School of Computing Science

Inference, Dynamics and Interaction Group

The Inference, Dynamics and Interaction group brings together three fundamental research areas: modern inference techniques, dynamic systems and control theory and interaction design. These are applied in wide range of situations:

- Health, Wellness & Entertainment
- Systems Biology
- Mobile Interaction
- Cognitive Neuroscience/neuroimaging
- Social Interaction

The group's strength lies in the unusual combination of theoretical backgrounds from machine learning to HCI, and the focus on building innovative working systems which achieve performance previously thought impossible, using the latest algorithms, sensors and devices. The group's skills in combining software engineering and mathematical inference allows us to attack complex systems problems with large high-dimensional data spaces and so in real-time.

Visit the dedicated Inference, Dynamics and Interaction Group Website to find out more.

  • European Network of Excellence called Social Signal Processing Network (SSPNet), coordinated by Alessandro Vinciarelli, together with with Maja Pantic (Imperial College). The network aims at establishing a European research community on modeling analysis and synthesis of social signals.
  • TOBI: Tools for Brain-Computer Interaction, EC-funded project. Roderick Murray-Smith (Glasgow PI), John Williamson, project coordinator:Prof. José del R. Millán, 2008-2012.
  • Multimodal, Negotiated Interaction in Mobile Scenarios, EPSRC funded project (£638k), Roderick Murray-Smith (PI), with Matt Jones (Swansea), Stephen Brewster, 2007-2010.
  • EC-COST action IC0601 on Sonic Interaction Design.
  • Social Interaction: A Cognitive-Neurosciences Approach, ESRC funded project (£3.7 million) , Simon Garrod (PI), 2008-2012.
  • PASCAL network member, EC-funded network in Pattern Analysis, Statistical Modelling and Computational Learning.

Academic Staff:  Prof. Roderick Murray-Smith, Dr. Maurizio Filippone, Dr. Simon Rogers, Dr. Alessandro Vinciarelli, Dr. John Williamson

Researchers: Mohammad Bin Md Noor, Dr. Andrew Crossan (TOBI), Rónán Daly, Andrew Ramsay (TOBI), Dari Trendafilov (Nokia/GU), Melissa Quek (TOBI), Dominik Gotojuch, Zac Mtema (joint supervision with Katie Hampson, Epidemiology), Lauren Norrie, Shimin Feng, Daryl Weir, Rebecca Mancy (jointly supervised with Pat Prosser), Edwin Thuma (jointly supervised with Iadh Ounis, IR), Mikhail Churakov (main supervisor is Rowland Kao, Vet School), Hugues Salamin, Joe Wandy

  • Machine Learning
  • Statistical Pattern Recognition
  • Human Computer Interaction
  • Mobile HCI
  • Brain Computer Interaction

'Can we work this out?: an evaluation of remote collaborative interaction in a mobile shared environment
Trendafilov, D., Vazquez-Alvarez, Y. , Lemmela, S., and Murray-Smith, R. (2011) 'Can we work this out?: an evaluation of remote collaborative interaction in a mobile shared environment. In: 13th International Conference on Human Computer Interaction with Mobile Devices and Services, MobileHCI '11, 30 Aug - 2 Sep 2011, Stockholm, Sweden.

Simulating the effects of laser dazzle on human vision
Williamson, C.A., Strachan, E., and Siebert, J.P. (2013) Simulating the effects of laser dazzle on human vision. In: International Laser Safety Conference 2013, 18-21 Mar 2013, Orlando, FL, USA.

Information-theoretic characterization of uncertainty in manual control
Trendafilovv, D., and Murray-Smith, R. (2013) Information-theoretic characterization of uncertainty in manual control. In: IEEE International Conference on Systems, Man and Cybertnetics, 13-16 2013, Manchester, UK. (In Press)

A P300-based image browser with automatic stimulation optimization
Williamson, J. , Ramsay, A. , Quek, M. , Tangermann, M., Schreuder, M., Viduarre, C., and Murray-Smith, R. (2010) A P300-based image browser with automatic stimulation optimization. In: TOBI Workshop II: Translational Issues in BCI Development: User Needs, Ethics, and Technology Transfer, 2-3 Dec 2010, Rome, Italy.

Optimized stimulation events for a visual ERP BCI
Tangermann, M., Schreuder, M., Dähne , J., Regler, S., Ramsay, A. , Quek, M. , Williamson, J. , and Murray-Smith, R. (2011) Optimized stimulation events for a visual ERP BCI. International Journal of Bioelectromagnetism , 13 (3). pp. 119-120. ISSN 1456-7857

Data driven neuroergonomic optimization of BCI stimuli
Tangermann, M., Höhne , J., Schreuder, M., Sagebaum, M., Blankertz, B., Ramsay, A. , and Murray-Smith, R. (2011) Data driven neuroergonomic optimization of BCI stimuli. In: 5th International Brain-Computer Interface Conference 2011, 22-24 Sep 2011, Graz, Austria.

