Data Science Researchers

Prof Hanlie Smuts

Position: Head of Department of Informatics

NRF rating: C2

Office: IT Building 5-78

http://www.hanliesmuts.com

ORCID: 0000-0001-7120-7787

As I have worked in industry until 2017, I work primarily in the field of Information Systems and Organisation focusing on

Knowledge exchange in organisation-outsource vendor relationships.
Management of knowledge assets and knowledge visualisation.
Enterprise Architecture and the application of knowledge about the enterprise.
The impact of digital business models / exponential organisations on knowledge management.
Combining knowledge in machines (Artificial Intelligence / Machine Learning) with knowledge in people for knowledge work.
Big data implications on knowledge management.
Industry 4.0 and big data management; disruptive technologies and business value.
Knowledge sharing in smart cities and digital twins.
Knowledge production in Society 5.0

The research domains that I investigate are are society 5.0, knowledge management, IT outsourcing, enterprise architecture, disruptive technologies and big data in organisations.

Topics that I am actively involved in are listed below. I will support students who are interested in related or similar research:

Any knowledge and knowledge management related research especially how it relates to IT outsourcing and Enterprise Architecture.
Aspects of Industry 4.0, digital disruption and digital transformation, such as the cross-functional nature of digital transformation strategies, alignment of Digital-IT-Business strategies over and above its alignment to business models.
The phenomenon of exponential organisations, often in the digital domain, their digital transformation and how they manage knowledge assets.
The impact and implication of big data on knowledge management in organisations.

These keywords and concepts are relevant to my research. Knowledge Management; Information Technology outsourcing; Enterprise Architecture; Digital Disruption; Digital Transformation; Big data; Knowledge visualisation; Artificial Intelligence for Knowledge Management (AI4KM); Knowledge Management for Development (KM4D).

View recent publication Collaboration of Human and Machine for Knowledge Work: An Organisational Transformation Framework for Data-driven Decision-making

Dr JP van Deventer

Position: Senior Lecturer

Office: IT Building 5-97

E-mail: [email protected]

ORCID: 0000-0002-3598-0921

My research generally focuses on IS and Organizations. I take an interdisciplinary view in applying mostly a quantitative approach to study the following research focus areas:

IT Value: Knowledge Representation, Enterprise Architecture, Unstructured Analytics, Text Analysis, Data Science
IS Implementation: Several domains of business, technology, people, infrastructure and market forces to change the Enterprise Architecture, symbolic representations of text and pattern analysis from one state to another

The research domains that I investigate include Knowledge Representation, Enterprise Architecture, Unstructured Analytics, Text Analysis and Data Science

Topics that I am actively involved in are listed below. I can support students who are committed to researching suitable topics in one of the following areas:

Enterprise Architecture in general and Knowledge Architecture in particular
Unstructured analytics and text analysis approaches
Fundamentals in Data Science and application thereof
Various forms of predictive modeling
The impact of artificial intelligence, big data and machine learning
Internet of things and the application of sensor networks
Pervasive and ubiquitous systems and computing especially security concerns
Ethics in general with a specific interest in concerns pertaining to procedural ethics

These keywords and concepts are relevant to my research. Knowledge Representation, Enterprise Architecture, Unstructured Analytics, Text Analysis, Data Science

View recent publication UGRansome1819: A Novel Dataset for Anomaly Detection and Zero-Day Threats

Mr Ridewaan Hanslo

Position: Lecturer

Office: IT Building 5-101

Email: [email protected]

My research generally focuses on Information Systems, Software Engineering, and Artificial Intelligence with specialised areas of study in:

Agile Project Management: Scrum adoption, Agile project success.
DevOps: DevOps environment success factors.
Distributed Ledger Technologies: DLT adoption, Blockchain.
Machine Learning: Predicting Agile project outcomes, agile adoption using regression analysis.
Natural language processing: Conversational agent technology factors, chatbot implementation, neural and statistical machine translation models.
Neural Networks: Deep learning transformer models, low-resourced languages.
Virtual Reality: Cybersickness, VR in Education and Training, VR in Gaming and Entertainment

The research domains that I investigate include - Agile practitioners, DevOps environments, DLT technologies, IT organizations, low-resourced languages, neural network architectures, NLP conversational agents, predictive analytics, virtual reality and software development practices.

Topics that I am actively involved in are listed below. I can support students who are committed to researching problems in one of the following:

Agile project success factors
Conversational agent technology implementation and use
DevOps success factors
DLT and Blockchain adoption
Named-entity recognition sequence tagging
Predicting agile project outcomes
Predictive analytics using Machine Learning and Neural Networks
Scrum adoption challenges
Virtual reality

Keywords and concepts relevant to my research: adoption, agile, agile practitioners, blockchain, chatbots, continuous delivery, continuous deployment, continuous integration, conversational agents, deep learning, devops, distributed ledger technology, IT organizations, low-resourced languages, machine learning, machine translation, natural language processing, neural network architectures, quantitative, scrum, software development, software engineering, statistical analysis, success factors, and virtual reality.

Dr Timothy Adeliyi

Position: Senior Lecturer

Office: IT Building, Room 5-76

Email: [email protected]

ORCID: 0000-0002-8034-1045

My research generally focuses on Data Science, IS, and organisations. I approach my research in the following specialized areas of study from a multidisciplinary perspective, using both qualitative and quantitative approaches:

Sentiment Analysis: The development of a hybridized sentiment analysis model for better public governance
Fake news: Detection of online fake news using ensemble machine learning
Analysing Channel Surfing Behaviour of IPTV Subscribers Using Machine Learning Models
E-learning monitoring and performance evaluation in education

The research domains that I investigate include 4IR, social media, multimedia systems, eGovernment, IS and organisations. Topics that I am actively involved in are listed below. I can support students who are committed to researching suitable topics in one of the following areas:

Ensemble machine learning and deep learning
Techniques for detecting rapid changes in the crime trends
Understanding the factors associated with credit card churning
Converged networks and wireless sensor network
Fake news and hate speech detection

The following keywords and concepts are relevant to my research: social media, multimedia systems, Fake news, crime trends, sentiment analysis, data science.

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