Teaching

Instructor

National University of Sciences and Technology (2014-17)

  • I was awarded the Best Faculty Award 2015-2016.
  • Participated in curriculum design and outcome-based education (OBE) efforts in preparation for accreditation and continuous program improvement
  • Designed and delivered lectures, labs, assignments, and exams for the following core courses in avionics engineering.
  1. AV 351 Modern Control Systems
    • I taught using state-space methods alongside hardware experiments.
    • Students designed MATLAB controllers for inverted pendulums and cart-pole demonstrators, tuned them on real equipment.
  2. CS 201 Intro to Programming
    • redesigned the course from Fortran/C++ to Python, introduced open-ended programming projects and emphasized algorithmic thinking.
    • Taught large class sizes.
    • introduced end-to-end app projects as the capstone deliverable, so students experienced problem framing, testing, and user-facing documentation.
  3. AV 101 DC Circuit Analysis
    • Breadboard labs with power supplies, resistors, capacitors, and standard instrumentation made Kirchhoff’s laws concrete
    • Students were asked not only to compute but also to explain when measurements and predictions diverged and why.
  4. IE 361 Computer-Aided Instrumentation
    • I rebuilt the course around hardware sensors, LabVIEW, and open-ended design.
    • Students developed instrumented systems, such as small data-acquisition setups, and presented them in a department-wide showcase.

Teaching Assistant

University of Colorado Boulder

  • I was awarded the Outstanding TA award (2023-2024) and the Best Mentor award (2022)
  1. CSCI 3104 Algorithms - Spring’22, Fall’22, Spring’23, Summer’23, Spring’24
    • Led weekly recitations focusing on problem-solving strategies
    • Developed new recitation materials, quizzes and exams to reflect standards based asessment.
    • Co-created the material with Prof. Divya Vernerey and catering to around 300 students each iteration.
    • Some of my live teaching notes can be accessed here.
  2. CSCI 4622 Machine Learning - Fall’23
    • Supported a project-based course that introduced supervised and unsupervised learning, with implementation in Python.
    • Guided student teams on scoping final projects, understanding model evaluation, and interpreting results.
    • Helped design and grade assignments involving regression, classification, and basic deep learning.
    • Introduced short weekly modules linking theory to practice, framing an interview-style question and then unpacking it together, so students could see how course concepts show up in real technical conversations.
    • The interview questions can be found at this link .

Oregon State University

  1. CS 562 – Software Project Management - Winter’18

  2. CS 372 – Introduction to Computer Networks (eCampus) - Fall’18, Spring’19

Live Teaching Notes