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.

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📘 Courses & Resources

1. Computational Astrophysics (M.Sc.)
   • Lecture 1 (View in Browser) | Download .ipynb
   • Lecture 2: Data Sorting Algorithms (View in Browser) | Download .ipynb
   • Lecture 3 (View in Browser) | Download .ipynb
   • Lecture 4 and 5 (View in Browser) | Download .ipynb
   • Lecture 6 (View in Browser) | Download .ipynb
   • Lecture 7 (View in Browser) | Download .ipynb
   • Lecture 11: Error Analysis (View in Browser) | Download .ipynb
   • Lecture 13: ODEs and Euler's Method (View in Browser) | Download .ipynb
   • Lecture 17: PDEs (View in Browser) | Download .ipynb
   • Lecture 19 (View in Browser) | Download .ipynb
   • Lecture 20 (View in Browser) | Download .ipynb
   • Lecture 21 (Curve Fitting) (View in Browser) | Download .ipynb
   • Lecture 22 (Fourier Transforms) (View in Browser) | Download .ipynb
   • Lecture 23 (2 body problem) (View in Browser) | Download .ipynb
   • Lecture 24 (N body problem) (View in Browser) | Download .ipynb
   • Lecture 25A (Monte Carlo Methods) (View in Browser) | Download .ipynb
   • Lecture 25B (Monte Carlo Methods) (View in Browser) | Download .ipynb
2. Computational Techniques (B.Sc. Physics)
   • Python Programming Notes (PDF)
   • Jupyter Notebooks (*Use crtl+s to save* and open in jupyter lab or VS code.)
   • Google Colab Notebooks Link
3. Introduction to Computational Physics Lab (Int. B.Sc. + M.Sc.)
   • Lab Manual (PDF)
4. Learning LaTeX
   • LaTeX Tutorial (PDF)
5. Computational Physics (M.Sc. Level)
   • Intro to Computational Physics (PDF)
6. Fundamentals of Astronomy (B.Sc. Physics)
   • Lecture Notes (PDF)
   • Problem Sets (PDF)
7. Observational Astronomy Lab (B.Sc. Physics)
   • Lab Manual (PDF)

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

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📚 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

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👨‍🏫 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

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📝 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.