Research/Scholarly/Creative Works

• Mohammadhassan N., Mitrovic A., Neshatian K. and Dunn J.. (2020) Automatic quality assessment of comments in active video watching using machine learning techniques. In So H-J; Rodrigo MM; Mason J; Mitrovic A (Eds). I: 1-10. Taiwan: Asia-Pacific Society for Computers in Education. (Conference Contributions - Published)

• Tupper A. and Neshatian K.. (2020) Evolving Neural Network Agents to Play Atari Games with Compact State Representations. In Coello Coello CA (Eds). GECCO '20- Proceedings of the Genetic and Evolutionary Computation Conference CompanionACM. (Conference Contributions - Published)

• Fabic GVF., Mitrovic A. and Neshatian K. (2019) Evaluation of Parsons Problems with Menu-Based Self-Explanation Prompts in a Mobile Python Tutor. International Journal of Artificial Intelligence in Education 29(4): 507-535. http://dx.doi.org/10.1007/s40593-019-00184-0. (Journal Articles)

• Neshatian K. and Varn L.. (2019) Feature Bundles and their Effect on the Performance of Tree-based Evolutionary Classification and Feature Selection Algorithms. In 2019 IEEE Congress on Evolutionary Computation, CEC 2019 - Proceedings: 1612-1619. http://dx.doi.org/10.1109/CEC.2019.8789951. (Conference Contributions - Published)

• Putri T., Mukundan R. and Neshatian K.. (2019) Circular Filtering and Neutrosophic Extraction of Vincent Van Gogh's Visible Brushstrokes. In IVCNZ 2018 Proceedings: 6. http://dx.doi.org/10.1109/IVCNZ.2018.8634702. (Conference Contributions - Published)

• Yamada S. and Neshatian K.. (2019) Comparison of Embedded and Wrapper Approaches for Feature Selection in Support Vector Machines. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 11671 LNAI: 149-161. http://dx.doi.org/10.1007/978-3-030-29911-8_12. (Conference Contributions - Published)

• Fabic G., Mitrovic A. and Neshatian K.. (2018) Adaptive Problem Selection in a Mobile Python Tutor. In Mitrovic A; Zheng J; Chen L; Chin D (Eds). UMAP '18 - Proceedings: 269-274. New York: ACM. http://dx.doi.org/10.1145/3213586.3225235. (Conference Contributions - Published)

• Fabic GV., Mitrovic A. and Neshatian K.. (2018) Supporting Novices and Advanced Students in Acquiring Multiple Coding Skills. In Yang JC (Eds). Proceedings ICCE 2018: 65-70. (Conference Contributions - Published)

• Fabic GVF., Mitrovic A. and Neshatian K. (2018) Investigating the effects of learning activities in a mobile Python tutor for targeting multiple coding skills. Research and Practice in Technology Enhanced Learning 13(1) http://dx.doi.org/10.1186/s41039-018-0092-x. (Journal Articles)

• Salah K., Chen X., Neshatian K. and Pretty C.. (2018) A hybrid control multi-agent cooperative system for autonomous bin transport during apple harvest. In ICIEA 2018 Proceedings: 644-649. http://dx.doi.org/10.1109/ICIEA.2018.8397794. (Conference Contributions - Published)

• Stockdill A. and Neshatian K.. (2018) Simulating neuromorphic reservoir computing: Abstract feed-forward hardware models. In IVCNZ 2017 Proceedings 2017-December: 7. http://dx.doi.org/10.1109/IVCNZ.2017.8402482. (Conference Contributions - Published)

• Yamada S. and Neshatian K.. (2018) Improving representation in benchmarking of binary PSO algorithms. In Mitrovic T; Bing X; Xiaodong L (Eds). Lecture Notes in Computer Science 11320 LNAI: 371-383. Springer Verlag. http://dx.doi.org/10.1007/978-3-030-03991-2_35. (Conference Contributions - Published)

• Neshatian K. and Varn, L.. (2017) On the Existence of Feature Bundles and their Effect on Symbolic Regression Algorithms. In IEEE. (Conference Contributions - Published)

• Putri T., Mukundan R. and Neshatian K.. (2017) Artistic style characterization and brush stroke modelling for non-photorealistic rendering. In : 1-6. IEEE. http://dx.doi.org/10.1109/IVCNZ.2017.8402475. (Conference Contributions - Published)

• Yamada S. and Neshatian K.. (2017) Hyper-parameter search in support vector machines using PSO with cellular fitness approximation. In 2017 IEEE Symposium Series on Computational Intelligence, SSCI 2017, Honolulu, HI, USA, November 27 - Dec. 1, 2017: 1-8. http://dx.doi.org/10.1109/SSCI.2017.8285406. (Conference Contributions - Published)

• Yamada S. and Neshatian K.. (2017) Kernel construction and feature subset selection in support vector machines. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 10593 LNCS: 605-616. http://dx.doi.org/10.1007/978-3-319-68759-9_49. (Conference Contributions - Published)

