Before we dive in, let's explore my coding journey—a journey fueled by unexpected passion and transformative discoveries.

To be candid, I once harbored a disdain for computers, adamantly vowing against a career in computer science due to the dreaded stereotype of becoming a technical geek. But fate had other plans. During my undergraduate studies in logic, I had to take programming courses in Java, Python, and other computing basics. Surprisingly, I found much fun in programming and excelled at it.

But as a logic major, I dedicated half of my undergraduate journey to exploring logical systems. A highlight was my research project on "a logic of ought to know" which earned me a spot at the 16th National Conference on Modern Logic. However, as the initial excitement waned, I felt distressed realizing my work had no practical impact on everyday life.

This realization prompted a profound shift in my perspective. While I still cherished the realms of thought and creation, my true passion lies in leveraging technology to solve real-world problems. Fueled by this newfound passion, I embarked on a relentless quest to hone my coding skills, seizing every opportunity to pave a path aligned with my fervent aspirations. I take immense pride in applying what I've learned to help my mom build her company website, enabling her to reach a wider audience and attract potential customers.

Navigating the path to a master's degree in computer science without a bachelor's background in the field presented its own set of challenges. Yet, my hard work paid off with offers from prestigious programs such as the Master of CSE at the University of Notre Dame. After completing my master's degree with a 3.93 GPA, I was thrilled to continue my academic journey at Notre Dame.

Now, as a first-year PhD student in the DIAL Lab under the guidance of Prof. Nitesh Chawla, I'm diving deep into the fascinating world of Large Language Model reasoning. My research explores how to enhance the reasoning capabilities of foundation models, pushing the boundaries of what AI can achieve in complex problem-solving.