Bob Williamson

Bob Williamson Research Group Leader, Professor ANU

Bob's research goal is to reconceive the field of machine learning. The research agenda is to develop a composable basis for machine learning to focus on problems rather than solutions.

James Bailey

James Bailey Associate Professor, University of Melbourne

James works in data mining and machine learning with applications in Computational Health Informatics and Bioinformatics.

Tim Baldwin

Tim Baldwin Associate Professor, University of Melbourne

Tim works in natural language processing and computational linguistics with applications in biomedical text mining.

Peter_Bartlett Peter Bartlett Professor, Queensland University of Technology & University of California at Berkeley

Peter's research interests include machine learning, statistical learning theory, and adaptive control.

Richard Nock

Richard Nock Senior Principal Researcher, ATP

Richard works on computational information geometry, with emphasis on machine learning and applications in computer vision and life sciences. 


Edwin Bonilla Senior Researcher, CRL

Edwin's research focuses on probabilistic models to build systems that can learn from their past experience and for the analysis of complex, structured data. His research lies at the intersection of machine learning, statistics, computer science and artificial intelligence.


Tiberio Caetano Principal Researcher, ATP

Tiberio is interested in big data. More specifically, he is working on developing learning algorithms that can efficiently infer robust patterns from messy, large, unstructured, noisy, diverse and ever-growing data repositories.

Chen_Fang_2013Fang Chen Senior Principal Researcher, ATP

Dr. Chen's main research interests are behaviour analytics, especially in human machine interaction, cognitive load modelling, speech processing, pattern recognition, human and system performance prediction and evaluation.

Justin Justin Domke Senior Researcher, CRL

Justin is interested in efficient methods for learning and inference in probabilistic graphical models, sometimes with applications in computer vision.

Julien Epps Senior Lecturer, UNSW

Julien's research interests include speech modeling and front-end processing, automatic cognitive load measurement, genomic signal processing and applications of digital signal processing and pattern recognition.

GabrielaFerraro_1 Gabriela Ferraro Researcher, CRL

 Interests: Computational linguistics and Natural language processing, especially collocations, with applications to patent texts.

Stephen_Gould Stephen Gould Researcher, CRL

 Steve has broad interests in computer and robotic vision, machine learning, probabilistic graphical models, and discrete and continuous optimization. His main research is in the application of machine learning techniques (specifically, conditional Markov random fields) to geometric and semantic scene understanding.

Asif M Asif Khawaja, Researcher, ATP

 Asif's research interests focus on behavioural analysis. This includes cognitive load measurement, trust measurement, and  linguistic  analysis. He is also interested in theoretical and applied research in building adaptive Human-Computer Interaction (HCI) systems.


Chris Leckie Associate Professor, University of Melbourne

Chris's research interests are in the field of Artificial Intelligence (AI) and telecommunications. He has made theoretical and practical contributions in areas such as machine learning, fault diagnosis, distributed systems and design automation.

Wei Wei Liu, Researcher, ATP

Wei works in machine learning and data mining. His research interests include tensor factorization, dynamic graph modelling, game theory, and causal inference.

Aditya_MenonAditya Menon, Researcher, CRL

Aditya's interests span a range of machine learning frameworks -- such as collaborative filtering, probability estimation, and multilabel learning -- and their applications to novel problem domains.

Khoa Khoa Nguyen Researcher, ATP

Khoa works in machine learning and data mining with focuses on unsupervised anomaly detection, clustering, spectral/graph-based methods, and matrix/tensor factorisation.


Simon O'Callaghan Researcher, ATP

Simon’s primary research focus is on non-parametric Bayesian inference methods with applications to computational sustainability and autonomous mobile robotics.


Fabio Ramos Senior Lecturer, University of Sydney

Fabio's research interests include Bayesian statistics, stochastic processes for spatial modelling, probabilistic networks, and multi-sensor perception.

alistair Alistair Reid, Researcher, CRL

Alistair's current research at NICTA is focused on Bayesian statistics and stochastic models of spatial data. He is currently applying  his research to geophysical inversion problems, and also maintains an interest in autonomous robotics.


