Ms. Farwa Ahmad obtained her master’s degree in Computer Science with a specialization in Machine Learning, during which her thesis focused on enhancing recommender systems for Community Question Answering (CQA) platforms. In her research, she developed a novel approach that integrates incremental learning and topic modeling to effectively recommend domain-specific experts, addressing challenges of dynamic content and evolving user interests in CQA environments. She began her academic career at FAST-NUCES as part of the Computing Faculty at the CFD campus and is currently serving as a Lecturer in the Department of Computing at the Multan campus. Her teaching experience includes core computing courses and she remains actively engaged in student mentorship and academic development. Her research interests lie in the areas of recommender systems, machine learning, and data-driven personalization. She is particularly focused on scalable, adaptive algorithms that can operate in real-time environments and improve user engagement and information retrieval in low-resource and domain-specific settings.