teaching
I see teaching and mentoring as part of the same scientific responsibility: helping students build confidence, develop physical intuition, and learn how to turn difficult problems into manageable steps. Before beginning my Ph.D., I spent roughly twelve years teaching school students, which gave me a lasting appreciation for patient explanation, careful pacing, and meeting learners where they are.
Today, my teaching is closely connected to research training in high-energy physics. I work with students on analysis strategy, coding practice, statistical interpretation, presentation skills, and scientific writing, with the goal of helping them become independent researchers rather than only task-oriented contributors.
Mentoring
Research supervision
- At Purdue, I regularly discuss physics analysis ideas and research progress with a Ph.D. student working in a related area.
- My broader mentoring experience includes earlier supervision and research guidance of multiple graduate students during my time at IHEP and within CMS collaborations.
- These interactions typically focus on analysis strategy, coding practice, interpretation of results, and development of independent scientific judgment.
Instruction
Schools and hands-on training
- Instructor at the CMS Data Analysis School 2018 at Fermilab, contributing to tracking and vertexing, pileup and MET, and contact-interaction exercises.
- Instructor for Collider Physics Simulation and Event Generation at the SERC School for Experimental High Energy Physics, University of Delhi, in 2016.
- Longstanding experience explaining physics and mathematics to school-level learners before transitioning fully into research.
Teaching focus
My teaching style emphasizes conceptual clarity first, followed by practical implementation. In particle physics, students often encounter several layers of complexity at once: detector effects, reconstruction choices, simulation, statistics, and software workflows. I try to break these into smaller connected ideas, so that students understand not only what procedure to follow, but also why the procedure is appropriate.
I place particular value on training students to read papers carefully, question assumptions, document their work clearly, and communicate results to different audiences. These skills matter just as much as technical fluency in tools such as ROOT, Python, C++, machine learning frameworks, and CMS analysis software.
Outreach and broader engagement
Teaching for me also includes public communication and interdisciplinary outreach. I have given invited seminars on high-energy physics and artificial intelligence, including talks at Acharya Narendra Dev College, University of Delhi, and Shah and Anchor Kutchhi Engineering College. These experiences have strengthened my interest in connecting frontier collider physics with a broader student audience, including learners who are new to the field.