I’m a Master’s student in Computer Science at the University of Colorado Boulder, with a focus on Artificial Intelligence, Data Science, and Software Engineering. My academic and professional journey reflects a deep passion for building intelligent systems that bridge theory and application—especially in interdisciplinary domains like climate science, healthcare, finance, and automation.
My primary interests lie in deep learning, generative AI, AI agents, and automation. I’m particularly driven by the challenge of making AI systems not just powerful, but also interpretable, efficient, and adaptable to real-world constraints. Recently, I’ve been working on projects involving lightweight reinforcement learning-based summarization pipelines and zero-shot learning using CLIP and knowledge graphs, both designed to optimize performance without relying on black-box transformer models.
Technically, I’m fluent in Python, SQL, and Java, and have experience with tools and libraries such as TensorFlow, PyTorch, PostgreSQL, Power BI, Tableau, and Google Looker Studio. I’ve also worked hands-on with cloud services, XML data processing, and large-scale data systems. Whether it’s building custom ML pipelines, visualizing trends with Power BI, or automating repetitive workflows using AI, I thrive at the intersection of innovation and impact.
I’m actively exploring opportunities where I can apply my skills in data, AI/ML, and automation to solve real-world problems, contribute to mission-driven projects, and build systems that are as ethical as they are efficient.
I’m driven by curiosity, continuous learning, and a passion for building purposeful technology. I thrive in problem-solving environments where I can explore new ideas, experiment with AI systems, and push the boundaries of what’s possible. From refining deep learning architectures to exploring the ethical dimensions of AI, I enjoy translating knowledge into impactful, real-world solutions.
I aspire to work at the intersection of AI, data science, and intelligent automation, solving complex, interdisciplinary problems with scalable and ethical solutions. My goal is to build interpretable, lightweight, and impactful AI systems—from agents that automate workflows to models that make sense of noisy, real-world data. Whether in applied research, product development, or innovation labs, I want to contribute to AI that serves people and the planet.
Outside of code and research papers, I’m a big fan of balance. I unwind by tinkering with Notion setups, hitting the gym with new routines, playing laser tag, or disappearing into nature on a spontaneous hike. I love discovering new cuisines, exploring hidden travel spots, and fine-tuning the perfect Spotify playlist. Life, like code, is more fun when it's both structured and spontaneous.
To work on bold, creative projects that merge AI, automation, and human-centered design—whether in clean energy, healthcare, or a domain yet to be imagined. If it involves building smart systems that make a difference, I’m in.