Dr. Jiangang Ma
Senior Lecturer, Information Technology
Dr Jiangang (Mike) Ma’s research expertise in information technology includes data science, machine learning, algorithms design, Internet of Things, cloud computing, and health informatics. Recently, Dr Ma has focused on data mining, deep learning and machine learning, particularly the design of new algorithms for data streams processing, outlier detection and pattern classification for health applications.
Mike’s research is informed by several years of industrial experience as a professional software engineer. He has published over 40 research papers for leading international journals and conferences, including IEEE International Conference on Data Engineering.
Mike is currently a Lecturer in information technology at Federation University Australia. Previously, he worked as a lecturer in data science and statistics with James Cook University and as a research fellow working on a couple of ARC funded research projects at the University of Adelaide and Victoria University, where he earned his PhD in computer science.
Bilateral Insider Threat Detection: Harnessing Standalone and Sequential Activities with Recurrent Neural Networks
Detection and explanation of anomalies in healthcare data
Detection of Anomalies and Explanation in Cybersecurity
A New Dimensionality-Unbiased Score for Efficient and Effective Outlying Aspect Mining
Anomaly Detection on Health Data
Enhancing dynamic ECG heartbeat classification with lightweight transformer model
Human pose based video compression via forward-referencing using deep learning
sGrid++: Revising Simple Grid Based Density Estimator for Mining Outlying Aspect
Image Preprocessing in Classification and Identification of Diabetic Eye Diseases
Diabetic eye disease (DED) is a cluster of eye problem that affects diabetic patients....
Mining Outlying Aspects on Healthcare Data
Active model selection for positive unlabeled time series classification
Positive unlabeled time series classification (PUTSC) refers to classifying time series with a...
A framework for cardiac arrhythmia detection from IoT-based ECGs
Cardiac arrhythmia has been identified as a type of cardiovascular diseases (CVDs) that causes...
A New Effective and Efficient Measure for Outlying Aspect Mining
Outlying Aspect Mining (OAM) aims to find the subspaces (a.k.a. aspects) in which a given query...
A weighted overlook graph representation of eeg data for absence epilepsy detection
Absence epilepsy is one of the most common types of epilepsy. The diagnosis of absence epilepsy...
Enhancing Linear Time Complexity Time Series Classification with Hybrid Bag-Of-Patterns
In time series classification, one of the most popular models is Bag-Of-Patterns (BOP). Most BOP...
Adversarial Heterogeneous Network Embedding with Metapath Attention Mechanism
Heterogeneous information network (HIN)-structured data provide an effective model for practical...
A Framework for Discovering Variable-length Motifs in Medical Data Streams
In this paper, we explore two key problems in time series motif discovery: releasing the...
Discovering regularities from traditional Chinese medicine prescriptions via bipartite embedding model
Regularities analysis for prescriptions is a significant task for traditional Chinese medicine...
PU-shapelets: Towards pattern-based positive unlabeled classification of time series
Real-world time series classification applications often involve positive unlabeled (PU) training...
Survey of Cloud SLA Assurance in Pre-interaction and Post-interaction Start Time Phases
Service level agreements (SLAs) are contracts that define the responsibilities, rights and...
Cloud Service Description Model: An Extension of USDL for Cloud Services
There are a variety of well-designed specification-modelling-languages serving Internet services,...
D-ECG: A dynamic framework for cardiac arrhythmia detection from IoT-based ECGs
Cardiac arrhythmia has been identified as a type of cardiovascular diseases (CVDs) that causes...
Limited-length suffix-array-based method for variable-length motif discovery in time series
In this paper, we explore two key problems in time series motif discovery: releasing the...
User-oriented Cloud SLA Assurance Framework
Cloud computing technology presents new challenges in terms of service provisions and...
THCluster: Herb supplements categorization for precision traditional Chinese medicine
There has been a continuing demand for traditional and complementary medicine worldwide. A...
Cloud-FuSeR: Fuzzy ontology and MCDM based cloud service selection
With the rapidly growing number of available Cloud services, to fulfill the need for ordinary...
Exploring data mining techniques in medical data streams
Data stream mining has been studied in diverse application domains. In recent years, a population...
Mining actionable knowledge using reordering based diversified actionable decision trees
Actionable knowledge discovery plays a vital role in industrial problems such as Customer...
Supervised anomaly detection in uncertain pseudoperiodic data streams
Uncertain data streams have been widely generated in many Web applications. The uncertainty in...
Efficiently managing uncertain data in RFID sensor networks
The ability to track and trace individual items, especially through large-scale and distributed...
Refining adverse drug reactions using association rule mining for electronic healthcare data
Cloud computing technology presents new challenges in terms of service provisions and...
Advances in ambient intelligence technologies
[No abstract available]
A hybrid fuzzy framework for Cloud service selection
QoS-based service rating has made positive contributions to the area of service selection....
Keyword search over web documents based on earth mover’s distance
Keyword search is widely used in many practical applications. Unfortunately, most keyword-based...
Multicriteria decision making with fuzziness and criteria interdependence in cloud service selection
With the advent of Cloud computing and subsequent big data, online decision makers usually find...
ServiceXplorer: A similarity-based Web service search engine
Finding relevant Web services and composing them into value-added applications is becoming...
User-centric ambient information systems and applications
[No abstract available]
A framework for processing uncertain RFID data in supply chain management
Radio Frequency Identification (RFID) is widely used to track and trace objects in supply chain...
A framework for distributed managing uncertain data in RFID traceability networks
The ability to track and trace individual items, especially through large-scale and distributed...
A temporal-based model of uncertain RFID data
Radio Frequency Identification (RFID) technology is widely used in object tracking and tracing....
Modeling sovereign RFID data streams in collaborative traceable networks
In the emerging environment of the Internet of Things (IoT), through the connection of billions...
WS-finder: A framework for similarity search of web services
Most existing Web service search engines employ keyword search over databases, which computes the...
Efficiently supporting secure and reliable collaboration in scientific workflows
Recently, workflow technologies have been increasingly used in scientific communities. Scientists...
Efficiently finding web services using a clustering semantic approach
Efficiently finding Web services on the Web is a challenging issue in service-oriented computing....
Web services discovery based on latent semantic approach
With an ever-increasing number of Web services being available, finding desired Web service is...
A probabilistic semantic approach for discovering web services
Service discovery is one of challenging issues in Service-Oriented computing. Currently, most of...
Discovering web services based on probabilistic latent factor model
Recently, web services have been increasingly used to integrate and build business applications...
Discovering User Access Pattern Based on Probabilistic Latent Factor Model
There has been an increased demand for characterizing user access patterns using web mining...
OMWSC- An ontology-based model for Web services composition
Web services have been increasingly used to integrate and build business applications over the...