With over twelve years of expertise in academic teaching and research, I am interested in various aspects of machine learning, including clustering and deep neural networks. Currently, I am deeply engaged in exploring the realms of interpretability, explainable AI, and bias mitigation in machine learning.
The course aims at answering two questions: what can be computed by a machine? And how efficiently? It starts by presenting machines models, then addresses the computability problem, and then the…
Overview of Compilers and Programming languages, Lexical Analysis, Parsing, Semantic Analysis, Runtime Environments: Stack Machine, Code Generation, Local and global Optimization
The purpose of CSC281 course is to understand and use (abstract) discrete structures that are the backbones of computer science. In particular, this class is meant to introduce logic, proofs, sets…