End user performance in a novel social BCI application: the photobrowser
Schreuder, M., Riccio, A., Ramsay, A. , Dähne , J., Quek, M. , Crossan, A. , Mattia, D., Murray-Smith, R. , and Tangermann, M. (2012) End user performance in a novel social BCI application: the photobrowser. In: TOBI Workshop III: Bringing BCIs to End-Users: Facing the Challenge Evaluation, User Perspectives, User Needs, and Ethical Questions , 20-22 Mar 2012, Würzburg, Germany.

A BCI-controlled photobrowser for social integration: perspectives of friends and family
Quek, M. , Ramsay, A. , Crossan, A. , Riccio, A, Schreuder, M, Höhne , S, Mattia, D, Tangermann, M, and Murray-Smith, R. (2012) A BCI-controlled photobrowser for social integration: perspectives of friends and family. In: TOBI Workshop III: Bringing BCIs to End-Users: Facing the Challenge Evaluation, User Perspectives, User Needs, and Ethical Questions , 20-22 Mar 2012, Würzburg, Germany.

Inferring Music Selections for Casual Music Interaction
Boland, D., McLachlan, R. , and Murray-Smith, R. (2013) Inferring Music Selections for Casual Music Interaction. In: EuroHCIR, 1 Aug 2013, Dublin.

Finding My Beat: Personalised Rhythmic Filtering for Mobile Music Interaction
Boland, D., and Murray-Smith, R. (2013) Finding My Beat: Personalised Rhythmic Filtering for Mobile Music Interaction. In: MobileHCI 2013, 27-30 Aug 2013, Munich, Germany.

From speech to personality: mapping voice quality and intonation into personality differences
Mohammadi, G., Origlia, A., Filippone, M. , and Vinciarelli, A. (2012) From speech to personality: mapping voice quality and intonation into personality differences. In: 20th ACM International Conference on Multimedia, 29 Oct - 2 Nov 2012, Nara, Japan.

Predicting the conflict level in television political debates: an approach based on crowdsourcing, nonverbal communication and Gaussian processes
Kim, S., Filippone, M. , Valente, F., and Vinciarelli, A. (2012) Predicting the conflict level in television political debates: an approach based on crowdsourcing, nonverbal communication and Gaussian processes. In: 20th ACM International Conference on Multimedia, 29 Oct - 2 Nov 2012, Nara, Japan.

Send me bubbles: multimodal performance and social acceptability
Williamson, J.R. (2011) Send me bubbles: multimodal performance and social acceptability. In: Proceedings of the 2011 annual conference extended abstracts on Human factors in computing systems - CHI EA '11, Vancouver, BC, Canada, 7-12 May 2011. ACM New York, New York, NY, USA, pp. 899-904. ISBN 9781450302685

Designing performative interactions in public spaces
Williamson, J.R. , and Hansen, L.K. (2012) Designing performative interactions in public spaces. In: Proceedings of the Designing Interactive Systems Conference - DIS '12, Newcastle, UK, 11-15 June 2012. ACM New York, New York, NY, USA, pp. 791-792. ISBN 9781450312103

Exploiting query logs and field-based models to address term mismatch in an HIV/AIDS FAQ retrieval system
Thuma, E., Rogers, S. , and Ounis, I. (2013) Exploiting query logs and field-based models to address term mismatch in an HIV/AIDS FAQ retrieval system. In: Proceedings of 18th International Conference on Application of Natural Language to Information Systems (NLDB2013), 19-21 June 2013, University of Salford, MediaCityUK. University of Salford, Salford, UK. (In Press)

Bayesian approaches for mass spectrometry-based metabolomics
Rogers, S. , Scheltema, R.A., Barrett, M. , and Breitling, R. (2011) Bayesian approaches for mass spectrometry-based metabolomics. In: Stumpf, M.P.H., Balding, D.J. and Girolami, M. (eds.) Handbook of Statistical Systems Biology. John Wiley & Sons, Chichester, UK, pp. 467-476. ISBN 9780470710869

Statistical methods and models for bridging omics data levels
Rogers, S. (2011) Statistical methods and models for bridging omics data levels. In: Mayer, B. (ed.) Bioinformatics for Omics Data: Methods and Protocols. Series: Methods in molecular biology (719). Humana Press, New York, NY, USA, pp. 133-151. ISBN 9781617790263

