Dr Teo Susnjak staff profile picture

Contact details +64 (09) 414 0800  ext. 43146

Dr Teo Susnjak

Lecturer in Information Technology

Institute of Natural and Mathematical Sciences

Prior to his academic career, Teo was a touring Tennis Professional, representing New Zealand in the Davis Cup.

Following his sporting career, he pursued studies in Computer Science, being awarded a PhD for his research focusing in machine learning. He worked in industry as a machine learning analyst and still continues to research applied and practical aspects of machine learning, and more broadly artificial intelligence.

His recent interest in the emerging field of Data Science has expended his research to include Big Data technologies for data processing, wrangling and visualisation as well as process mining. 

Roles and Responsibilities

  • Data Science Major Leader
  • Member of the Information Sciences Program Management Committee
  • Member of the Board of the College of Sciences
  • Auckland Knowledge Exchange Hub representative for the College of Sciences

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Professional

Contact details

  • Ph: +64 9 414 0800 ext 43146
    Location: 19(c), Oteha Rohe, Building 106
    Campus: Albany

Qualifications

  • Bachelor of Science (Computer Science) - Massey University (2008)
  • Master of Science (Computer Science) - Massey University (2010)
  • Doctor of Philosophy (Computer Science) - Massey University (2012)

Prizes and Awards

  • Awarded the NZ Ministry of Science and Innovation Internship to investigate the feasability of implementing machine learning algorithms connected with my doctoral research, into the software owned by a NZ based company Compac Sorting Ltd. - NZ Ministry of Science and Innovation (2012)
  • Best Conference Paper Award for: Susnjak, T., Barczak, A., & Reyes, N. (2013). A Decomposition Machine-learning Strategy for Automated Fruit Grading. In Proceedings of the World Congress on Engineering and Computer Science (Vol. 2). - Organising committee for the World Congress on Engineering and Computer Science (2013)
  • Awarded the prize and the inclusion onto the "Dean's List of Outstanding Theses" for the PhD Thesis titled: "Efficient boosted ensemble-based machine learning in the context of cascaded frameworks" - Massey University (2013)

Research Expertise

Research Interests

Data science, machine learning, data mining, pattern recognition, artificial intelligence, expert systems, decision support systems, software engineering.

Area of Expertise

Field of research codes
Artificial Intelligence and Image Processing (080100): Computer Software (080300): Decision Support and Group Support Systems (080605): Information And Computing Sciences (080000): Information Systems (080600): Pattern Recognition and Data Mining (080109): Software Engineering (080309)

Keywords

Data Science
    - Data Wrangling
    - Data Visualisation
    - Big Data Technologies
    - Missing Data Imputation
    
Machine Learning
    - Ensemble-based learning
    - Boosting
    - Feature Selection Algorithms
    
Data Mining
    - Rule-based Induction Algorithms
    - Clustering
    
Artificial Intelligence
    - Decision Support Systems
    
Software Engineering
    - Test Driven Development
    - Regression Testing

Research Projects

Summary of Research Projects

Position Current Completed
Project Leader 1 0

Research Outputs

Journal

Suriadi, S., Susnjak, T., Ponder-Sutton, A., Watters, P., & Schumacher, CR. (2016). Using data-driven and process mining techniques for identifying and characterizing problem gamblers in New Zealand.. Complex Systems Informatics and Modeling Quarterly. 9, 44-66 Retrieved from https://csimq-journals.rtu.lv/
[Journal article]Authored by: Schumacher, C., Susnjak, T.
Parsons, D., Susnjak, T., & Mathrani, A. (2016). Design from detail: Analyzing data from a global day of coderetreat. Information and Software Technology. 75, 39-55
[Journal article]Authored by: Mathrani, A., Susnjak, T.
Parsons, D., Susnjak, T., & Lange, M. (2014). Influences on regression testing strategies in agile software development environments. Software Quality Journal. 22(4), 717-739
[Journal article]Authored by: Susnjak, T.
Parsons, D., Mathrani, A., Susnjak, T., & Leist, A. (2014). Coderetreats: Reflective practice and the game of life. IEEE Software. 31(4), 58-64
[Journal article]Authored by: Mathrani, A., Susnjak, T.
Parsons, D., Susnjak, T., & Lange, M. (2013). Influences on regression testing strategies in agile software development environments. Software Quality Journal. , 1-23
[Journal article]Authored by: Susnjak, T.
Susnjak, T., Barczak, A., Reyes, N., & Hawick, K. (2013). Coarse-to-fine multiclass learning and classification for time-critical domains. Pattern Recognition Letters. 34(8), 884-894
[Journal article]Authored by: Barczak, A., Reyes, N., Susnjak, T.
Susnjak, T., Barczak, ALC., & Hawick, KA. (2012). Adaptive cascade of boosted ensembles for face detection in concept drift. Neural Computing and Applications. 21(4), 671-682
[Journal article]Authored by: Barczak, A., Susnjak, T.

