The project introduced me to the practical side of artificial intelligence and computer vision. I explored how machine learning models analyze image patterns, textures, and inconsistencies that may not be immediately visible to the human eye. I learned how datasets are collected and processed, how training and testing models work, and how image classification systems can distinguish between human-created and AI-generated artwork. Through this experience, I strengthened my programming and analytical skills while gaining a deeper understanding of how artificial intelligence systems are designed and evaluated. One of the most rewarding aspects of the project was learning how technical research can address real-world issues. Before this experience, I viewed programming mainly as writing code to solve computational problems. However, my research taught me that technology also has social consequences, and engineers play an important role in shaping how these technologies are used. Detecting AI-generated artwork was not simply a technical challenge; it was also about protecting artistic integrity and encouraging ethical innovation. This perspective changed the way I approach computer science and inspired me to think critically about the broader impact of emerging technologies. Presenting my research poster during research week was another important milestone in my academic journey. Explaining my work to professors, students, and visitors challenged me to communicate complex technical concepts clearly and accessibly. Many people expressed interest in the topic and encouraged me to continue the research. Their feedback gave me confidence in my abilities as both a researcher and a future engineer. More importantly, it showed me that technology research can foster meaningful discussions and help solve contemporary challenges. Working in technology inspires me because the field is constantly evolving and creating opportunities to make a difference. Computer science allows me to combine technical problem-solving with creativity and critical thinking. I am especially inspired by areas such as artificial intelligence and machine learning because they have the potential to transform industries, improve accessibility, and solve complex global problems when developed responsibly. At the same time, my experiences have taught me that innovation must be guided by ethical considerations and respect for the people affected by it. The Chadwick D. McNab Scholarship represents values that strongly resonate with me: growth, progress, and dedication to using technical skills to positively impact others. Through my education and future career, I hope to continue researching ethical applications of artificial intelligence and contribute to building technologies that support both innovation and human creativity.

I relate deeply to the challenges Maggie faced as an international student navigating life in a new country. Moving to the United States for education is not only a cultural transition but also an emotional and intellectual one. It means adjusting to unfamiliar systems, overcoming language barriers, and building a support network from nothing, all while keeping up academically. As an immigrant, I successfully navigated this journey firsthand. My family’s fourteen-year immigration process required resilience in the face of uncertainty, and I quickly adapted upon our move. Arriving in the U.S., I confidently confronted a high school curriculum taught entirely in English. While I encountered challenges with language and unfamiliar resources, I focused on learning quickly and embracing every opportunity compared to my peers. Through the motivation to overcome these challenges to gain new knowledge, I learned to adapt quickly. By humbly asking teachers and classmates for help, I built meaningful relationships and gradually gained the confidence to express myself. These experiences strengthened my resilience and taught me the importance of community and persistence. Like Maggie, I am driven to push beyond my comfort zone and focus on the meaningfulness of exploration that is driven by my curiosity. One of the decisions I made was to become a lab instructor. At first, the idea of teaching complex material in my second language felt intimidating. However, inspired by the support I once received from my own instructors, I chose to take on the challenge. What began as a daunting step turned into a transformative experience where I not only reinforced my own knowledge but also helped others succeed. Besides that, I also decided to continue my pursuit in my academic journey, that answering my curiosity and questions through the journey, as becoming a Master’s in Machine Learning at Carnegie Mellon University, which will be very challenging, but I believe it will bring me new experiences and continue my exploration to assist me in achieving my goal as using inputting my own vision into how to make technology to be ethical. Maggie’s determination, curiosity, and resilience resonate deeply with me. I commit to facing challenges with courage, pursuing continuous learning, and contributing to the communities. Like Maggie, I view every obstacle as an opportunity for growth, and I am dedicated to using my journey to empower and uplift others. I believe that by doing so, I can create lasting positive change both for myself and those around me.

Machine learning is the field of STEM that most excites me because it combines mathematical foundations with meaningful real-world applications. I am drawn to how models can learn patterns from data and apply them across domains such as art, healthcare, and communication. In particular, I am interested in how AI interacts with creative work, as generative models raise important questions about artistic ownership and fairness. As this technology continues to advance, I believe it is critical to ensure that it is developed responsibly and with awareness of its impact on human creativity and society. My academic and research experiences have focused on exploring these challenges. Through an independent study, I conducted research on detecting AI-generated artwork. I presented my findings through conference and research posters to highlight the importance of verifying the authenticity of digital art. In addition, I served as a workshop ambassador and project lead for the Responsible Computing Club. In this role, I organized workshops on topics such as facial recognition bias and disparities in speech recognition systems. I also worked on a machine learning–based bias detection tool designed to promote transparency in data and model behavior. These experiences strengthened my understanding of both the technical and ethical dimensions of STEM, and reinforced my commitment to building systems that are both innovative and socially responsible. I am committed to ensuring that AI and machine learning serve as tools that empower human creativity rather than exploit it. By reducing bias, enhancing interpretability, and improving accountability, I want to help build AI systems that can be integrated into society in ways that support innovation, safety, and fairness. I have faced adversity in my academic journey, including limited research resources, balancing school and work, and managing financial constraints. I have also worked to find a field that matches my skills and long-term interests. To address these, I sought independent research, took leadership roles in STEM, and applied for scholarships to support my education. In my lifelong journey of exploration, I aim to continuously grow, build meaningful connections with more people, learn from others, and ultimately achieve my goals. Overall, my experiences in machine learning have shaped my commitment to using STEM as a tool to address complex global challenges. I hope to continue building on this foundation through advanced study, including a Master’s in Machine Learning at Carnegie Mellon University, where I plan to further develop my expertise in fairness and interpretability in AI systems.

My goal is to shape how intelligent systems behave in the real world through the study of Machine Learning. Long term, I aim to become a researcher focused on ethical AI, designing systems that reflect fairness and human-centered values. To prepare, I have taken advanced coursework and conducted research projects that deepen my understanding of its theories and applications. Through this work, I have grown increasingly curious about why certain architectures succeed and how theory can guide the development of more reliable models. I seek to bridge the gap between abstract algorithms and real-world impact, ensuring systems are both powerful and responsible. Beyond computer science, I am deeply committed to painting and visual art, which have shaped how I perceive patterns, emotion, and human experience. Art has strengthened my ability to recognize nuance and engage with meaning, and I believe creativity and logical understanding are uniquely human qualities that should be preserved and not diminished by technological progress. My interest in combining these fields stems from examining how AI interacts with creative work. As generative models advance, questions of authorship and artistic value have become more urgent. Many artists are concerned about the use of their work in training datasets without consent and the lack of legal protection against style imitation. These issues have shown me that technological development requires diverse perspectives, motivating my focus on the intersection of Machine Learning and art. During my undergraduate studies, I began my research under Professor Mark Stamp through an independent project on detecting AI-generated artwork. I built a complete Machine Learning pipeline, including dataset creation, preprocessing, training, and evaluation. This work explored how feature-based models can address challenges relevant to artists while clarifying my goal of developing solutions aligned with my values. In addition to research, I contributed to the Responsible Computing Club as a workshop ambassador and project lead. I organized workshops on facial recognition bias, disparities in speech recognition, and the misuse of artists’ work in datasets. I also led the development of a Machine Learning-based bias detection tool to promote transparency in data and model behavior. These experiences reinforced my commitment to building socially responsible systems. In the near term, I plan to pursue a master’s degree in Machine Learning at Carnegie Mellon University, strengthening my foundation in optimization, interpretability, and applied AI. By combining my technical background with my lifelong engagement in art, I aim to develop AI systems that scale responsibly and support rather than exploit human creativity.