• Yamada S. and Neshatian K.. (2017) Multiple kernel learning with one-level optimization of radius and margin. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 10400 LNAI: 52-63. http://dx.doi.org/10.1007/978-3-319-63004-5_5. (Conference Contributions - Published)

• Chen X., Mitrovic A. and Mathews M.. (2016) How to present example-based support adaptively in intelligent tutoring systems. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 9684: 538-540. (Conference Contributions - Published)

• Stockdill A. and Neshatian K.. (2016) Restricted echo state networks. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 9992 LNAI: 555-560. http://dx.doi.org/10.1007/978-3-319-50127-7_49. (Conference Contributions - Published)

• Hong JK., Mitrovic A. and Neshatian K.. (2015) Predicting quitting behavior in SQL-tutor. In Proceedings of the 23rd International Conference on Computers in Education, ICCE 2015: 37-45. (Conference Contributions - Published)

• Najar AS., Mitrovic A. and Neshatian K.. (2015) Identifying learner differences in example processing from eye gaze data. In Proceedings of the 23rd International Conference on Computers in Education, ICCE 2015: 19-26. (Conference Contributions - Published)

• Yamada S., Neshatian K. and Sainudiin R.. (2015) Optimal Hyper-Parameter Search in Support Vector Machines Using Bezier Surfaces. In Lecture Notes in Computer Science (LNCS), Vol 9457: AI 2015 9457: 623-629. http://dx.doi.org/10.1007/978-3-319-26350-2_55. (Conference Contributions - Published)

• Young TJ. and Neshatian K.. (2015) The Effect of Reactant and Product Selection Strategies on Cycle Evolution in an Artificial Chemistry. In Lecture Notes in Computer Science (LNCS), Vol 8955: ACALCI-2015: 310-322. http://dx.doi.org/10.1007/978-3-319-14803-8_24. (Conference Contributions - Published)

• Algarni M., Martin B., Bell T. and Neshatian K.. (2014) Simple Arabic Stemmer. In : 1803-1806. (Conference Contributions - Published)

• Cresswell-Miley K. and Neshatian K.. (2014) A Stepwise Multi-centroid Classification Learning Algorithm with GPU Implementation. In Lecture Notes in Computer Science (LNCS) - SEAL 2014 8886: 347-358. http://dx.doi.org/10.1007/978-3-319-13563-2_30. (Conference Contributions - Published)

• Varn L. and Neshatian K. (2014) A Promising Direction towards Automatic Construction of Relevance Measures. In Alam S; Dobbie G; Koh YS; Rehman SU (Ed.), Biologically-Inspired Techniques for Knowledge Discovery and Data Mining: 221-235. Hershey: IGI Global. http://dx.doi.org/10.4018/978-1-4666-6078-6.ch010. (Chapters)

• de Jong J. and Neshatian K.. (2013) Binary Classification Using Genetic Programming: Evolving Discriminant Functions with Dynamic Thresholds. In Lecture Notes in Computer Science 7867: 464-474. http://dx.doi.org/10.1007/978-3-642-40319-4_40. (Conference Contributions - Published)

• Neshatian K. and Varn L.. (2013) On the Optimality of Subsets of Features Selected by Heuristic and Hyper-heuristic Approaches. In Lecture Notes in Computer Science 7867: 440-451. http://dx.doi.org/10.1007/978-3-642-40319-4_38. (Conference Contributions - Published)

• Young TJ. and Neshatian K.. (2013) A constructive artificial chemistry to explore open-ended evolution. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 8272 LNAI: 228-233. http://dx.doi.org/10.1007/978-3-319-03680-9_25. (Conference Contributions - Published)

• Young TJ. and Neshatian K.. (2013) A Constructive Artificial Chemistry to Explore Open-Ended Evolution. In Lecture Notes in Computer Science 8272: 228-233. http://dx.doi.org/10.1007/978-3-319-03680-9. (Conference Contributions - Published)

• Al-Sahaf H., Song A., Neshatian K. and Zhang M. (2012) Two-tier genetic programming: Towards raw pixel-based image classification. Expert Systems With Applications 39(16): 12291-12301. http://dx.doi.org/10.1016/j.eswa.2012.02.123. (Journal Articles)

• Hunt R., Neshatian K. and Zhang M.. (2012) A Genetic Programming Approach to Hyper-Heuristic Feature Selection. In Lecture Notes in Computer Science (LNCS) 7673:: 320-330. http://dx.doi.org/10.1007/978-3-642-34859-4_32. (Conference Contributions - Published)

• Hunt R., Neshatian K. and Zhang M.. (2012) Scalability analysis of genetic programming classifiers. In : 8pp. http://dx.doi.org/10.1109/CEC.2012.6256520. (Conference Contributions - Published)

