My research primarily focuses on developing Machine Learning (ML) approaches for Natural Language Processing (NLP) tasks, particularly emphasising societal and human security and safety. My recent work has concentrated on three main areas: online event detection (including temporal and textual event profiling, trigger and argument detection, and event causality identification), online safety (covering offensive content detection, misinformation identification, and fake news detection), and information extraction (such as named entity recognition, relation extraction, and rule generation). The recent advancements in NLP have significantly impacted society and human beings, providing many benefits while raising serious concerns about the trustworthiness, truthfulness, and fairness of NLP technologies. Therefore, I am also interested in exploring the capabilities of Large Language Models (LLMs), the multilingualism of models/ NLP technologies, support for low-resource languages, and the explainability of models/ NLP technologies.