Lulwah AlKulaib ☕️
Lulwah AlKulaib

Assistant Professor

About Me

I am an Assistant Professor in the Computer Science Department at Kuwait University. My research focuses on developing innovative models with practical applications in social media analytics, the study of low-resource languages, and public health initiatives. My work integrates my extensive experience in various research roles with my interest in Natural Language Processing, Machine Learning, and Deep Learning. I am dedicated to advancing these fields by creating robust algorithms that effectively navigate and interpret the complexities of human language and behavior.

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Interests
  • Artificial Intelligence
  • Computational Linguistics
  • Information Retrieval
  • Social Network Analysis
  • Behavioral Modeling
Education
  • PhD in Computer Science

    Virginia Tech

  • MSc in Computer Science

    George Washington University

  • BSc in Computer Science

    Gulf University for Science and Technology

📚 My Research

I am an Assistant Professor in the Computer Science Department at Kuwait University. My research concentrates on designing novel frameworks with real-world applications in social media analytics, low-resource languages, and public health. I apply a range of qualitative and quantitative methods to investigate the efficacy of graph-based models in behavioral modeling.

Please reach out to collaborate 😃

Featured Publications
Recent Publications
(2023). Hypergraph Text Classification for Mental Health Misleading Advice. Proceedings of the International Conference on Advances in Social Networks Analysis and Mining.
(2023). Analyzing Prediction of Depression and Anxiety on Reddit: a Multi-task Learning Approach through GMMTL.
(2023). Balancing the Scales: HyperSMOTE for Enhanced Hypergraph Classification. 2023 IEEE International Conference on Big Data (BigData).
(2023). From Guest to Family: An Innovative Framework for Enhancing Memorable Experiences in the Hotel Industry. Proceedings of the International Conference on Advances in Social Networks Analysis and Mining.