Dr Lyudmila Mihaylova

Professor of Signal Processing and Control

Photo: Dr MihalovaAddress:
Dr Lyudmila Mihaylova MEng, SM IEEE
Professor of Signal Processing and Control
Department of Automatic Control and Systems Engineering
University of Sheffield
S1 3JD
Tel: (+44) (0)114 222 5675
Email: L.S.Mihaylova@sheffield.ac.uk, mila.mihaylova@ieee.org


Prof. Lyudmila Mihaylova and her team are working to develop novel methods for autonomous intelligent systems: for sensing, tracking and decision making, machine learning and their engineering applications. Prof. Mihaylova undertook pioneering work on traffic flow estimation with particle filtering for intelligent transportation systems which was followed later with developments for large scale systems, including large scale transportation and video processing systems. She has experience with a range of image modalities, including optical, thermal, LIDAR, SAR and hyperspectral image processing. Previously she had academic positions with Lancaster University (2006-2013), University of Bristol (2004-2006), and research visiting positions with the University of Ghent, Belgium, the Katholic University of Leuven, Belgium and the Bulgarian Academy of Sciences, Bulgaria. Her interests are in the area of nonlinear filtering, sequential Monte Carlo Methods, statistical signal processing and sensor data fusion. Her work involves the development of novel techniques, e.g. for high dimensional problems (including vehicular traffic flow estimation and image processing) and localisation and positioning in sensor networks. Dr. Mihaylova is an Associate Editor of the IEEE Transactions on Aerospace and Electronic Systems, an Associate Editor of Elsevier Signal Processing Journal and the Editor-in-Chief of the Open Transportation Journal. Dr. Mihaylova is a senior member of the IEEE, Signal Processing Society, the President of the International Society of Information Fusion (ISIF) and an ISIF board member.

Dr Mihaylova has also been serving the scientific community as a member of the Programme/ Organising Committee of international conferences and symposia, including the International Conferences on Information Fusion, the American Control Conferences, EUSIPCO, conferences on Intelligent Transportation Systems and the German workshops on Multiple Sensor Data Fusion. She has given a number of invited talks, e.g. the keynote speech for the 5th IET International Conference on Wireless, Mobile and Multimedia Networks (2013), Beijing, China, and tutorials including for the EU Marie Curie ITN (2010, Sweden, 2012, Germany) and COST-NEARCTIS workshop (2010, Switzerland). Her research is funded by sponsors such as EPSRC, EU, MOD and industry.

Research Interests

Broad research in the areas of signal processing, Bayesian methods, Monte Carlo methods, nonlinear estimation, target tracking, sensor data fusion, control, autonomous and complex systems (e.g. image and video processing, transportation systems, large scale systems) – both at theoretical and applied level. Assisted living and eHealth systems is another application area of my research.

My Research Group

We share knowledge, we grow. We actively work as a team.

Postdoctoral Researchers

  • Matthew Hawes, Efficient Methods for Dealing with Big Data, funded by the EU SETA project
  • Allan de Freitas, Sequential Monte Carlo Methods for Tracking Groups an Extended Objects in Complex Environments, funded by the EU TRAX project and Grantham project
  • Le Yang, Localisation in Wireless Sensor Networks, funded by the Chinese Science Fund
  • Olga Isupova, Machine Learning Methods for Behaviour Analysis in Video, funded by the EU TRAX project

PhD students

  • Danil Kuzin, Interoperability and Fusion of Large Data for Surveillance Systems, writing dissertation
  • Aroland Kiring, Wireless Sensor Networks for Localisation in Urban Environments, writing PhD dissertation
  • Chao Liu, Smart Cities and Smart Cars with Assisted Wireless Sensor Networks, writing PhD dissertation
  • Ruilong Chen, Deep Learning Models and Methods for Intelligent Transportation Systems, writing dissertationt
  • Maria Luisa Davila Garcia, Advanced Image and Video Processing Methods for In Vitro Purposes, 3rd year PhD student
  • James Douthwaite, Methods for Coordination and Control of Swarms of UAVs, 2nd year PhD student
  • Fodio Longman, A Hybrid Satellite & Wireless Sensor Network (WSN) System for Reliable Monitoring, Surveillance and Security Operations of Oil and Gas Pipelines and Facilities, 2nd year PhD student
  • Hayder Amer, Methods for Localisation for Intelligent Transportation Systems, 2nd year PhD student
  • Zhenglin Li, Image Processing Methods for Fire Detection, 2nd year PhD student
  • Kennedy Offor, Sensor Data Fusion for Improving Traffic Mobility in Smart Cities, 1st year PhD student
  • Waqas Aftab, Multi-Sensor Data Fusion and Tracking with Massive Data, 1st year PhD student
  • Ke Wang, Tracking and Collision Avoidance for UAVs, 1st year PhD student

