Teaching and Pedagogy

Teaching philosophy: Experienced educator in AI and Computer Science teaching across undergraduate  levels with a strong emphasis on student-centered, inclusive, and research-informed pedagogy.

Pedagogical Approach : Active learning, hands-on laboratories, and project-based assessment; inclusive teaching for diverse learners; integration of real-world datasets and case studies; continuous feedback and reflective practice.

Teaching Areas

Artificial Intelligence & Computer Vision

• Computer Vision
• Digital Image and Video Processing
• Introduction to Artificial Intelligence
• Computational Intelligence with Python Lab
• Machine Learning with Python
• Data Mining

Data Science & Analytics

• Data Wrangling & Visualization using Python
• Predictive Analytics with R

Programming & Software Engineering

• Data Structures
• Theory of Computation
• Object Oriented Analysis & Design
• Design Patterns

Mathematics for Computing

• Mathematical Foundations of Computer Science
• Maths Lab
• Essentials of Mathematics for Machine Learning (Python)