Book

Wang, W., Reyes, NH., Barczak, ALC., Susnjak, T., & Sincak, P. (2015). Multi-behaviour robot control using genetic network programming with fuzzy reinforcement learning. (pp. 151 - 158).
[Chapter]Authored by: Barczak, A., Reyes, N., Susnjak, T.
Reyes, NH., Barczak, ALC., Susnjak, T., Sincák, P., & Vaščák, J. (2013). Real-time fuzzy logic-based hybrid robot path-planning strategies for a dynamic environment. In Robotics: Concepts, Methodologies, Tools, and Applications. (pp. 1545 - 1571).
[Chapter]Authored by: Barczak, A., Reyes, N., Susnjak, T.
Susnjak, T., & Barczak, A. (2014). On combining boosting with rule-induction for automated fruit grading. In Transactions on Engineering Technologies: Special Issue of the World Congress on Engineering and Computer Science 2013. (pp. 275 - 290).
[Chapter]Authored by: Barczak, A., Reyes, N., Susnjak, T.
Reyes, NH., Barczak, ALC., Susnjak, T., Sinčák, P., & Vaščák, J. (2013). Real-time fuzzy logic-based hybrid robot path-planning strategies for a dynamic environment. In Efficiency and Scalability Methods for Computational Intellect. (pp. 115 - 141).
[Chapter]Authored by: Barczak, A., Reyes, N., Susnjak, T.

Thesis

Susnjak, T. (2012). Efficient boosted ensemble-based machine learning in the context of cascaded frameworks. (Doctoral Thesis)
[Doctoral Thesis]Authored by: Susnjak, T.Edited by: Barczak, A.
Susnjak, T. (2009). Accelerating classifier training using AdaBoost within cascades of boosted ensembles. (Master's Thesis)
[Masters Thesis]Authored by: Susnjak, T.

Report

Barczak, T.(2011). AA new 2D static hand gesture colour image dataset for asl gestures. (Report No. Volume 15, pp.12 - 20, ISSN 1175-2777). Institute of Information and Mathematical Sciences, Massey University Albany
[Technical Report]Authored by: Susnjak, T.
Susnjak, T., Barczak, ALC., & Hawick, KA.(2010). A Novel Bootstrapping Method for Positive Datasets in Cascades of Boosted Ensembles. (Report No. Volume 14, pp.17-24, ISSN 1175-2777). Institute of Information and Mathematical Sciences, Massey University Albany
[Technical Report]Authored by: Susnjak, T.
Susnjak, T., Barczak, ALC., & Hawick, KA.(2009). Accelerated Face Detector Training using the PSL Framework. (Report No. Volume 13, pp.68 - 80, ISSN 1175-2777). Institute of Information and Mathematical Sciences, Massey University Albany
[Technical Report]Authored by: Susnjak, T.