• Neshatian K. and Zhang M.. (2012) Improving Relevance Measures Using Genetic Programming. In Lecture Notes in Computer Science (LNCS) 7244: 97-108. http://dx.doi.org/10.1007/978-3-642-29139-5_9. (Conference Contributions - Published)

• Neshatian K., Zhang M. and Andreae P. (2012) A filter approach to multiple feature construction for symbolic learning classifiers using genetic programming. IEEE Transactions on Evolutionary Computation 16(5): 645-661. http://dx.doi.org/10.1109/TEVC.2011.2166158. (Journal Articles)

• Abdulhamid F., Neshatian K. and Zhang M.. (2011) Genetic programming for evolving programs with loop structures for classification tasks. In : 202-207. http://dx.doi.org/10.1109/ICARA.2011.6144882. (Conference Contributions - Published)

• Al-Sahaf H., Neshatian K. and Zhang M.. (2011) Automatic feature extraction and image classification using genetic programming. In : 157-162. http://dx.doi.org/10.1109/ICARA.2011.6144874. (Conference Contributions - Published)

• Atkins D., Neshatian K. and Zhang M.. (2011) A domain independent genetic programming approach to automatic feature extraction for image classification. In : 238-245. http://dx.doi.org/10.1109/CEC.2011.5949624. (Conference Contributions - Published)

• Friedlander A., Neshatian K. and Zhang M.. (2011) Meta-learning and feature ranking using genetic programming for classification: variable terminal weighting. In : 941-948. http://dx.doi.org/10.1109/CEC.2011.5949719. (Conference Contributions - Published)

• Neshatian K. and Zhang M. (2011) Using genetic programming for context-sensitive feature scoring in classification problems. Connection Science 23(3): 183-207. http://dx.doi.org/10.1080/09540091.2011.630065. (Journal Articles)

• Neshatian K. (2010) Feature Manipulation with Genetic Programming. Wellington, New Zealand. Victoria University of Wellington. (Theses / Dissertations)

• Neshatian K. and Zhang M. (2009) Input space transformation in classification problems using genetic programming. University of Auckland, New Zealand: 7th New Zealand Computer Science Research Student Conference, 6-9 Apr 2009. (Conference Contributions - Other)

• Neshatian K. and Zhang M.. (2009) Dimensionality reduction in face detection: A genetic programming approach. In IEEE Conference Publications: 391-396. http://dx.doi.org/10.1109/IVCNZ.2009.5378375. (Conference Contributions - Published)

• Neshatian K. and Zhang M.. (2009) Genetic Programming for Feature Subset Ranking in Binary Classification Problems. In Lecture Notes in Computer Science 5481: 121-132. http://dx.doi.org/10.1007/978-3-642-01181-8_11. (Conference Contributions - Published)

• Neshatian K. and Zhang M.. (2009) Pareto front feature selection: Using genetic programming to explore feature space. In Proceedings: 1027-1034. http://dx.doi.org/10.1145/1569901.1570040. (Conference Contributions - Published)

• Neshatian K. and Zhang M.. (2009) Unsupervised elimination of redundant features using genetic programming. In Lecture Notes in Artificial Intelligence (subseries of Lecture Notes in Computer Science): AI 2009: Advances in Artificial Intelligence 5866: 432-442. http://dx.doi.org/10.1007/978-3-642-10439-8_44. (Conference Contributions - Published)

• Neshatian K. and Zhang M.. (2008) Genetic programming and class-wise orthogonal transformation for dimension reduction in classification problems. In Lecture Notes in Computer Science 4971: 242-253. http://dx.doi.org/10.1007/978-3-540-78671-9_21. (Conference Contributions - Published)

• Neshatian K. and Zhang M.. (2008) Genetic programming for performance improvement and dimensionality reduction of classification problems. In : 2811-2818. http://dx.doi.org/10.1109/CEC.2008.4631175. (Conference Contributions - Published)

• Neshatian K., Zhang M. and Andreae P.. (2008) Genetic programming for feature ranking in classification problems. In Lecture Notes in Computer Science 5361: 544-554. http://dx.doi.org/10.1007/978-3-540-89694-4_55. (Conference Contributions - Published)

• Neshatian K., Zhang M. and Johnston M.. (2007) Feature construction and dimension reduction using genetic programming. In Lecture Notes in Computer Science 4830: 160-170. http://dx.doi.org/10.1007/978-3-540-76928-6_18. (Conference Contributions - Published)

Review and Refereeing

Displaying all items.

• Genetic and Evolutionary Computation Conference, GECCO 2017 ( 2017 - 2021)
• NZCSRSC ( 2009 )
• IEEE Transaction of Evolutionary Computation ( 2010 - 2021)
• IEEE Transactions on Neural Systems and Rehabilitation Engineering ( 2014 - 2021)
• International Journals ( 2006 - 2011)

Research Groups