Teo Susnjak
Orcid: 0000-0001-9416-1435
According to our database1,
Teo Susnjak
authored at least 66 papers
between 2008 and 2025.
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Bibliography
2025
Ransomware Reloaded: Re-examining Its Trend, Research and Mitigation in the Era of Data Exfiltration.
ACM Comput. Surv., January, 2025
2024
ACM Trans. Interact. Intell. Syst., September, 2024
The Inadequacy of Reinforcement Learning From Human Feedback - Radicalizing Large Language Models via Semantic Vulnerabilities.
IEEE Trans. Cogn. Dev. Syst., August, 2024
IEEE Trans. Artif. Intell., June, 2024
Beyond Predictive Learning Analytics Modelling and onto Explainable Artificial Intelligence with Prescriptive Analytics and ChatGPT.
Int. J. Artif. Intell. Educ., June, 2024
Transfer Learning on Transformers for Building Energy Consumption Forecasting - A Comparative Study.
CoRR, 2024
Image First or Text First? Optimising the Sequencing of Modalities in Large Language Model Prompting and Reasoning Tasks.
CoRR, 2024
Over the Edge of Chaos? Excess Complexity as a Roadblock to Artificial General Intelligence.
CoRR, 2024
CoRR, 2024
From COBIT to ISO 42001: Evaluating Cybersecurity Frameworks for Opportunities, Risks, and Regulatory Compliance in Commercializing Large Language Models.
CoRR, 2024
Inadequacies of Large Language Model Benchmarks in the Era of Generative Artificial Intelligence.
CoRR, 2024
From COBIT to ISO 42001: Evaluating cybersecurity frameworks for opportunities, risks, and regulatory compliance in commercializing large language models.
Comput. Secur., 2024
2023
Forecasting patient flows with pandemic induced concept drift using explainable machine learning.
EPJ Data Sci., December, 2023
Harnessing GPT-4 for generation of cybersecurity GRC policies: A focus on ransomware attack mitigation.
Comput. Secur., November, 2023
Forecasting patient demand at urgent care clinics using explainable machine learning.
CAAI Trans. Intell. Technol., September, 2023
Current stance on predictive analytics in higher education: opportunities, challenges and future directions.
Interact. Learn. Environ., August, 2023
Use of Predictive Analytics within Learning Analytics Dashboards: A Review of Case Studies.
Technol. Knowl. Learn., 2023
Effectiveness of a Learning Analytics Dashboard for Increasing Student Engagement Levels.
J. Learn. Anal., 2023
From Google Gemini to OpenAI Q* (Q-Star): A Survey of Reshaping the Generative Artificial Intelligence (AI) Research Landscape.
CoRR, 2023
Towards Clinical Prediction with Transparency: An Explainable AI Approach to Survival Modelling in Residential Aged Care.
CoRR, 2023
PRISMA-DFLLM: An Extension of PRISMA for Systematic Literature Reviews using Domain-specific Finetuned Large Language Models.
CoRR, 2023
Chat2VIS: Fine-Tuning Data Visualisations using Multilingual Natural Language Text and Pre-Trained Large Language Models.
CoRR, 2023
Applying BERT and ChatGPT for Sentiment Analysis of Lyme Disease in Scientific Literature.
CoRR, 2023
Chat2VIS: Generating Data Visualisations via Natural Language using ChatGPT, Codex and GPT-3 Large Language Models.
CoRR, 2023
Hate Speech Patterns in Social Media: A Methodological Framework and Fat Stigma Investigation Incorporating Sentiment Analysis, Topic Modelling and Discourse Analysis.
Australas. J. Inf. Syst., 2023
Chat2VIS: Generating Data Visualizations via Natural Language Using ChatGPT, Codex and GPT-3 Large Language Models.
IEEE Access, 2023
2022
Runtime prediction of big data jobs: performance comparison of machine learning algorithms and analytical models.
J. Big Data, 2022
The Application of Machine Learning Techniques for Predicting Match Results in Team Sport: A Review.