Mark Reid Researcher, CRL

Mark has a wide range of interests in symbolic and statistical machine learning, ranging from the theoretical to algorithm implementation and methodologies for their evaluation.

paulr Paul Rivera Software Engineer, CRL

Paul is an experienced JEE web applications developer and works on the web version of OpinionWatch - a visual document explorer project of NICTA.


Scott Sanner Senior Researcher, CRL

Scott's research focuses on a broad range of topics under the umbrella of intelligent decision-making in AI spanning sequential decision theory, machine learning, symbolic representations and reasoning, and information retrieval.


Hanna Suominen Senior Researcher, CRL

Hanna is an experienced researcher, coordinator and teacher on health and wellness technologies. She works as a machine learning researcher in the business team of health at NICTA.


Ronnie Taib Senior Research Engineer/Scientist, ATP

Ronnie has a broad interest in all the technologies enabling more friendly and useful machines and programs, encompassing multi-agent systems, context and user-aware systems, multimodal user interaction, and machine learning.


Yang Wang Senior Researcher, ATP

Yang’s research interests include machine learning and information fusion techniques, especially weakly-supervised learning, spatiotemporal modelling, and their applications to intelligent infrastructure, cognitive and emotive computing, and image and video analysis.


Christfried Webers Senior Research Engineer, CRL

Chris manages the Distributed Solar Prediction project and teaches Statistical Machine Learning at The Australian National University.

lexingx Lexing Xie Senior Lecturer, ANU

Lexing's research focus broadly on innovative use and design of machine learning algorithms and systems, especially on spatial, temporal and multi-relational graph data.

Xinhua Xinhua Zhang, Researcher, CRL

Xinhua’s research interests are in nonparametric methods for machine learning. This includes kernel methods, graphical models, sparse learning, and large scale optimization.

zhou_nicta Jianlong Zhou, Researcher, ATP

Jianlong Zhou's research interests include interactive machine learning, human computer interaction (HCI), spatial augmented  reality,  visualization, image analysis and bioimage informatics.


Australian National University

Eshan Ehsan Abbasnejad

Research interests: Machine Learning, Information Retrieval, Graphical Models, Approximate Inference, Non-parametric Bayesian Methods, Recommender Systems, and Decision Theory.

Project Title:  Decision-theoretic Approximations for Machine Learning

Most machine learning algorithms focus on either learning the probabilistic model or minimizing the loss. In probabilistic models, approximate inference, the process of obtaining the desired model from the observations when its is not tractable, does not consider the task loss. On the other end of the spectrum, the common practice in learning is to minimize the task loss without considering the uncertainty of prediction model. Therefore, we investigate the intersection of decision theory and machine learning considering both uncertainty in prediction model and the task loss.

Changyou_chen Changyou Chen

Research interest: Machine Learning,  Dependent Normalized Random Measures, Dependent Poisson-Kingman Processes, Some topics on Diffusion Processes, MCMC for Hierarchical Poisson-Dirichlet Processes, Topic Models, Manifold Learning and Gait Recognition (master research topics).

Project Title: Dependent Nonparametric Bayesian Methods

Changyou's research focuses on Bayesian nonparametric, including Poisson processes, dependent normalized random measures, dependent Poisson-Kingman processes, random graph and their applications such as nonparametric Bayesian topic modelling.

Engerer_Nick_2 Nick Engerer

Nick's research work is focused on creating short term power output forecasts for groups (10s to 1000s) of rooftop solar photovoltaic systems.

Project Title: Short term power forecasts for distributed photovoltaic arrays through machine learning

Nick is using power output data from photovoltaic arrays to create city-wide estimates of the power produced by rooftop-scale solar energy systems.  Using his expertise in meteorology and solar radiation, he is working with the NICTA Distributed Solar Prediction research group to develop solar forecast algorithms for Australian cities.

Kai_Wai_lim Kar Wai Lim

Kar Wai is currently doing his research under the supervision of Dr. Wray Buntine (NICTA), primarily focusing on statistical machine learning in topic modelling.

Project Title: Non-parametric Bayesian approach on topic modelling and its applications

Kar Wai is developing a better topic model for analysing tweets, with the aim of opinion mining of general public.

trung Van Trung Nguyen

Research Interests: Statistical and large scale machine learning, approximate inference, Gaussian processes, topic models, sentiment analysis, data analysis.

