Education
• MSc Computer Science, University of North Carolina at Greensboro
• BSc Computer Science, BRAC University
Courses Taught
• CSC105: Data, Computing, and Quantitative Reasoning (MAC: Quantitative Reasoning)
• CSC250: Foundations of Computer Science I
• CSC350: Foundations of Computer Science II
• CSC330: Advanced Data Structures
• CSC350: System Programming
Research
Research: Natural Language Processing; Large Language Models (LLMs); Data Science; Deep Learning
I specialize in large language models (LLMs) and my work generally focuses on developing computational models and training them so that they can understand and generate human language with a high level of precision. The two major domains of my research are tackling the challenges of deploying misinformation-preventing measures and improving conversational AI.
My research delves into the realm of multimodal analysis, encompassing text, images, videos, and audio, develop models that can understand the context surrounding a piece of content, including historical context, user demographics, and network dynamics to develop context awareness of models, and also explores cross-lingual and cross-cultural aspects of misinformation, ensuring that detection models can be applied globally and adapted to diverse linguistic and cultural contexts.
I study approaches to enhance emotion recognition in conversational AI systems by understanding the complexity of human emotions, especially within nuanced dialogues, which requires complex hybrid models that combine deep learning techniques with traditional machine learning that can accurately perceive and respond to users’ emotional states. My work has direct implications for improving user experiences in AI-driven applications, from virtual assistants to mental health support systems.
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