teaching

Teaching has always been an immensely rewarding experience for me. I thoroughly enjoy engaging with students and exploring various topics together, while deepening our mutual understanding.

Throughout my teaching journey, I have delivered lectures to both undergraduate and graduate students on a diverse range of topics, including computational materials science methods, machine learning, and engineering thermodynamics. It brings me immense satisfaction to witness students’ “a-ha” moments as they grasp key concepts and form connections in their minds.

The importance of fostering appreciation for basic science and its crucial role in society cannot be understated. To this end, I strive to make my teaching accessible and engaging, ensuring that people from all walks of life can find meaning and recognize the value of supporting research.

ME 3322 – Engineering Thermodynamics (GTA)

My first experience as a Graduate Teaching Assistant has been nothing short of rewarding. I had the pleasure of working with over 50 students this summer, helping them learn about engineering thermodynamics. This role allowed me to lecture students, grade their homework and exams, hold weekly office hours, and develop notes that aid in their learning journey. Receiving recognition from the Georgia Tech Center for Teaching and Learning was an honor, and I eagerly look forward to a new semester of working with students and continuing this gratifying experience.

ME 3057 – Experimental Methods Laboratory (GTA - lab supervisor)

In this role, I supervised and guided students as they performed a series of lab tasks. My responsibilities also included grading their homework and lab reports, ensuring that they effectively learned and applied the principles of experimental methodology.

Computational Materials Science and Machine Learning Lecturer:

Serving as a lecturer in computational materials science and machine learning has not only allowed me to share my knowledge with eager students but has also contributed significantly to my growth as a researcher. Preparing and delivering lectures on topics such as Density Functional Theory (DFT), Molecular Dynamics (MD), and machine learning techniques challenged me to deepen my understanding of these subjects and stay up-to-date with the latest advances in the field.

Engaging with students and addressing their questions encouraged me to think critically and creatively about the subjects I taught. This experience has sharpened my problem-solving skills, enabling me to tackle complex research challenges with greater ease and confidence. Additionally, the process of breaking down complex concepts into digestible components for my students has improved my communication skills, allowing me to articulate my research findings more effectively to a broad range of audiences.

Ultimately, my role as a lecturer in computational materials science and machine learning has not only enriched the learning experience for my students but has also played a pivotal role in enhancing my abilities as a researcher in the field of materials science and engineering.