Teaching Career

  1. Applied AI and ML in Practice (Fall 2025)
    Course content: Supervised and Unsupervised learning, Neural networks, Convolutional neural networks, GAN, Reinforcement learning, Federated learning, Large language models, and hands-on AI applications.
  2. Wireless Communications (Spring 2026)
    Course content: Wireless propagation, Path-loss models, Ground reflection model, Shadowing and fading, Diffraction and Scattering, Cellular system concepts, Multiple access techniques, and MIMO.
  3. Digital Communication (Fall 2025)
    Course content: Different types of signals, Orthogonality, Digital modulation techniques, ASK/PSK/FSK/OFSK, Matched filtering, Pptimum detection, Probability of error analysis, Pulse shaping and Interference.
  4. Computational Problem Solving (Spring 2026)
    Course content: Arrays and matrices, Loops and conditional statements, Numerical methods in MATLAB, Root finding, Numerical differentiation and integration, Systems of equations, and Engineering problem solving.