Alumni from Sheffield

  • Naveed Salman, Postdoctoral researcher, May 2014 - June 2016
  • Atta ur-Rehman, Postdoctoral researcher, Dec. 2013 - Jan. 2016, now Assistant Professor at the at University of Engineering and Technology, Lahore, Pakistan
  • Nikolay Petrov, PhD student (2009-2013) and Postdoctoral researcher, August 2013 - August 2014

Other graduated PhD students

  • Nickolay Petrov, Anna Zvikhachevskaya, Mahsa Honary, Chris Nemeth, Ali Arshad, Dennis Rodionov

Current Grants

I am grateful to the sponsors of my research: EPSRC, MoD/DSTL, EU, industrial and other partners. A brief description of projects of mine is given below.

  1. SETA: An open, sustainable, ubiquitous data and service ecosystem for efficient, effective, safe, resilient mobility in metropolitan areas, Horizon 2020 project, 2006-2019, co-I, jointly with Fabio Ciravegnia, PI, (2016-2019).

    SETA is set to create a technology and methodology that will address the challenges above and change the way mobility is organised, monitored and planned in large metropolitan areas. The solution will be based on the management of high-volume, high-velocity, multi-dimensional, heterogeneous, cross-media, cross-sectoral data and information which is sensed, crowdsourced, acquired, linked, fused, and used to model mobility with a precision, granularity and dynamicity that is impossible with today’s technologies. Such models will be used to provide always-on, pervasive services to citizens and business, as well as decision makers to support safe, sustainable, effective, efficient and resilient mobility. The consortium involves partners from 5 countries, UK, Italy, Spain, Poland and The Netherlands. Funded by EU, the project partners are University of Sheffield (Lead), Delft University (NL), University of Cantabria (Spain), Sheffield Hallam University (UK), Knowledge now Limited (UK), The FLOOW Limited (UK), TSS-TRANSPORT SIMULATION SYSTEMS SL (Spain), Software Mind SA (Poland), AIZOON CONSULTING SRL (Italy), AYUNTAMIENTO DE SANTANDER (Spain), Citta di Torino (Italy), Birmingham City Council, Scyfer B.V. (NL).
  2. Mobility grant with China, funded by the Royal Academy of Engineering 1 April 2016 - 31 March 2018, £9,500.
  3. TRAX : TRAcking in compleX sensor systems, EU FP7 Marie Curie project, €609,981 (2013-2017)

    The TRAX research project is an International Training Network (ITN) sponsored by the EU under the Marie Curie actions in the Seventh Framework Program (FP7). TRAX concentrates on Tracking in Complex Sensor Systems, focussing on complexities due to large volumes of data, complex object dynamics and measurement models, as well as large scale systems. The project partners are a well-known and well-respected mixture of academia, research institutes, small and large business companies, including University of Sheffield and Rinicom from the United Kingdom, Linköping University and Ericsson from Sweden, Fraunhofer FKIE from Germany, and University of Twente, Xsens and Thales from The Netherlands.
  4. Remote Sensing for Hedgerow Assessment in Agricultural Areas, Grantham centre grant £9,567. There is an imminent necessity to help analyse data of many types in automated and semi-automated manners, especially multispectral, hyperspectral, thermal, ISAR and LiDAR data. This project aims to ensemble methods for imagery data to support analysis of hedgerows in agricultural areas by synthesising data from multiple sources.

