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Dr Jiangang Ma

Lecturer, Information Technology

School of Engineering, IT and Phys. Sci.

Section/Portfolio:

Information Technology (Berwick)

Location:

Berwick Campus, Online

Biography

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.

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...

  • Conference Proceedings

OMWSC- An ontology-based model for Web services composition

Web services have been increasingly used to integrate and build business applications over the...