Conference

Reyes, NH., Barczak, ALC., Susnjak, T., & Jordan, A. (2017). Fast and smooth replanning for navigation in partially unknown terrain: The hybrid Fuzzy-D*lite algorithm. Advances in Intelligent Systems and Computing. Vol. 447 (pp. 31 - 41).
[Conference Paper in Published Proceedings]Authored by: Barczak, A., Reyes, N., Susnjak, T.
Alqahtani, S., Barczak, A., Reyes, N., Susnjak, T., & Ganley, A.Automatic alignment and comparison on images of petri dishes containing cell colonies. International Conference Image and Vision Computing New Zealand. 2151-2191.
[Conference]Authored by: Barczak, A., Susnjak, T.
Suriadi, S., Susnjak, T., Ponder-Sutton, AM., Watters, PA., & Schumacher, C.Characterizing problem gamblers in New Zealand: A novel expression of process cubes. CEUR Workshop Proceedings. (pp. 185 - 192). 1613-0073.
[Conference]Authored by: Schumacher, C., Susnjak, T.
Bayati, S., Parsons, D., Susnjak, T., & Heidary, M.Big data analytics on large-scale socio-technical software engineering archives. 2015 3rd International Conference on Information and Communication Technology, ICoICT 2015. (pp. 65 - 69).
[Conference]Authored by: Susnjak, T.
Susnjak, T., Kerry, D., Barczak, A., Reyes, N., & Gal, Y. (2015). Wisdom of crowds: An empirical study of ensemble-based feature selection strategies. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 9457 (pp. 526 - 538).
[Conference Paper in Published Proceedings]Authored by: Barczak, A., Reyes, N., Susnjak, T.
Parsons, D., Susnjak, T., & Mathrani, A. (2015). The software developer cycle: Career demographics and the market clock : SQL the new COBOL?. ACM International Conference Proceeding Series. Vol. 28-September-2015 (pp. 86 - 90).
[Conference Paper in Published Proceedings]Authored by: Mathrani, A., Susnjak, T.
Barczak, ALC., susnjak, T., & Reyes, NH. (2014). Characterisation of the discriminative properties of the radial tchebichef moments for hand-written digits. Poster session presented at the meeting of 29th International Conference on Image and Vision Computing New Zealand, IVCNZ 2014. Hamilton
[Conference Poster]Authored by: Barczak, A., Reyes, N., Susnjak, T.
Barczak, ALC., Susnjak, T., & Reyes, NH. (2014). Characterisation of the discriminative properties of the Radial Tchebichef Moments for hand-written digits. ACM International Conference Proceeding Series. Vol. 19-21-November-2014 (pp. 154 - 159).
[Conference Paper in Published Proceedings]Authored by: Barczak, A., Reyes, N., Susnjak, T.
Susnjak, T., Barczak, A., & Reyes, N. (2013). A decomposition machine-learning strategy for automated fruit grading. Lecture Notes in Engineering and Computer Science. Vol. 2 (pp. 819 - 825).
[Conference Paper in Published Proceedings]Authored by: Barczak, A., Reyes, N., Susnjak, T.
Barczak, ALC., Susnjak, T., Reyes, NH., & Jonhson, MJ. (2013). Colour Segmentation for Multiple Low Dynamic Range Images using Boosted Cascaded Classifiers. (pp. 136 - 141). : IVCNZ 2013 (International Conference on Image and Vision Computing New Zealand
[Conference Paper in Published Proceedings]Authored by: Barczak, A., Johnson, M., Reyes, N., Susnjak, T.
Reyes, NH., Barczak, ALC., & Susnjak, T. (2013). Tuning fuzzy-based hybrid navigation systems using calibration maps. Advances in Intelligent Systems and Computing. Vol. 208 AISC (pp. 713 - 722).
[Conference Paper in Published Proceedings]Authored by: Barczak, A., Reyes, N., Susnjak, T.
Reyes, N., Barczak, A., & Susnjak, T. (2012, December). Tuning fuzzy-based hybrid navigation systems using calibration maps. Presented at The 1st International Conference on Robot Intelligence Technology and Applications 2012 (RITA 2012). Gwangju, South Korea.
[Conference Oral Presentation]Authored by: Barczak, A., Reyes, N., Susnjak, T.
Susnjak, T., Barczak, A., & Reyes, N. (2012, August). Multiclass cascades for ensemble-based boosting algorithms. Presented at Proceedings of the Sixth Starting AI Researchers' Symposium. Montpellier, France.
[Conference Oral Presentation]Authored by: Susnjak, T.
Susnjak, T., Barczak, A., Reyes, N., & Hawick, K. (2012, August). Multiclass cascades for ensemble-based boosting algorithms. Presented at ECAI 2012: 20th European Conference on Artificial Intelligence. Montpellier, France.
[Conference Oral Presentation]Authored by: Susnjak, T.
Mendonca, L., Barazani, B., Chaves, B., Torikai, D., Ibrahim, R., Piazzeta, M., . . . Susnjak, T.Study of a Copper Capacitive MEMS as a Sensor for Automotive Fuel Evaluation.
[Conference Paper]Authored by: Susnjak, T.
Susnjak, T., Barczak, A., Reyes, N., & Hawick, K. (2012). Multiclass cascades for ensemble-based boosting algorithms. Frontiers in Artificial Intelligence and Applications. Vol. 241 (pp. 330 - 335).
[Conference Paper in Published Proceedings]Authored by: Barczak, A., Reyes, N., Susnjak, T.
Susnjak, T., Barczak, A., Reyes, N., & Hawick, K. (2011). A new ensemble-based cascaded framework for multiclass training with simple weak learners. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 6854 LNCS (pp. 563 - 570).
[Conference Paper in Published Proceedings]Authored by: Barczak, A., Reyes, N., Susnjak, T.
Susnjak, T., Barczak, A., & Hawick, K. (2010, August). A modular approach to training cascades of boosted ensembles. Presented at Joint International Association for Pattern Recognition International Workshop, Structural and Syntactic Pattern Recognition and Statistical Techniques in Pattern Recognition 2010 Proceedings
[Conference Oral Presentation]Authored by: Susnjak, T.
Susnjak, T., Barczak, ALC., & Hawick, KA. (2010). Adaptive ensemble based learning in non-stationary environments with variable concept drift. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 6443 LNCS (pp. 438 - 445).
[Conference Paper in Published Proceedings]Authored by: Barczak, A., Susnjak, T.
Susnjak, T., Barczak, AL., & Hawick, KA. (2010). A modular approach to training cascades of boosted ensembles. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 6218 LNCS (pp. 640 - 649).
[Conference Paper in Published Proceedings]Authored by: Barczak, A., Susnjak, T.
Susnjak, T., & Barczak, ALC. (2009). Accelerated classifier training using the PSL cascading structure. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 5506 LNCS (pp. 945 - 952).
[Conference Paper in Published Proceedings]Authored by: Barczak, A., Susnjak, T.
Barczak, ALC., Reyes, NH., Susnjak, T., & Johnson, MJ. (2011). Real-time computation of moment invariants combined with contrast stretching. European Signal Processing Conference. (pp. 544 - 548).
[Conference Paper in Published Proceedings]Authored by: Barczak, A., Johnson, M., Reyes, N., Susnjak, T.

