PhD Scholarships

PhD Scholarships

About

As part of developing a sustainable big data workforce for Australia, the D2D CRC is committed to supporting and developing PhD students through the D2D CRC PhD Scholarship program.

The PhD Scholarship Program has provided scholarships to over 58 exceptional PhD students undertaking in-depth research into real-world data science challenges.  The students are part of research teams across several Australian universities and provide comprehensive research to the D2D CRC program areas.

Having reached, and exceeded, the scholarship target of 52 PhD scholarships, the program is now closed to applications. 

Quality Research Outcomes

Supervised by experts at the D2D CRC’s University partners, the PhD students achieve high quality research outcomes and have completed numerous papers and presentations around Australia and overseas.  Each year students also contribute their knowledge to the D2D CRC Annual Conference through posters, presentations and demonstrations.

Developing Professional Skills

As well as research expertise, the D2D CRC supports PhD Scholarship students to develop skills that will enhance their ability to enter workplaces or continue on to further research excellence.  Regular workshops are held to develop skills around communication, innovation and creativity, leadership and collaboration.  The workshops are also an excellent opportunity to share experiences and learn about other student’s research and will often involve PhD students from another CRC or similar organisation.

These professional skills can then be put into practice through a placement or internship, where PhD students work closely with industry and government agencies on relevant projects.  As well as contributing to a specific project, PhD students bring significant expertise and fresh perspectives to host organisations, while in return gaining hands on experience, mentorship and networking.

Broadening Experiences

Other opportunities to develop their networks are also provided through the Applied Research Program where students are sponsored to attend conferences, work with internationally recognised research groups and seek out innovative new ideas in their area of research.  So far, students have visited UK, Netherlands, Italy, Denmark and Finland, returning to share insights and expertise.

Each PhD Scholarship student has a profile contained within the relevant R&D program web page. 

PhD Achievements

Submitted Thesis

Seung Youb Ssin, University of South Australia, Tangible Spatiotemporal Visualisation

Alex Mathews, Australian National University, Automatic Sentence Re-writing/Generation and Building Visual Knowledge Graphs

John Wondoh, University of South Australia, Briefing Tool for Law Enforcement with Narrative Visualisation

Stanley Shanapinda, University of New South Wales, Australian Story: Advance Metadata Fair

Peter Mathews, University of Adelaide, Characterising the Social Media Temporal Response to External Events

Ang Yang, University of South Australia, An Information Quality Model for Big Data

Formal Publications

The retention and disclosure of location information and location identifiers: OTT content and communications services, S Shanapinda 

On Automating Basic Data Curation Tasks, A Beheshti, A Tabebordbar, B Benatallah and R Nouri

Propagation of Event Content Modification in Business Processes, J Wondoh, G Grossmann and M Stumptner

Utilising Bitemporal Information for Business Process Contingency Management, J Wondoh, G Grossmann and M Stumptner

Propagation of Event Content Modification in Business Processes, J Wondoh, G Grossmann and M Stumptner,

Bitemporal Support for Business Process Contingency Management, J Wondoh, G Grossmann, D Gasevic and M Reichert,

The Nature and Origin of Heavy Tails in Retweet Activity, P Mathews, L Mitchell, G Nguyen, N Bean

Data mining for building knowledge bases: techniques, architectures and applications,  A Krzywicki, W Wobcke, M Bain and J Calvo Martinez

Automatic Event Detection in Microblogs Using Incremental Machine Learning, T Bandaragoda, D De Silva, D Alahakoon

Apache spark based distributed self-organizing map algorithm for sensor data analysis, M Jayaratne, D Alahakoon, D De Silva, X Yu

More is Less: A More Complicated Network with Less Inference Complexity, X Dong, J Huang, Y Yang, S Yan

Self-paced co-training, F Ma, D Meng, Q Xie, Z Li, X Dong

A Dual-Network Progressive Approach to Weakly Supervised Object Detection X Dong, D Meng, F Ma, Y Yang

Supervision-by-Registration: An unsupervised approach to improve the precision of facial landmark detectors, X Dong, SI Yu, X Weng, SE Wei, Y Yang, Y Sheikh

Style Aggregated Network for Facial Landmark Detection, X Dong, Y Yan, W Ouyang, Y Yang

Few-Example Object Detection with Model Communication, X Dong, L Zheng, F Ma, Y Yang, D Meng