Project Title: Gaussian process models for large-scale regression

Van Trung works on mixtures and products of sparse Gaussian processes for regression problems with very large datasets.

Giorgio_Patrini Giorgio Patrini

Research interest: weakly/semi supervised learning, topic modelling, matrix factorisation, spectral algorithms, comparison of statistical experiments, optimisation.

Project Title:  Weakly supervised learning and interpretability

Giorgio is interested in how big data affects methods and practice of machine learning. In particular, he is working on weakly supervised learning and interpretability of high dimensional feature spaces.

Mindika Premachandra

Avraham Ruderman

suvashSuvash Sedhain

Research interests: Large scale Machine learning, Recommender Systems, Learning to rank and Social networks

Project Title: Large Scale Social Collaborative filtering

Suvash is working on leveraging the social information and scalable algorithms for large scale personalised recommender system.

Zahra_Zamani Zahra Zamani

Research interests: Artificial Intelligence, Agent frameworks, Logic, Learning (AI context as well as the original definition!)

Project Title:  Exact Symbolic dynamic programming for Hybrid MDPs and POMDPs

Zahra is developing exact solutions for planning under uncertainty when problem domains are continuous much like the real world.


University of New South Wales and University of Sydney

sarshad Syed Arshad

Research interests: Machine Learning, Bayesian data analysis, Big Data analytics, Computational Intelligence

Project Title:  Bayesian Nonparametrics machine learning for realtime cognitive load measures

The project aims to develop bayesian nonparametric techniques for realtime multimodal cognitive load measures.

Siyuan Siyuan Chen

Research interests:primarily on human-centred computing, pattern recognition, intelligent user interface and multimodal  information fusion.  

Project Title: Real-time cognitive load measurement via eye activity

The aim of this project is to use low-cost IR webcams to capture user eye activity, extract useful eye features that are correlated to cognition and then use supervised machine learning techniques to classify whether a user is under low, medium or high cognitive load level during tasks.

Victor_Chu_NICTA_2_sVictor Chu

Research interests: smart predictions and modeling by the application of machine learning and data mining techniques.

Project Title: Time-varying Dynamic Bayesian Causal Networks for Moving Objects

To learn the periodic behaviors of moving objects, e.g., traffic, and to infer their correlations are essential knowledge related to our daily life.  The popularity of spatial-temporal-aware equipments allow the collection of trajectories in unprecedented scale.  Depending on the type of moving objects, their trajectories might exhibit unfavorable statistical properties, e.g., data sparseness and skewness, and heterogeneous data patterns, etc.  To address the problems, we aim to reveal the moving objects' view of areas by learning regions directly from their trajectories based on unsupervised machine learning techniques, and to capture the evolution of region structure by using a time-varying model.  Upon satisfying causal Markov assumption, causal inference can be made.

Nick_cummins Nicholas Cummins

Research interests: main area of research is the automatic classification of depressed voices using supervised machine learning techniques. 

Project Title: Depression in speech - effects and classification

Nick's research involves using speech processing and machine learning techniques to assess whether the voice can be used an objective marker for the diagnosis of clinical depression.

melissa Melissa Duell

Research interests:Network systems models, Traffic modelling methodologies, Sustainability models integrating the transport and electricity systems.

Project Title:  Modelling Dynamic Transport Network Conditions to Support User Information and System Evaluation Applications

Melissa is developing model variants to represent traffic volatility and furthermore conducting specific case studies of novel traffic assignment methodologies for large scale networks applications.

Ewald Enzinger

Research interests: Forensic voice comparison, speaker recognition, speech processing

Project Title: Forensic voice comparison

Ewald's research focuses on the application of speech processing and statistical modeling in the implementation of forensic voice comparison in the new paradigm for the evaluation of forensic evidence, using the likelihood-ratio framework, quantitative measurements, statistical models, and testing the degree of validity and reliability under specific casework conditions.

mojgang Mojgan Ghanavati

Research interests: Data mining and knowledge discovery, Customer Relationship Management, Electronic marketing, Electronic business models, Market Segmentation, Text retrieval, Knowledge Management. Semantic web, Recommender Systems.

Project Title:  Mining and Analysis for spatio-temporal multi-dimensional data

Chee_cheung Chee Cheun Huang

Research interests: Speech processing, Automatic phonetic segmentation and statistical modeling with applications in forensic voice comparison and automatic speaker recognition.

