Dr Philip Weber

Research Fellow in Computer Sciencephilip weber

Phone number: 0121 204 4991

Email: p.weber1@aston.ac.uk

Room number: MB267



Dr Philip Weber is a post-doctoral computer science researcher specialising in data analysis and visualisation, machine learning, and applied artificial intelligence.

He currently provides data analytics, machine learning and artifiical intelligence consultancy and training to small and medium entrerprises (SMEs) through the ERDF-funded Think Beyond Data programme.

Philip obtained his PhD in Computer Science from the University of Birmingham, for his thesis “A framework for the analysis and comparison of process mining algorithms”, which proposed a probabilistic, machine learning framework within which to consider business process mining.

He has extensive experience in Automatic Speech Recognition, with particular interest in new models for robust speech recognition, inspired by linguistically and physically plausible models of speech production.

His background is systems analysis, design, integration, and administration in industry, focussing on designing and developing cross-platform solutions to protect data, reduce risk, and improve information available to management and other stakeholders.


  • PhD in Computer Science, University of Birmingham, 2014
  • MSc in Advanced Computer Science, University of Birmingham, 2009
  • BSc in Computer Science, Loughborough University, 1994




  • 2018 – date: Business Research Associate, Aston University Think Beyond Data project.
  • 2016 – 2018: Research Fellow, Automated Conflict Resolution in Clinical Pathways, University of Birmingham.
  • 2013 – 2016: Rsearch Fellow, Speech Recognition by Synthesis, University of Birmingham.
  • 2011 – 2012: International Research Fellowship (3 months), Etisalat BT Innovation Centre (Abu Dhabi).



  • 2002 – 2008: Senior UNIX and Storage systems Administrator, Egg Bank (Citi Group).
  • 1999 – 2002: Principal Infrastructure Analyst, Analyst Programmer, Dixons Stores Group.
  • 1994 – 1997: Systems Engineer, International Computers Limited, Fujitsu.


My main research interests are

  • machine learning, data analytics and AI, and their industrial, commercial and healthcare applications;
  • business process mining, modelling and analysis, and broad application beyond business;
  • Automatic speech recognition and synthesis, modelling speech, and their relation to human speech production and perception.
I have co-supervised students in the field of Automatic Speech Recognition, but am not at present available to supervise new PhD Students.
  • Member of the IEEE.
  • Former Chartered Information Technology Professional (CITP) and Member of the British Computer Society (MBCS).


  • P. Weber: A Framework for the Analysis and Comparison of Process Mining Algorithms. PhD thesis, University of Birmingham, UK, 2014. ( eTheses ).


  • I. Litchfield, C. Hoye, D. Shukla, R. Backman, A. Turner, M. Lee, P. Weber: Can process mining automatically describe care pathways of patients with long-term conditions in UK primary care? A study protocol. BMJ Open, 8:e019947, 2018.
  • P. Weber, J. B. F. Filho, B. Bordbar, M. Lee, I. Litchfield and R. Backman: Automated Conflict Detection Between Medical Care Pathways. Journal of Software: Evolution and Process (Special Issue on Software Engineering for Connected Health), e1898 (18 pages), 2017.
  • P. Weber, B. Bordbar and P. Tiňo: A Framework for the Analysis of Process Mining Algorithms. IEEE Transactions on Systems, Man and Cybernetics: Systems, 43(2), pp. 303-317, 2013.

Refereed Conference Publications:

  • L. Bai, P. Weber, P. Jančovič and M. Russell: Exploring how Phone Classification Neural Networks Learn Phonetic Information by Visualising and Interpreting Bottleneck Features. Interspeech 2018, pp1472-1476, Hyderabad, India, 2018.
  • P. Weber, R. Backman, I. Litchfield and M. Lee: A Process Mining and Text Analysis Approach to Analyse the Extent of Polypharmacy in Medical Prescribing. In Proc. the 6th IEEE International Conference on Healthcare Informatics (ICHI 2018), pp1-11, New York, NY, USA, 2018.
  • M. Najafian, S. Safavi, P. Weber and M. J. Russell: Identification of British English regional accents using fusion of i-vector and multi-accent phonotactic systems. Odyssey 2016, pp132-139, Bilbao, Spain, 2016.
  • P. Weber, C. Champion, S. Houghton, P. Jančovič and M. Russell: Consonant Recognition with Continuous-State Hidden Markov Models and Perceptually-Motivated Features. Interspeech 2015, pp1893-1897, Dresden, Germany, 2015.
  • P. Weber, B. Bordbar and P. Tiňo: A Principled Approach to Mining From Noisy Logs Using Heuristics Miner. In Proc. Computational Intelligence and Data Mining (CIDM), 2013 IEEE Symposium on, Singapore, 2013.