ODE parameter inference using adaptive gradient matching with Gaussian processes
Dondelinger, F., Filippone, M. , Rogers, S. , and Husmeier, D. (2013) ODE parameter inference using adaptive gradient matching with Gaussian processes. In: Sixteenth International Conference on Artificial Intelligence and Statistics, 29 Apr - 1 May 2013, Scottsdale, AZ, USA. (In Press)

Evaluating bad query abandonment in an iterative SMS-Based FAQ retrieval system
Thuma, E., Rogers, S. , and Ounis, I. (2013) Evaluating bad query abandonment in an iterative SMS-Based FAQ retrieval system. In: OAIR 2013, 22-24 May 2013, Lisbon, Portugal. (In Press)

Investigating the disagreement between clinicians’ ratings of patients in ICUs
Rogers, S. , Sleeman, D. , and Kinsella, J. (2013) Investigating the disagreement between clinicians’ ratings of patients in ICUs. IEEE Journal of Biomedical and Health Informatics . ISSN 2168-2194 (doi:10.1109/JBHI.2013.2252182 ) (In Press)

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Past Events

IDI Seminar (29 November, 2012)

Speaker: Konstantinos Georgatzis

Visualisation of multivariate data sets is often done by mapping data onto a low-dimensional display with nonlinear dimensionality reduction (NLDR) methods. We have introduced a formalism where NLDR for visualisation is treated as an information retrieval task, and a novel NLDR method called the Neighbor Retrieval

Visualiser (NeRV) which outperforms previous methods. The remaining concern is that NeRV has quadratic computational complexity with respect to the number of data. We introduce an efficient learning algorithm for NeRV where relationships between data are approximated through mixture modeling, yielding efficient computation with near-linear computational complexity with respect to the number of data. The method is much faster to optimise as the number of data grows, and it maintains good visualisation performance.

Evaluating Bad Query Abandonment in an Iterative SMS-Based FAQ Retrieval System (14 February, 2013)

Speaker: Edwin Thuma

We investigate how many iterations users are willing to tolerate in an iterative Frequently Asked Question (FAQ) system that provides information on HIV/AIDS. This is part of work in progress that aims to develop an automated Frequently Asked Question system that can be used to provide answers on HIV/AIDS related queries to users in Botswana. Our system engages the user in the question answering process by following an iterative interaction approach in order to avoid giving inappropriate answers to the user. Our findings provide us with an indication of how long users are willing to engage with the system. We subsequently use this to develop a novel evaluation metric to use in future developments of the system. As an additional finding, we show that the previous search experience of the users has a significant effect on their future behaviour.

Pre-interaction Identification By Dynamic Grip Classification (28 February, 2013)

Speaker: Faizuddin Mohd Noor

We present a novel authentication method to identify users at they pick up a mobile device. We use a combination of back-of-device capacitive sensing and accelerometer measurements to perform classification, and obtain increased performance compared to previous accelerometer-only approaches. Our initial results suggest that users can be reliably identified during the pick-up movement before interaction commences.

Flexible models for high-dimensional probability distributions (04 April, 2013)

Speaker: Iain Murray

Statistical modelling often involves representing high-dimensional probability distributions. The textbook baseline methods, such as mixture models (non-parametric Bayesian or not), often don’t use data efficiently. Whereas the machine learning literature has proposed methods, such as Gaussian process density models and undirected neural network models, that are often too computationally expensive to use. Using a few case-studies, I will argue for increased use of flexible autoregressive models as a strong baseline for general use.

Interdependence and Predictability of Human Mobility and Social Interactions (23 May, 2013)

Speaker: Mirco Musolesi

The study of the interdependence of human movement and social ties of individuals is one of the most interesting research areas in computational social science. Previous studies have shown that human movement is predictable to a certain extent at different geographic scales. One of the open problems is how to improve the prediction exploiting additional available information. In particular, one of the key questions is how to characterise and exploit the correlation between movements of friends and acquaintances to increase the accuracy of the forecasting algorithms.

In this talk I will discuss the results of our analysis of the Nokia Mobile Data Challenge dataset showing that, by means of multivariate nonlinear predictors, it is possible to exploit mobility data of friends in order to improve user movement forecasting. This can be seen as a process of discovering correlation patterns in networks of linked social and geographic data. I will also show how mutual information can be used to quantify this correlation; I will demonstrate how to use this quantity to select individuals with correlated mobility patterns in order to improve movement prediction. Finally, I will show how the exploitation of data related to friends improves dramatically the prediction with respect to the case of information of people that do not have social ties with the user.