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Manuel Martin Salvador (MEng'09 -- MSc'11) graduated with distinction as a Computer Engineer from the University of Granada (Spain) in 2009, where he also received the MSc in Soft Computing and Intelligent Systems in 2011. Manuel has worked in a range of R&D projects for the industry in several sectors: renewable energy, process industry and public transport. Currently he is a PhD candidate at Bournemouth University and works as R&D engineer at We Are Base. His main research areas include automatic data preprocessing, predictive modelling and adaptive systems.
- Salvador, M.M., Budka, M. and Gabrys, B., 2016. Effects of Change Propagation Resulting from Adaptive Preprocessing in Multicomponent Predictive Systems. Procedia Computer Science, 96, 713-722.
- Salvador, Budka, M. and Quay, T., 2017. Automatic Transport Network Matching Using Deep Learning. In: European Transport Conference 2017 4-6 October 2017 Barcelona, Spain.
- Salvador, Budka, M. and Gabrys, B., 2017. Modelling Multi-Component Predictive Systems as Petri Nets. In: Kacprzyk, J. and Owsinski, J., eds. 15th Annual Industrial Simulation Conference 31 May-2 June 2017 Warsaw, Poland. Eurosis-ETI, 17-23.
- Salvador, M, Budka, M., Quay, T. and Carver-Smith, A., 2016. Improving transport timetables usability for mobile devices: a case study. In: 11th International Conference on the Practice and Theory of Automated Timetabling 23-26 August 2016 Udine, Italy.
- Salvador, Budka, M. and Gabrys, B., 2016. Adapting Multicomponent Predictive Systems using Hybrid Adaptation Strategies with Auto-WEKA in Process Industry. In: AutoML 2016 @ ICML 20-24 June 2016 New York (USA).
- Martin Salvador, M., Budka, M. and Gabrys, B., 2016. Towards automatic composition of multicomponent predictive systems. 27-39.
- Schroeder, J.W., Martin-Salvador, M., Bakirov, R. and Straus, U., 2015. Tactile satellite navigation system: Using haptic technology to enhance the sense of orientation and direction. 3364-3371.
- Budka, M., Eastwood, M., Gabrys, B., Kadlec, P., Martin Salvador, M., Schwan, S., Tsakonas, A. and Žliobaitė, I., 2014. From Sensor Readings to Predictions: On the Process of Developing Practical Soft Sensors. In: The Thirteenth International Symposium on Intelligent Data Analysis (IDA 2014) 30 October-1 November 2014 Leuven, Belgium. Springer, 49-60.
- Salvador, M.M., Gabrys, B. and Žliobaitė, I., 2014. Online Detection of Shutdown Periods in Chemical Plants: A Case Study. 580 - 588.
- Stahl, F., Medhat Gaber, M. and Martin Salvador, M., 2012. eRules: A Modular Adaptive Classification Rule Learning Algorithm for Data Streams. In: AI-2012, The Thirty-second SGAI International Conference on Innovative Techniques and Applications of Artificial Intelligence 11-13 December 2013 Cambridge, England. 65-78.
- Salvador, 2017. Automatic and adaptive preprocessing for the development of predictive models. PhD Thesis. Bournemouth University, Faculty of Science and Technology.
- Salvador, M.M., 2014. Identifying Shutdown Periods in a Chemical Production Plant. In: 7th Annual DEC PGR Poster Conference.
- Salvador, M.M., 2014. Automating Data Pre-processing for Online and Dynamic Processes in the Chemical Industry. In: 6th Annual Postgraduate Research Conference.
- Salvador, M.M., 2012. Automatic and Adaptive Preprocessing for the Development of Predictive Models. In: 4th Annual Postgraduate Research Conference.
- Salvador, M.M., 2012. Automatic and Adaptive Preprocessing for the Development of Predictive Models. In: 5th Annual DEC PGR Poster Conference.
Profile of Teaching UG
- Advanced Data Management
- MSc in Computer Engineering (2009)
- MSc in Soft Computing and Intelligent Systems (2011)