Exploit the Unknown Gradually: One-Shot Video-Based Person Re-Identification by Stepwise Learning, Y Wu, Y Lin, X Dong, Y Yan, W Ouyang, Y Yang

EraseReLU: A Simple Way to Ease the Training of Deep Convolution Neural Networks, X Dong, G Kang, K Zhan, Y Yang

PatchShuffle Regularization, G Kang, X Dong, L Zheng, Y Yang

Unlabeled samples generated by gan improve the person re-identification baseline in vitro, Z Zheng, L Zheng, Y Yang

A Discriminatively Learned CNN Embedding for Person Reidentification, Z Zheng, L Zheng, Y Yang

Improving person re-identification by attribute and identity learning, Y Lin, L Zheng, Z Zheng, Y Wu, Y Yang

Pedestrian alignment network for large-scale person re-identification, Z Zheng, L Zheng, Y Yang

Camera Style Adaptation for Person Re-identification, Z Zhong, L Zheng, Z Zheng, S Li, Y Yang

Diagnose like a radiologist: Attention guided convolutional neural network for thorax disease classification, Q Guan, Y Huang, Z Zhong, Z Zheng, L Zheng, Y Yang

Multi-pseudo Regularized Label for Generated Samples in Person Re-Identification, Y Huang, J Xu, Q Wu, Z Zheng, Z Zhang, J Zhang

Dual-Path Convolutional Image-Text Embedding, Z Zheng, L Zheng, M Garrett, Y Yang, YD Shen

Mining Twitter for Fine-Grained Political Opinion Polarity Classification, Ideology Detection and Sarcasm Detection, S KannangaraEvent Mining over Distributed Text Stream, J Calvo Martinez

CrowdCorrect: A Curation Pipeline for Social Data Cleansing and Curation, A Beheshti, K Vaghani, B Benatallah, A Tabeordbar

Decoupled Novel Object Captioner, Y Wu, L Zhu, L Jiang, Y Yang

Uncovering the temporal context for video question answering, L Zhu, Z Xu, Yi Yang, Alexander G Hauptmann

Super-blockers and the effect of network structure on information cascades, C Gray, L Mitchell, M Roughan


Conference Presentations

Mark Carman, Paper accepted for the IEEE TrustCom-18, New York, July 2018

Dennis Liu, Accepted for first talk at the Society of Mathematical Biology (SMB2018), Sydney, July 2018

Miah Hammond-Errey, Accepted to present at the 2018 International Association of Intelligence Education Conference (IAFIE), Sydney, July 2018

Miah Hammond- Errey, Accepted to present at the 17th European Conference on Cyber Warfare and Security, Oslo, June 2018

Sandeepa Kannangara, The 11th ACM International Conference on Web Search and Data Mining, Los Angeles, 2018

Peter Mathews, ISI Foundation, Italy, 2018

Caitlin Gray, World Wide Web Conference, France 2018

Peter Mathews, World Wide Web Conference, Australia & France, 2017 & 2018

Miah Hammond-Errey, Australian Cyber Security Centre Conference, Australia, 2017

Adrian Johnston, International Conference on Computer Vision, Italy, 2017

Ruth Frimpong, 14th Extended Semantic Web Conference, Slovenia, 2017

John Calvo Martinez, Global Security PLuS Alliance Symposium, Australia - August 2017.

John Calvo Martinez, UNSW Research Symposium - “Event Mining over Distributed Text Data”, Australia, 2017. This paper has also been accepted for the 2018 WSDM Doctoral Consortium. 

 

Awards

Awarded Best Paper BDVA 2017 - SONA: Improving Situational Awareness of Geotagged Information Using Tangible Interfaces, Seung Youb Ssin, Joanne E. Zucco, James A. Walsh, Ross T. Smith, Bruce H. Thomas

UniSA Three Minute Thesis (ITMS) 2018 - Jeffery Ansah and Carolin Riechherzer 

People's Choice Award 2018 - Jeffery Ansah

 

Other Activities

Jeffery Ansah, President of the School of Information Technology and Mathematical Sciences Higher Degree Research Club (Unisa)

Jeffery Ansah, Mentor for the Unisa Mentor Program

Jeffery Ansah, Accepted into the UniSA Premium Leadership Program 

Caitlin Gray, Mathematics Tutor at the University of Adelaide

Carolin Riechherzer, Code Like A Girl Mentor 

Yanbin Liu, Undertook internship at AITRICS (Korea)

Xuanyi Dong, Undertook internship at Facebook Oculus Research