Rate My Professor Usman Naseem

Dr. Usman Naseem is a Lecturer in the School of Computing within the Faculty of Science and Engineering at Macquarie University, a position he has held since February 2024. He earned his PhD from the University of Sydney and previously accumulated over ten years of industry experience in technical and leadership roles before entering academia. His prior academic appointments include Lecturer in the College of Science and Engineering at James Cook University, as well as Research Fellow positions at the University of Sydney and the University of South Australia. Naseem leads the NLP for Social Good Lab, known as SocialNLP, at Macquarie University and is affiliated with the Frontier AI Research Centre, Future Communications Research Centre, and Data Horizons Research Centre.

Naseem's research centers on natural language processing, multimodal analysis, and social computing, particularly language modeling and the development of socially aware methods for cyber informatics, online opinion and sarcasm mining, responsible code-mixed and low-resource language processing, multimodal content analysis, and health and medical informatics. He has earned prestigious awards such as the DAAD AINet Fellowship and Rising Star in AI Fellowship in 2023, multiple Best Paper Awards from 2021 to 2026 including Best IEEE Transactions Paper Award in 2022, Outstanding Senior Area Chair Award at EMNLP 2025, and recognition among the World's Top 2% Scientists in 2024. Naseem serves as an area chair on program committees for leading conferences including ACL, EMNLP, COLING, WSDM, WebConf, SIGIR, ACM MM, and IEEE Transactions. Notable publications include 'A survey of progress in LLM alignment from the perspective of reward design' (IEEE Transactions on Artificial Intelligence, 2026), 'CLARITY: a lightweight multimodal transformer for harmful content detection' (IEEE Transactions on Artificial Intelligence, 2026), 'LLM Alignment should go beyond Harmlessness–Helpfulness and incorporate Human Agency' (Cognitive Computation, 2026), 'Early identification of depression severity levels on Reddit using ordinal classification' (2022), 'A comprehensive survey on word representation models: from classical to state-of-the-art word representation language models' (2021), and 'A multimodal framework for the identification of vaccine critical memes on Twitter' (2023). His contributions advance AI safety, trust, and applications for social good, including harmful content detection and mental health surveillance.