Principal Investigator of Completed Projects

  • BTaRoT: Bayesian Tracking and Reasoning over Time , £446,037, EP/K021516/1, EPSRC funded (2013-2016)
    This EPSRC funded project provided new advances in methods for reasoning about many objects that evolve in a scene over time. Information about such objects arrives, typically in a real-time data feed, from sensors such as radar, sonar, LIDAR and video. The Bayesian methodology is adopted due to its power to solve a wealth of complex inference problems, to take into account prior information and to incorporate it in flexible manners in the solutions. The main focus is on scalable approaches able to deal both with groups composed of a small number of objects (up to 20) and large groups, consisting of hundreds Partners for the project: Prof. Simon Godsill, Dr Sumeetpal S. Singh from Cambridge University and supported by QinetiQ.  
  • Information Fusion: Framework Architectures for Dynamic Heterogeneous Information Fusion, Funded by Sellex Gallileo, £111,000 (2012-2014)
    This project focuses on extracting knowledge from large amounts of data and fusion methods related with tracking and behavior analysis. The main approach is based on combinatorial pattern matching and statistical data mining methods. The project is part of the Centres of Excellence funded by Selex Gallileo and comprises Aberdeen University, Cambridge University, Cranfield University, University of Sheffield, Lancaster University, and Robert Gordon University.
  • EU FP7 Marie Curie Initial Training Network project: MC Impulse (“Monte Carlo Based Innovative Management and Processing for an Unrivalled Leap in Sensor Exploitation”), Dec. 2009 - Dec. 2013 (€400,000).
  • Object Tracking over Sensor Networks, EP/E027253/1, £228,883, 2007-2010
  • Object Tracking Over Sensor Networks - Pathway to Impact, August 2010 - March 2011, EPSRC (£4,795)
  • Particle Methods for Estimation and Control, EP/G501513/1, EPSRC contribution, £63,000, 2009-2012
  • CAN/05/105, M. Honary, Methods for Indoor Positioning and Mobile Phone Applications, EPSRC contribution £62,319, 2007-2012
  • Sequential Monte Carlo for Estimation and Control, PhD studentship, Funded by EPSRC & MBDA, UK, Sept. 2011 – Aug. 2014 , £81,000
  • Use of Particles for Estimation and Control, MBDA, UK, Funding from the Anglo-French Innovation Technology Partnership (ITP), April 2008 - April 2010 (£195,000 )
  • Particle Methods for Estimation and Control, industrial PhD studentship (EPSRC + BAEs), Aug. 2008 - Dec. 2011 (£81,000)
  • Royal Academy of Engineering: Grant for distinguished visiting professors, Sep. 2008 - March 2009, £1,905
  • Ad hoc Wireless Sensor Networks for Decision Making and Tracking, April 2007 - March 2009, project sponsored by the Data Information Fusion - Defense Technology Centre, UK (£158,665)
  • Object Recognition Using Graphical Models, Competition of ideas, UK MoD sponsored grant, Feb. - July 2008, QinetiQ (£30,000)
  • Tracking Cluster Project - Phase II, Oct. 2006 - Sept. 2008, DIF-DTC funded project, (£80,000)

PhD Projects

For a current list of PhD projects related to my areas of research please see the PhD Research Projects web pages. The Figures below show results from the methods and technique developed by me and my team.

Object Tracking and Behaviour Analysis in Video Sequences

Object Tracking and Behaviour Analysis in Video Sequences

Tracking in Heterogeneous
Multisensor data

Image: Tracking in Heterogeneous Multisensor data

Localisation and Positioning in Wireless Sensor Networks

Localisation and Positioning in Wireless Sensor Networks Localisation and Positioning in Wireless Sensor Networks
                        - destination detail

Target Tracking in Sensor Networks and Sensor Data Fusion

Image: Target tracking in sensor networks

Sensor Data Fusion

Image: Sensor fusion

Extended Object Tracking in Sensor Networks

Contour Segmentation for Medical Diagnostics

Image: Contour Segmentation for Medical Diagnostics

        Estimated contours for cists and liver tumors

Image: Estimated contours for cists and liver tumors

Modelling, and Estimation Methods for Intelligent Transportation Systems

Photo: motorway traffic Image: flow vs density plot
Image: tarffic flow shockwave


  • AERO324 Aircraft Dynamics and Control
  • ACS410 Flight Dynamics and Control
  • ACS6123 Intelligent and Vision Systems

Recent Invited Talks

  • Invited speaker, the 4th International Conference on Control Engineering & Information Technology (CEIT-2016)
  • Invited speaker for the Advances and Innovations on Traffic Modeling and Control, Control Summer School of GIPSA-Lab, CNRS, 12-16 Sept 2016, Grenoble, France
  • Invited talk at the Allan Turing Scoping Workshop: "Recursive Bayesian Estimation with Big Data", 10-12 February 2016, British Library, London
  • Invited talks for the "Advances and Innovations on Traffic Modeling and Control", Control Summer School of GIPSA-Lab, CNRS, 12-16 Sept 2016, Grenoble, France
  • Invited talk: "Sequential Monte Carlo Methods for Tracking and Inference in Intelligent Transportation Systems", Institute of Pure and Applied Mathematics (IPAM) Workshop II: Traffic Estimation, University of California, UCLA, Los Angeles, October 12 - 16, 2015
  • Plenary talk: "Recent Advances in Bayesian Methods for Tracking Groups, Extended Objects and Challenges with Big Data", IEEE Sensor Data Fusion Workshop, 6-8 October, Bonn, Germany 2015.
  • Invited Talk: "Machine Learning for Autonomous Systems and Knowledge Extraction from Big Data", Queen Mary University of London, UK, 23 Oct 2014
  • Plenary talk: "Advances and Challenges to Localisation in Wireless Sensor Networks'', The IET 5th International Conference on Wireless, Mobile and Multimedia Networks, (ICWMMN2013), Beijing, China, Nov. 22-25, 2013.
  • Invited talk: "Modelling, Estimation and Control for Intelligent Transportation Systems'', Jiatong University, Beijing, China, 25 November 2013.