J. Artif. Intell. Res., 2022
Data quality challenges in educational process mining: building process-oriented event logs from process-unaware online learning systems.
Int. J. Bus. Inf. Syst., 2022
Predicting Football Match Outcomes with eXplainable Machine Learning and the Kelly Index.
CoRR, 2022
A Prescriptive Learning Analytics Framework: Beyond Predictive Modelling and onto Explainable AI with Prescriptive Analytics.
CoRR, 2022
Supporting Students' Academic Performance Using Explainable Machine Learning with Automated Prescriptive Analytics.
Big Data Cogn. Comput., 2022
On Developing Generic Models for Predicting Student Outcomes in Educational Data Mining.
Big Data Cogn. Comput., 2022
2021
A parallelization model for performance characterization of Spark Big Data jobs on Hadoop clusters.
J. Big Data, 2021
An Enhanced Parallelisation Model for Performance Prediction of Apache Spark on a Multinode Hadoop Cluster.
Big Data Cogn. Comput., 2021
2020
A comprehensive performance analysis of Apache Hadoop and Apache Spark for large scale data sets using HiBench.
J. Big Data, 2020
A systematic literature review: What is the current stance towards weight stigmatization in social media platforms?
Int. J. Hum. Comput. Stud., 2020
2019
The Application of Machine Learning Techniques for Predicting Results in Team Sport: A Review.
CoRR, 2019
Assessment of the Local Tchebichef Moments Method for Texture Classification by Fine Tuning Extraction Parameters.
CoRR, 2019
Aust. J. Intell. Inf. Process. Syst., 2019
Proceedings of the Neural Information Processing - 26th International Conference, 2019
Proceedings of the Australasian Conference on Information Systems, 2019
2016
Inf. Softw. Technol., 2016
Using Data-Driven and Process Mining Techniques for Identifying and Characterizing Problem Gamblers in New Zealand.
Complex Syst. Informatics Model. Q., 2016
Proceedings of the CAiSE'16 Forum, 2016
2015
Fast and Smooth Replanning for Navigation in Partially Unknown Terrain: The Hybrid Fuzzy-D*lite Algorithm.
Proceedings of the Robot Intelligence Technology and Applications 4, 2015
Automatic alignment and comparison on images of petri dishes containing cell colonies.
Proceedings of the 2015 International Conference on Image and Vision Computing New Zealand, 2015
Proceedings of the AI 2015: Advances in Artificial Intelligence, 2015
The Software Developer Cycle: Career demographics and the market clock: or, is SQL the new COBOL?
Proceedings of the 24th Australasian Software Engineering Conference, 2015
2014
Influences on regression testing strategies in agile software development environments.
Softw. Qual. J., 2014
Multi-Behaviour Robot Control using Genetic Network Programming with Fuzzy Reinforcement Learning.
Proceedings of the Robot Intelligence Technology and Applications 3, 2014
Characterisation of the Discriminative Properties of the Radial Tchebichef Moments for Hand-written Digits.
Proceedings of the 29th International Conference on Image and Vision Computing New Zealand, 2014
2013
Pattern Recognit. Lett., 2013
Colour segmentation for multiple low dynamic range images using boosted cascaded classifiers.
Proceedings of the 28th International Conference on Image and Vision Computing New Zealand, 2013
2012
Neural Comput. Appl., 2012
Proceedings of the STAIRS 2012, 2012
Proceedings of the Robot Intelligence Technology and Applications 2012, 2012
2011
Proceedings of the 19th European Signal Processing Conference, 2011
A New Ensemble-Based Cascaded Framework for Multiclass Training with Simple Weak Learners.
Proceedings of the Computer Analysis of Images and Patterns, 2011
2010
Proceedings of the Structural, 2010
Adaptive Ensemble Based Learning in Non-stationary Environments with Variable Concept Drift.
Proceedings of the Neural Information Processing. Theory and Algorithms, 2010
2008
Proceedings of the Advances in Neuro-Information Processing, 15th International Conference, 2008