The Google PhD Fellowship program supports PhD students in computer science and related fields, and is part of our commitment to building strong relationships with the global academic community.
In our most recent round four PhD students in Australia have been recognised for their outstanding efforts.
- Samaneh Movassaghi, Google Australia PhD Fellowship in Networking (Australian National University) - Research Proposal Title: iConect: Interference Coordination and Optimisation for Negligible Energy Consumption over Time in Coexisting Wireless Body Area Networks.
Samaneh’s natural curiosity was nurtured by her family to develop inquisitive tinkering skills to discover how the world works. Taking up engineering at university she is now working to develop affordable and timely health care through the interconnection of network sensory devices worn on the body to monitor vital health signs.
- Ekaterina Vylomova, Google Australia PhD Fellowship in Natural Language Processing (The University of Melbourne) - Research Proposal Title: Compositional Morphology through Deep Learning.
Ekaterina’s focus on language generation and computational morphology was inspired by the works of Stanislaw LEm and Issaac Asimov on robotics and AI. When introduced by her cousin to programming she wrote her first chat-bot program “Golem”, an early experiment in AI.
- Sarah Webber, Google Australia PhD Fellowship in Human Computer Interaction (The University of Melbourne) - Interactive Technology for Human-Animal Encounters at the Zoo.
Sarah’s research looks at digital technology designed to provide zoo animals with enriching experiences and cognitive challenges. Her PhD examines how the design of such technology can shape people's attitudes to other species, and to conservation issues. Hearing a talk by Dr Genevieve Bell first revealed to Sarah that human-computer interaction researchers were, like her, interested in how technology design can help to solve difficult societal problems - and she has been hooked ever since.
- Ling Luo, Google Australia PhD Fellowship in Machine Learning, (The University of Sydney) - Temporal Modelling for Customer Behaviours.
Ling’s research in machine learning is focusing on modelling customer behaviour, including discovering temporal patterns, identifying key factors for behaviour changes and predicting future behaviour. Ling’s interest in machine learning and data mining stemmed from an introductory artificial intelligence course during her undergraduate studies. She has been fascinated by how problems can be elegantly solved by smart algorithms and computer programs. She hopes her research can contribute to the body of knowledge in data mining and user behaviour analytics, which can help discover useful information from vast and ever-growing amounts of behavioural data.
By supporting these four Australian Fellows we recognise their significant academic achievements and hope that they will go on to be leaders in their respective fields. We look forward to building even stronger links between industry and academia to help push important research forward in Australia.