Project Title:  Forensic Voice Comparison (FVC)

Research focuses on improving the efficiency and performance of FVC systems by investigating automatic techniques for detecting speaker-discriminative segments of speech, and new statistical modeling and machine learning techniques that complement conventional FVC systems.

ahmadAhmad Alhossin Khawaji

Research interests: Evaluating trust using human and system behavior. Trust in social media and computer-mediated communication (CMC).

Project Title: Trust in social media and computer-mediated communication (CMC)

Ahmad is finding methods to assess the trust and study the factors that may affect the trust in these mediums.

Zelin Zelin Li

Research interests: computer vision, pattern recognition and machine learning, specifically on sparse coding, dictionary learning and object detection with application on thermal images. 

Xiang Xianghang Liu

Research interests:  Probabilistic graphical models, Statistical inference, Optimization

Nargess Nourbakhsh
Nargess Nourbakhsh

Research topics: Physiology and behaviour analysis and machine learning techniques especially in human-computer interactions and cognitive load measurement.

Project Title: Machine Learning Methods for Multimodal Cognitive Load Measurement

Yi Wang

Research topics: Unbounded Dictionary Learning, Visual Representation, Dependence Modelling, Data Association.

Project Title: Spatial/Temporal Dependent Visual Data Representation and Dimensionality Reduction

Spatial/temporal visual data is always over-redundant and highly-dependent. Yi's research is to discover the latent structure/patterns and dependence from the visual data.

Kun_yu Kun Yu

Research interests: Pen interaction & computing technologies; Cognitive load measurement and evaluation; Pattern recognition and statistic learning methods; Mobile social networking applications and services; and User interface design.

Project Title:  Cognitive Load Measurement via Pen Interactions

Kun's project aims at understanding the cognitive load experienced by the writer, via the analysis of writing performance and behaviors with statistic learning methods.


Queensland University of Technology and University of Queensland

Johnson_Fong Johnson Fong

Research interests: Ubiquitous Computing (improving the intelligibility and user control of context-aware applications, Modelling and reasoning of context information) and Network Security.


University of Melbourne

Bo_Han Bo Han

Research interest: Natural Language Processing, Social Media.

Project Title: Improve the utility of social media data (under BioTALA)

Social media data is noisy and massive. Bo's research objective is to clean the text and to concentrate on spatial-aware data, so that existing text mining algorithms can be more effective and efficient.

jeyhanlau Jey Han Lau

Research Interests: Topic Models, Probabilistic Graphical Models, Multiword Expressions, Terminology Extraction Social Media Text  Analysis, Distributional Semantics.

Project Title:  Topic Modelling

Most of Jey's research focuses on building NLP applications and evaluations of topic models.

Marco Marco Lui

Research interests: Language Identification, Text Categorization, Machine Learning, Natural Language Processing, Web-Scale Data, Online Forum Data.

Project Title:  Generalized language identification

Marco is investigate the problem of identifying the language of a written document without any a-priori knowledge of the domain it is drawn from.

Goce Goce Ristanoski

Research interests: Time series regression, Distribution change and event detection, Loss and error definition.

Project Title:  Data mining for time series

Goce's research is focusing on modification of regularized risk function and definition of new loss functions for time series regression, using quadratic mean error and distribution change information.

mahsa-salehi Mahsa Salehi

Research interests: anomaly detection, data stream mining, ensemble clustering, pattern recognition, data mining with application in Parkinson's Disease patients.

Project Title: Anomaly Detection in Data Streams Using Consensus Approach

Traditional approaches have drawbacks for detecting anomalies in data streams where the environment changes intermittently (switching). Mahsa’s research objective is a consensus based approach to overcome the problem of constructing a robust model of normal behaviour in the switching data stream.

Li_Wang Li Wang

Research interests:  Online Forums, Social Media, Natural Language Processing, Machine Learning, Information Retrieval.

Project Title:  Knowledge Discovery and Extraction of Domain-specific Web Data

Li's current research focus is on improving information access over troubleshooting-oriented technical user forums.

Lei Zhang

hejiazhenJiazhen He

Research interests: Data mining and Machine Learning, especially mining information networks.