Teaching & Student Resources

As an Assistant Professor at UPES, Dehradun, I actively teach and mentor undergraduate and postgraduate students. My teaching philosophy emphasizes clarity, experimentation, and the integration of computation into modern physics education.

📘 Courses & Resources

1. Computational Techniques (B.Sc. Physics)

2. Introduction to Computational Physics Lab (Int. B.Sc. + M.Sc.)

3. Learning LaTeX

4. Computational Physics (M.Sc. Level)

5. Fundamentals of Astronomy (B.Sc. Physics)

6. Observational Astronomy Lab (B.Sc. Physics)

Topics include numerical integration, solving differential equations, Monte Carlo simulations, and the use of Linux, Fortran, C++, Gnuplot, and LaTeX.

📚 Courses Taught

  • Python Programming — Data structures, logic building, and scientific computing
  • Fortran Programming — Fundamentals and numerical applications
  • C++ Programming — OOP and scientific modeling
  • LaTeX for Science — Scientific writing and document preparation
  • Computational Physics — Numerical techniques in physics simulations
  • Machine Learning in Astronomy — Hands-on projects using real datasets
  • Astrophysics — Stellar evolution, variable stars, cosmology
  • Astronomy Laboratory — Observational techniques and simulations
  • Planetary Science — Planet formation and solar system dynamics
  • General Physics Labs — Mechanics, optics, electromagnetism experiments

👨‍🏫 Mentorship

I mentor several B.Sc. and M.Sc. students in research projects involving:

  • RR Lyrae and Cepheid variable star classification
  • Machine learning applications in astronomical time series
  • Photometric data analysis using Python & neural networks

📝 Dissertation Guidance

  • Multiwavelength study of RR Lyrae stars: Atharva Bhatele
  • Exoplanet parameter extraction using ExoFAST: Neelesh

If you’re a student interested in working on a project or thesis related to astrophysics, computation, or data science, feel free to get in touch.