Professional Activities

  • Member, EPSRC Peer Review College, 2012 –
  • Elected as the president of the International Society of Information Fusion in March 2016, On the Board of Directors of ISIF, since 2011
  • Associate Editor for the IEEE Transactions on Aerospace and Electronic Systems, since 2011
  • Associate Editor of Elsevier Signal Processing Journal, since 2008
  • On the Editorial Board of Intelligent Decision Technologies. An International Journal, from 2011
  • Associate Editor for the IEEE Intelligent Transportation Systems Conference, Washington DC, USA, Oct. 5-7, 2011
  • Associate Editor for the American Control Conferences, since 2008 till present


  • A. Y. Carmi, L. Mihaylova, S. J. Godsill (Editors), Compressed Sensing and Sparse Filtering, Series Signals and Communication Technology, Springer, Berlin Heidelberg, ISBN 978-3-642- 38397-7, 2014.
  • P. Georgieva, L. Mihaylova, L. Jain (Editors), Advances in Intelligent Signal Processing and Data Mining: Principles and Applications (Studies in Computational Intelligence), Springer, Berlin Heidelberg, Vol. 410, Jan. 2013, ISSN 1860-949X, ISBN 978-3-642-28695-7.
          Advances in Intelligent Signal Processing and Data Mining book thumbnail    Compressed Sensing and Sparse Filtering book cover thumbnail

