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
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Computational Astrophysics (M.Sc.)
View Lecture Notebooks & Materials
- Lecture 1
- Lecture 2: Data Sorting Algorithms
- Lecture 3
- Lecture 4 & 5
- Lecture 6
- Lecture 7
- Lecture 11: Error Analysis
- Lecture 13: ODEs and Euler's Method
- Lecture 17: PDEs
- Lecture 19
- Lecture 20
- Lecture 21: Curve Fitting
- Lecture 22: Fourier Transforms
- Lecture 23: 2 Body Problem
- Lecture 24: N Body Problem
- Lecture 25A: Monte Carlo Methods
- Lecture 25B: Monte Carlo Methods
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Computational Techniques (B.Sc. Physics)
*Use ctrl+s to save and open Notebooks in Jupyter Lab or VS Code.*
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Laboratory & Specialized Courses
Intro to Computational Physics Lab (Int. B.Sc. + M.Sc.): 📄 Lab Manual (PDF)Learning LaTeX: 📄 LaTeX Tutorial (PDF)Computational Physics (M.Sc. Level): 📄 Intro to Computational Physics (PDF)Observational Astronomy Lab (B.Sc. Physics): 📄 Lab Manual (PDF)
- Fundamentals of Astronomy (B.Sc. Physics)
💡 Key Topics Covered: 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 & Dissertation Guidance
Research Mentorship
Current projects with B.Sc. and M.Sc. students:
- RR Lyrae and Cepheid variable star classification
- Machine learning applications in astronomical time series
- Photometric data analysis using Python & neural networks
Dissertation Guidance
- Atharva Bhatele: Multiwavelength study of RR Lyrae stars
- Neelesh: Exoplanet parameter extraction using ExoFAST
🚀 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!