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Hello! I am an assistant professor in the Department of Data Science and Artificial Intelligence of Monash, and an affiliated lecturer of University of Cambridge. Prior to joining Monash, I was a lecturer at the Department of Electrical and Electronic Engineering of UCL, and before that a postdoc in the Language Technology Lab at University of Cambridge.

I lead a team of students working on predictive models for language (text and speech). During my PhD I worked on integrating nonparametric models and compressed data structures for predictive models on large volumes of text. In my PostDoc, I worked on multilingual NLP and Bayesian learning of neural models with their application in low-resource conditions. Since 2019 I have been working on various speech and text models in understanding, translation, and reasoning tasks. While in principle the solutions we investigate are agnostic to the underlying models, we leverage foundational large language models (for text and speech) as much as possible. Hence, in recent years my team has also been investigating various shortcomings of such models.

Research Areas in Language and Text.

  • Probing and Augmenting LLMs (verification, symbolic grounding)
  • Self-supervised learning (e.g., applications in text, speech, and graph)
  • Utilising graphs for knowledge intensive tasks (e.g., graph-to-text generation, applications in biomedical domain)
  • Deep generative models (e.g., generation, semi-supervised learning, sparsity and disentanglement)
  • Bayesian learning and inference (e.g., applications in training with small data)


Future Students.

I am looking for self-motivated Ph.D students to work on any of the above topics or related areas (you may also want to check my publications in the last 2-3 years). You can use this link and check if you meet the deadline and minimum requirement to apply for scholarships from Monash.