STAFF PROFILE
Associate Professor Vic Ciesielski
Position:
Associate Professor
College / Portfolio:
STEM College
School / Department:
STEM|School of Computing Technologies
Phone:
+61399252926
Email:
vic.ciesielski@rmit.edu.au
Campus:
City Campus
Contact me about:
Research supervision
- Peng, Y.,Song, A.,Ciesielski, V.,Abokela, H.,Chang, X. (2022). PRE-NAS: predictor-assisted evolutionary neural architecture search In: GECCO '22: Proceedings of the Genetic and Evolutionary Computation Conference, Boston, United States of America, 09/07/2022 -13/07/2022
- Peng, Y.,Ciesielski, V. (2020). Stylised Image Generation from Deep Neural Networks In: Proceedings of the International Joint Conference on Neural Networks (IJCNN 2020), Glasgow, United Kingdom, 19-24 July 2020
- Banal, S.,Ciesielski, V. (2020). A deep learning neural network for classifying good and bad photos In: Proceedings of the 9th International Conference on Artificial Intelligence in Music, Sound, Art and Design (EvoMUSART 2020), Seville, Spain, 15-17 April 2020
- Campbell, A.,Ciesielski, V.,Qin, K. (2016). Node label matching improves classification performance in deep belief networks In: Proceedings of the IEEE Annual International Joint Conference on Neural Networks (IJCNN 2016), Vancouver, Canada, 24-29 July 2016
- Campbell, A.,Ciesielski, V.,Qin, A. (2015). Feature discovery by deep learning for aesthetic analysis of evolved abstract images In: Evolutionary and Biologically Inspired Music, Sound, Art and Design, Copenhagen, Denmark, 8-10 April 2015
- Xie, F.,Song, A.,Ciesielski, V. (2014). Genetic programming based activity recognition on a smartphone sensory data benchmark In: Proceedings of the IEEE Congress on Evolutionary Computation (CEC 2014), Beijing, China, 6-11 July 2014
- Bishop, A.,Ciesielski, V.,Trist, K. (2014). Feature construction using genetic programming for classification of images by aesthetic value In: Proceedings of the 3rd International Conference on Evolutionary and Biologically Inspired Music, Sound, Art and Design (EVOMUSART-2014), Lecture Notes in Computer Science Volume 8601, Granada; Spain, 23-25 April 2014
- Dau, H.,Song, A.,Xie, F.,Salim, F.,Ciesielski, V. (2014). Genetic Programming for Channel Selection from Multi-stream Sensor Data with Application on Learning Risky Driving Behaviours In: Proceddings of the10th International Conference 2014 (LNCS 8886), Dunedin, New Zealand, 15-18 December 2014
- Dau, H.,Ciesielski, V.,Song, A. (2014). Anomaly detection using replicator neural networks trained on examples of one class In: Proceedings of 10th International Conference on Simulated Evolution And Learning, SEAL 2014, Dunedin, New Zealand, 15-18 December 2014
- Xie, F.,Song, A.,Ciesielski, V. (2014). Learning patterns of states in time series by genetic programming In: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 8886, 371 - 382
Note: Supervision projects since 2004
2 PhD Current Supervisions8 PhD Completions and 2 Masters by Research Completions
Evolutionary computing, computer vision, artificial intelligence, genetic programming, robot soccer.
- Searching, combining and interpreting tabular data in scientific papers. Funded by: Google Faculty Research Awards Grant pre-2014 from (2013 to 2014)
- Improving Genetic Programming for Classification based on a Multiobjective Approach. Funded by: VPAC Expertise Grant pre-2014 from (2004 to 2005)
- An Integrated Intelligent Bio-machines Network. Project now known as: The Australian Research Network for Smart Medical Devices.. Funded by: ARC Research Initiatives Seed Funding Grant pre-2014 from (2003 to 2005)
- Genetic Programming with Expensive Fitness Evaluation. Funded by: VPAC Expertise Grant pre-2014 from (2002 to 2002)
- Automated cephalometric analysis using novel computer image enhancement and feature recognition techniques.. Funded by: ARC SPIRT Grant 2001 from (2001 to 2004)