Reza Haffari

Reza's work is focused on Artificial Intelligence (AI), particularly in low-level perception and high-level reasoning under uncertainty, mainly from text and potentially from other data modalities such as vision and speech. His research tackles problems such as:

• Understanding and generating natural language text eg translating documents from one language to another while keeping the document's coherency/semantics intact.
• Effective training of deep neural networks with minimal human supervision as this powerful technology is data hungry, eg through interaction with human to achieve effective lifelong learning.
• Explaining the outcome of black-box computational models in order to make them trustable in critical decision making scenarios such as digital health.
  

Reza has experience as the Chief Examiner for the following units in the Faculty of IT:

• FIT1045 Algorithms and programming fundamentals in python
• FIT1053 Algorithms and programming fundamentals in python (advanced)
• FIT2004 Algorithms and data structures
• FIT5201 Data analysis algorithms

Reza has experience as the Lecturer for the following units in the Faculty of IT:

• FIT1045 Algorithms and programming fundamentals in python
• FIT2004 Algorithms and data structures
• FIT3080 Intelligent systems
• FIT4005/FIT5185 IT research methods
• FIT4009 Advanced topics in intelligent systems
• FIT5201 Data analysis lgorithms