Ms. Samia Aziz obtained her master’s degree in computer science from FAST National University of Computer and Emerging Sciences in 2022. Her master’s research focused on classifying and geo-mapping political hate speech in Roman Urdu collected from Twitter. In this work, she developed a novel dataset (RU-PHS) and employed a combination of text vectorization methods and machine learning approaches to achieve high prediction accuracy. Spatial analysis with ArcGIS further identified regional clusters and hot spots, validated through interpolation.

She joined FAST-NUCES as a Lab Instructor in 2023 and is currently serving as a Lecturer in the Department of Software Engineering. Over the years, she has been involved in teaching core lab-based courses such as Programming Fundamentals, Object-Oriented Programming, and Database Systems.

Her ongoing research lies at the intersection of natural language processing and affective computing, with a particular focus on large language models and their ability to interpret sentiment and emotion in multilingual, code-switched, and low-resource environments. She is especially interested in developing computational frameworks that integrate linguistic, emotional, and contextual signals to enable machines to better understand and respond to human language in diverse real-world settings.

Interests

• Emotion Detection in Multimodal Contexts
• Cross-lingual Transfer Learning
• Fake News and Misinformation Detection
• Spatio-temporal Analysis of social media Trends