Marcin Budka

Professor Marcin Budka

  • Professor of Data Science
  • Poole House P256b, Talbot Campus, Fern Barrow, Poole, BH12 5BB
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Biography

Marcin Budka received his dual MSc/BSc degree in Finance and Banking from the Katowice University of Economics (Poland, 2003), BSc in Computer Science from the University of Silesia (Poland, 2005) and PhD in Computational Intelligence from Bournemouth University (UK, 2010). Between 2003 and 2007 he was working as an engineer, project manager and team leader in a smart-metering start-up company, before pursuing an academic career. In the years 2011-2012 he was appointed as a Visiting Research Fellow at the Wroclaw University of Technology, Poland. He currently acts as Head of Research in the Department of Computing and Informatics.

Research

My research interests lie in a broadly understood area of machine learning and data science, with a particular focus on practical applications. Throughout my career, I was involved in a number of research projects with industry, with a particular focus on tangible impact and societally useful innovation.

Journal Articles

Chapters

  • Balaguer-Ballester, E., Tabas-Diaz, A. and Budka, M., 2014. Empirical identification of non-stationary dynamics in time series of recordings. Springer Verlag, 142-151.
  • Musial, K., Budka, M. and Blysz, W., 2013. Understanding the Other Side - The Inside Story of the INFER Project. 1-9.
  • Budka, M., 2013. Clustering as an example of optimizing arbitrarily chosen objective functions. In: Nguyen, N., Trawinski, B., Katarzyniak, R. and Geun-Sik, J., eds. Advanced Methods for Computational Collective Intelligence. Springer Berlin / Heidelberg, 177-186.
  • Musial, K., Budka, M. and Blysz, W., 2012. Understanding the Other Side - the Inside Story of the INFER Project. In: Howlett, R.J., Howlett, R.J. and Jain, L.C., eds. Innovation through Knowledge Transfer 2012. Springer Berlin Heidelberg, (in press).
  • Schierz, A.C. and Budka, M., 2011. High-Performance Music Information Retrieval System for Song Genre Classification. In: Kryszkiewicz, M., Rybinski, H., Skowron, A. and Ras, Z.W., eds. Proceedings of the 19th International Symposium on Methodologies for Intelligent Systems (ISMIS'11). Springer-Verlag.

Conferences

  • Wahid-Ul-Ashraf, A., Budka, M. and Musial-Gabrys, K., 2017. Newton’s Gravitational Law for Link Prediction in Social Networks. In: Complex Networks 2017 29 November-1 December 2017 Lyon, France.
  • Budka, D., Budka, M., Bennett, M.R. and Bakirov, R., 2017. CAPTURE AND ANALYSIS OF 3D FOOTWEAR EVIDENCE: NEW HORIZONS AND OPPORTUNITIES. 172.
  • Budka, D., Bennett, M.R., Budka, M. and Bakirov, R., 2017. COMPARING FOOTWEAR EVIDENCE AND THE POWER OF THE 3RD DIMENSION. 162-163.
  • 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, M.M., Budka, M. and Gabrys, B., 2016. Towards Automatic Composition of Multicomponent Predictive Systems. 27-39.
  • Bennett, M., Morse, S. and Budka, M., 2015. Tracks and sediments: evolutionary stasis in foot function?
  • 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.
  • Balaguer-Ballester, E., Tabas, A. and Budka, M., 2014. Attracting Dynamics, non-stationarity and trial-to-trial variability in frontal ensemble recordings. In: Bernstein Computational Neuroscience Conference 2014 2-5 September 2014 Tubingen.
  • Balaguer-Ballester, E., Tabas-Diaz, A. and Budka, M., 2014. Empirical identification of non-stationary dynamics in time series of recordings. 142-151.
  • Krol, D., Budka, M., Musial, K. and IEEE, 2014. Simulating the information diffusion process in complex networks using push and pull strategies. 1-8.
  • Juszczyszyn, K., Gonczarek, A., Tomczak, J.M., Musial, K. and Budka, M., 2012. A probabilistic approach to structural change prediction in evolving social networks. 996-1001.
  • Budka, M., Musial, K. and Juszczyszyn, K., 2012. Predicting the evolution of social networks: Optimal time window size for increased accuracy. 21-30.
  • Juszczyszyn, K., Budka, M. and Musial, K., 2011. The Dynamic Structural Patterns of Social Networks Based on Triad Transitions. 581-586.
  • Juszczyszyn, K., Musial, K. and Budka, M., 2011. On analysis of complex network dynamics – changes in local topology. 61-70.
  • Juszczyszyn, K., Musial, K. and Budka, M., 2011. Link prediction based on Subgraph evolution in dynamic social networks. 27-34.
  • Juszczyszyn, K., Budka, M. and Musial, K., 2011. The dynamic structural patterns of social networks based on triad transitions. 581-586.
  • Schierz, A.C. and Budka, M., 2011. High--Performance music information retrieval system for song genre classification. In: Kryszkiewicz, M., Rybinski, H., Skowron, A. and Ras, Z.W., eds. Proc. of the 19th International Symposium on Methodologies for Intelligent Systems (ISMIS'11) June 2011 Warsaw, Poland. Lecture Notes in Computer Science, 2011, Volume 6804: Springer-Verlag, 725-733.
  • Budka, M. and Gabrys, B., 2010. Correntropy–based density–preserving data sampling as an alternative to standard cross–validation. In: World Congress on Computational Intelligence (WCCI 2010) 18-23 July 2010 Barcelona, Spain. IEEE, 1-8.
  • Budka, M. and Gabrys, B., 2009. Electrostatic Field Classifier for Deficient Data. Heidelberg: Springer, 311-318.

Reports

  • Budka, M., Eastwood, M., Gabrys, B., Kadlec, P., Schwan, S., Tsakonas, A. and Žliobaitė, I., 2011. From sensor readings to predictions: on the process of building soft sensors.
  • Budka, M., 2010. Coolant temperature forecasting for transformers data.

Theses

Others

  • Juszczyszyn, K., Budka, M. and Musial, K., 2011. Complex Network Model - a New Perspective. The International School and Conference on Network Science (NetSci2011).
  • Schierz, A.C., Budka, M. and Apeh, E., 2011. Winners' notes. Using Multi-Resolution Clustering for Music Genre Identification. TunedIT.

Grants

  • KTP - We Are Base Limited (Innovate UK, 26 Oct 2015). In Progress

Qualifications

  • MSc/BSc (dual) in E-banking: threats and safeguards (University of Economics in Katowice, Poland, 2003)
  • BSc (Hons) in Ant Colony System for Cluster Analysis (University of Silesia, Poland, 2005)
  • PhD in Computational Intelligence (Bournemouth University, UK, 2010)
The data on this page was last updated at 04:05 on December 18, 2017.