Prof Alta van der Merwe

Position: Deputy Dean Teaching and Learning (EBIT)

NRF rating: B3

Office: IT Building 5-82.2

E-mail: [email protected]

ORCID: 0000-0002-3652-7512

My research generally focuses on IS and Organizations. The majority of my students use design science as their research approach, mainly using qualitative data collection.  My students are involved in the following research focus areas:

• Enterprise Architecture (EA):  EA approaches, data and process management within EA, modelling and adoption.
• Society 5.0: Disruptive technologies, Data Science related topics from an Organization perspective.
• Design: Design of systems within an IS organization, Social-technical systems.
• Design Science: Studying the approach of Design Science.

The research domains that I investigate include IS organizations, Education. 

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, Enterprise Architecture Management
• Innovation Cycles, methodologies, practices
• Design Science;
• IT Strategy for Society 5.0.

These keywords and concepts are relevant to my research. Enterprise Architecture, Enterprise Architecture Management, Innovation, Design, Data Science, Design Science, Industry 4.0.

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Prof Machdel Matthee

Position: Associate Professor 

NRF rating: C2

Office: IT Building 5- 58

E-mail: [email protected]

ORCID: 0000-0002-6973-1798

My research generally focuses on 21st century skills (skills needed to function in a technology-dominated society) and the teaching thereof. The aim is to provide quality education and promote social well-being:

Keywords and concepts relevant to my research: Critical thinking, Change, Societal Implications, ICT and education, Disruption, Social media, Future, 21st century skills, Society 5.0, well-being.

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Prof Hanlie Smuts

Position: Head of Department of Informatics

NRF rating: C2

Office: IT Building 5-78

E-mail: [email protected]

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).

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Dr Henk Pretorius

Position: Senior Lecturer

Office: IT Building 5-65

E-mail: [email protected]

ORCID: 0000-0003-2051-5290

My research in general focuses on IS in Organizations, but also include technology and sport. I prefer a qualitative research approach. Research areas (in various combinations) that I focus on include: 

• Governance, fraud and corruption;
• Process Management;
• Women in ICT;
• Innovative and future technologies (4IR, Robotic Process Automation, Artificial Intelligence, Social Media, etc.); and
• Technology and sport.

IS research is of interdisciplinary nature that involves various organizational research contexts. The exception may be technology and sport. 

Keywords: Process Management (Business), Women in ICT, Governance, Fraud, Corruption, 4IR, Robotic Process Automation, Artificial Intelligence, Social Media, Innovation, Technology in Sport, Disruptive technologies.

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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

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Dr Lizette Weilbach

Position: Senior lecturer 

Office: IT Building 5-69

E-mail: [email protected]

ORCID: 0000-0002-0827-2444

The research domains that I focus on include IS and organisations, Society 5.0, disruptive technologies and UX (User Experience) Design.  I am particularly interested in the way in which information technology affects the social and emotional well-being of people.  This includes, but is not limited to:

• The use of Social media
• The use of AI
• FOMO
• The overuse of technology
• Cyber-bullying

IS development and design is another passion.  I have presented multiple business & systems analysis and design courses to industry.  My latest interest in this field focuses on UX design and I’m interested in pursuing research which focusses on evaluating and enhancing the human computer interaction aspects of IS. 

I’ve been teaching in the field of IS for many years, and thus also have an interest in ICT to support quality education.  Here my focus is on ICT to enhance teaching and learning: the use of current tools, techniques, and approaches available for both face-to-face and online teaching and learning.

I can support students wanting to do research on all the topics mentioned above.

Keywords: Society 5.0; AI use and consequences; disruptive technologies; UX Design; Social Media use; cyberbullying; technology to enhance teaching and learning.

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Prof Tendani Mawela

Position: Associate Professor

NRF rating: Y2

Office: IT Building 5-99

E-mail: [email protected]

ORCID: 0000-0003-0574-3340

My research generally focuses on IS and Organizations. I take an interdisciplinary view in applying either qualitative or quantitative approaches to study the following research focus areas:

• Digital Government (E-Government). The use of information and communication technologies to support the policies and operations of government. 
• ICT for Development (ICT4D). The relation between information and communication technologies and development.
• Digital Skills (E-Skills). The skills and capabilities required to take advantage of the opportunities afforded by ICT’s and mobile technologies.

The research domains that I investigate include Public sector organizations, citizens and other e-government user communities. 

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 areas:

• ICTs for service delivery, citizen participation and governance.
• Social media for civic engagement and political participation.
• The role of ICTs in social and financial inclusion.
• Opportunities, challenges and implications of emerging and disruptive technologies in government.
• The systematic review of Digital Government, Digital Skills and ICT4D literature.

These keywords and concepts are relevant to my research. Digital Government, e-Government, Mobile Government (m-Government), Smart Governance, Digital skills, e-Participation, e-Democracy, ICT  for  Development (ICT4D), Sustainable Development Goals (SDGs), Digital Divide, Digital Inclusion, Social Media, Systematic Literature Reviews. 

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Mr Mike Nkongolo

Position: Lecturer

Office:  IT Building, Room 5-100

Email: [email protected]

ORCID: 0000-0003-0938-113X

My research focuses on Network Security, Deep Packet Inspection (DPI), Artificial Intelligence (AI), Natural Language Processing (NLP), and Machine Learning (ML). I take a multidisciplinary view in applying experimental and model-building approaches to work in the following specialized areas of Information Science (IS), Computer Science (CS), and Information Technology (IT):

• Intrusion Detection Problems and cyber threats analysis. The application of Intrusion Detection Systems and Intrusion Prevention Systems for zero-day threats detection.
• Machine Learning. The role of various ML algorithms for subscriber service analysis, social media classification, and network optimization.
• Artificial Intelligence. Application of Knowledge Representation and Reasoning (KRR) in AI (e.g., game design or implementation, game theory, ludology, recommendation systems, and discrete optimization for big data). 
• Data Science and NLP. The role of Sentiment Analysis (SA) to study online Corporate Reputation.
• Web mining and search engine optimization.

The research domains that I investigate also include software testing, quality assurance, systems engineering, the criticality of network infrastructures, and network traffic anomaly. I have also developed an interest in Bioinformatics (Computational Chemistry). 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:

• 0-day threats analysis (detection and prevention).
• Time series forecasting using DPI data.
• The role of network traffic management in the prediction of subscriber behaviours.
• The classification of social networks for subscriber behaviour analysis.
• Game design and implementation (Indigenous Knowledge Games).
• Online Corporate Reputation analysis using SA.
• Ethical, security, and privacy issues related to Data Science and Big Data. 
• Telecommunication (cybersecurity and ubiquitous computing).

The keywords and concepts relevant to my research are zero-day threats analysis, artificial intelligence, machine learning, natural language processing, time series forecasting, subscriber management, social media classification, sentiment analysis, data science, data insights, anomaly detection, big data, reputation analysis, telecommunication engineering, pattern recognition, web mining, and search engine optimization.

 Mr Ridewaan Hanslo

 Position: Lecturer

 Office: IT Building 5-101

 Email: [email protected]

• 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.

• 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