Other

Susnjak, T. (2013, April). On Fruit Sorting and Grading using Boosting and Rule Induction Algorithms. In Massey University I.T. Seminar.
[Oral Presentation]Authored by: Susnjak, T.
Susnjak, T. (2013, October). A Decomposition Machine-learning Strategy for Automated Fruit Sorting. In Massey University I.T. Seminar.
[Oral Presentation]Authored by: Susnjak, T.
Barczak, A., reyes, N., Abastillas, A., Piccio, A., & Susnjak, T. (2012). MU_HandImages_ASL. Retreived from http://www.massey.ac.nz/~albarcza/gesture_dataset2012.html
[Dataset]Authored by: Barczak, A., Reyes, N., Susnjak, T.

Consultancy and Languages

Languages

  • German
    Spoken ability: Average
    Written ability: Average
  • Croatian
    Spoken ability: Average
    Written ability: Average
  • English
    Spoken ability: Excellent
    Written ability: Excellent

Supervision and Teaching

Summary of Doctoral Supervision

Position Current Completed
Supervisor 1 0

Teaching

  • Data science papers
  • Analytics papers
  • Application software development
  • Software engineering
  • Software engineering project supervision

Courses Coordinated

  • 158.222 Data Wrangling and Machine Learning
  • 158.333 Applied Machine Learning and Data Visualisation
  • 158.739 Introduction to Analytics
  • 158.755 Data Science - Making Sense of Data
  • 158.796 Special Topic
  • 247.310 ICT Industry Engagement Project

Current Doctoral Supervision

Supervisor of:

  • Rahila Umer - PhD
    Predicting student's performance through data mining approaches

Media and Links

Media

  • 30 Nov 2015 - Newspaper
    Data science: Making use of a valuable by-product
    http://m.nzherald.co.nz/technology/news/article.cfm?c_id=5&objectid=11551722 Together with PVC Ray Geor, I wrote an article for the Herald discussing the opportunities that Data Science is providin
  • 30 Jul 2016 - Television
    Killer robots fuelled by artificial intelligence
    https://tvnz.co.nz/seven-sharp/killer-robots-fuelled-artificial-intelligence-you-scared-video-6365632 In mid 2015, Prof Stephen Hawking wrote a letter warning about the potential threat that AI pose
  • 25 Jan 2016 - Magazine
    The ‘internet of things’ and the data challenge
    http://viewer.zmags.com/publication/c905856a#/c905856a/4 Precision agriculture is one of the key industries set to be revolutionised by the deluge of data that is about to become available through

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