Courses (taught at IIT Delhi) 

• APL 745: Deep Learning for Mechanics (Jan-Mar 2022) [taught jointly with Prof. Souvik Chakraborty]

• APL 100: Engineering Mechanics (Apr-Jul 2022) (Tutorials) 

• APL 104: Solid Mechanics (Aug-Dec 2022) [Github link]

• APL 405: Machine Learning in Mechanics (Jan-Apr 2023) [Github link]

• APL 104: Solid Mechanics (Aug-Dec 2023) [Github link]

• APL 405: Machine Learning in Mechanics (Jan-Apr 2024) [Github link]

• APL 104: Solid Mechanics (Aug-Dec 2024) [Github link]

• APL 100: Engineering Mechanics (Jan-May 2025) [Github link]

Courses (taught at University of Waterloo as Teaching Assistant) 

• CIVE 104: Mechanics I (Spring 2018)

• CIVE 303: Structural Analysis I (Winter 2018)

• CIVE 221: Advanced Calculus (Fall 2017)

• ENVE 223: Differential Equations and Balance Laws (Winter 2017)

• CIVE 221: Advanced Calculus (Fall 2016)

• CIVE 331: Advanced Mathematics (Winter 2016)

• CIVE 224: Probability and Statistics (Fall 2015)

• CIVE 405: Structural Dynamics (Winter 2015)

A collection of links to books and course notes 

• Matrix Analysis and Applied Linear Algebra by Carl D. Meyer

• Numerical Linear Algebra course notes from Lund University

• Introduction to Linear Dynamical Systems: Lectures by Prof. Stephen Boyd 

• System Identification by Prof. Henry P. Gavin

• Introduction to Machine Learning by Prof. Andrew Ng

• Bayesian Filtering and Smoothing by Prof. Simo Särkkä

• Applied Stochastic Differential Equations by Prof. Simo Särkkä and Prof. Arno Solin

• Stochastic Structural Dynamics by Prof. C.S. Manohar

• Bayesian Networks (or directed acyclic graphs)

• A short summary of Monte Carlo methods using MATLAB by Roberto Casarin (2013)

• Short note on conjugate priors by M.I. Jordan 

• Machine learning for engineers by Osvaldo Simone