Teaching & Education
Transforming AI education through experiential learning, industry relevance, and research-led instruction.
Teaching Philosophy
My approach to education blends rigorous theoretical foundations with practical, hands-on implementation. I aim to cultivate critical thinking and problem-solving skills, preparing students not just to use AI tools, but to understand their underlying mechanics and innovate upon them.
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Experiential Learning
Bridging theory and practice through real-world projects and coding assignments.
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Industry Relevance
Updating curriculum with the latest advancements in Deep Learning and computer vision frameworks.
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Research-Led Teaching
Integrating ongoing research challenges into classroom discussions to spark innovation.
Courses
Introduction to Programming (CS101)
Foundations of programming, algorithmic thinking, and problem-solving using Python/C++.
Data Structures & Algorithms (CS201)
Core data structures, algorithm analysis, sorting, and graph algorithms.
Database Management Systems (CS301)
Relational algebra, SQL, normalization, and modern NoSQL databases.
Machine Learning Fundamentals (CS401)
Supervised/unsupervised learning, linear models, decision trees, and model evaluation.
Artificial Intelligence (CS402)
Search algorithms, knowledge representation, expert systems, and AI applications.
Computer Vision Lab (CS501L)
Hands-on implementation of image processing and CNN models using OpenCV and PyTorch.
Join My Research Lab
Seeking motivated undergraduate and graduate students passionate about AI, computer vision, and building intelligent systems.
Contact for Openings