Selected Journal Papers

  1. O. Isupova, D. Kuzin, L. Mihaylova, Learning Methods for Dynamic Topic Modelling in Automated Behaviour Analysis, IEEE Transactions on Neural Networks and Learning Systems, 2017
  2. A. de Freitas, L. Mihaylova, A. Gning, M. Schikora, M. Ulmke, D. Angelova, W. Koch, A Box Particle Filter Method for Tracking Multiple Extended Objects, IEEE Transactions on Signal Processing, 2016, under review
  3. A. de Freitas, F. Septier, L. Mihaylova, Sequential Markov Chain Monte Carlo for Bayesian Filtering with Massive Data, IEEE Transactions on Signal Processing, 2017, under review
  4. S. Rohou, L. Jaulin, L. Mihaylova, F. Le Bars, S. M. Veres, Guaranteed Computation of Robots Trajectories, Robotics and Autonomous Systems, 2017.
  5. H. Zhu, Ka-Veng Yuen, L. Mihaylova, and H. Leung, Overview of Environment Perception for Intelligent Vehicles, IEEE Transactions on Intelligent Transportation Systems, 2017.
  6. M. Hawes, L. Mihaylova, W. Liu, Location and Optimisation Orientation for Spatially Stretched Tripole Arrays Based on Compressed Sensing, IEEE Transactions on Signal Processing, 2017.
  7. A. Kiring, N.Salman, C. Liu, I. Esnaola, L. Mihaylova, Tracking with Sparse and Correlated Measurements via a Shrinkage-based Particle Filter, IEEE Sensors Journal, 2017.
  8. M. Hawes, L. Mihaylova, F. Septier, S. Godsill, Bayesian Compressive Sensing Approaches for Direction of Arrival Estimation with Mutual Coupling Effects, IEEE Transactions on Antennas and Propagation, 2017.
  9. A. de Freitas, L. Mihaylova, A. Gning, D. Angelova and V. Kadirkamanathan, Autonomous Crowds Tracking with Box Particle Filtering and Convolution Particle Filtering, Automatica, Vol. 69, pp. 380-394, 2016. Code available on Mathworks Central http://www.mathworks.com/matlabcentral/fileexchange/55657-crowd-tracking-with-the-box-and-convolution-particle-filter/content/BPF/main.m
  10. P. Georgieva, N. Bouaynaya, F. Silva, L. Mihaylova, L. Jain, A Beamformer-Particle Filter Framework for Localization of Correlated EEG Sources, IEEE Journal on Biomedical and Health Informatics, Vol. 20, No. 3, pp. 880-892, May, 2016.
  11. A.-ur Rehman, S.M. Naqvi, L. Mihaylova, J. Chambers, Multi-target Tracking and Occlusion Handling with Learned Variational Bayesian Clusters and a Social Force Model, IEEE Transactions on Signal Processing, Vol. 64, No. 5, pp. 1320-1335, 2016.
  12. A. Carmi, L. Mihaylova, F. Septier, Subgradient-Based Markov Chain Monte Carlo Particle Methods for Discrete-time Nonlinear Filtering, Signal Processing Journal, Elsevier, Vol. 120, March, pp. 532-536, 2016.
  13. A. Ali, B. Adebisi, I. Ikpehai, L. Mihaylova, Location Prediction Optimisation in WSN Using Kriging Interpolation, IET Wireless Sensor Systems Journal, Vol. 6, No. 3, pp. 74 – 81, 2016,.
  14. H. Amer, N. Salman, M. Hawes, M. Chaqfeh, L. Mihaylova, and M. Mayfield, An Improved Simulated Annealing Technique for Enhanced Mobility in Smart Cities, Sensors, Special Issue on Smart City: Vision and Reality, MDPI Publisher, Vol. 16, Article no 1013, pp. 1-23 2016.
  15. M. W. Khan, N. Salman, A.H. Kemp, L. Mihaylova, Localization of Sensor Nodes with Hybrid Measurements in Wireless Sensor Networks, Sensors. Special Issue on Scalable Localization in Wireless Sensor Networks, MDPI Publisher, 2016, in press
  16. M. Hawes, W. Liu, L. Mihaylova, Compressive Sensing Based Design of Sparse Tripole Arrays, Sensors Journal, MDPI Publisher, Vol. 15, No. 12, pp. 31056-31068, 2015.
  17. C. Nemeth, P. Fearnhead, L. Mihaylova, Particle Approximations of the Score and Observed Information Matrix for Parameter Estimation in State Space Models with Linear Computational Costs, Journal of Computational and Graphical Statistics, 2015
  18. H. Bhaskar, K. Dwivedi, D. P. Dogra, M. Al-Mualla, L. Mihaylova, Autonomous Detection and Tracking Under Illumination Changes, Occlusions and Moving Camera, Signal Processing, Vol. 117, pp. 343-354, 2015
  19. M. Schikora, A. Gning, L. Mihaylova, D. Cremers, W. Koch, Box-Particle Hypothesis Density Filter for Multi-Target Tracking, IEEE Transactions on Aerospace and Electronic Systems, Vol. 50, No. 3, July, pp. 1660 - 1672, 2014.
  20. H. H. Chhadé, F. Abdallah, I. Mougharbel, A. Gning, S. Julier, L. Mihaylova, Localization of an Unknown Number of Land Mines Using a Network of Vapour Detectors, Sensors, 14(11), 21000-21022, 2014.
  21. L. Mihaylova, A. Carmi, F. Septier, A. Gning, S. K. Pang, S. Godsill, Overview of Sequential Bayesian Monte Carlo Methods for Group and Extended Object Tracking, Digital Signal Processing, February, Vol. 25, pp. 1-16, 2014.
  22. C. Nemeth, P. Fearnhead, L. Mihaylova, Sequential Monte Carlo Methods for State and Parameter Estimation in Abruptly Changing Environments, IEEE Transactions on Signal Processing, Vol. 62, No. 5, pp. 1245-1255, 2014.
  23. M. Cannaud, L. Mihaylova, E. F. Nour-Eddin, J. Sau, Probability Hypothesis Density Filtering For Real-Time Traffic State Estimation and Prediction, Applied Mathematics Journal on Networks and Heterogeneous Media. Special Issue on: Mathematics of Traffic Modelling, Estimation and Control, American Institute of Mathematical Sciences, Vol. 3, No. 3, 2013, pp. 825 - 842.
  24. A. Gning, B. Ristic, L. Mihaylova, F. Abdallah, An Introduction to the Box Particle Filtering, IEEE Signal Processing Magazine, Vol. 30, No. 4, pp. 166 - 171, July, 2013.
  25. H. Bhaskar, L. Mihaylova, S. Maskell, Automatic Human Body Parts Detection Based on Cluster Background Subtraction and Foreground Learning, Neurocomputing. Special Issue on Behaviours in Video, Vol. 100, No. 1, pp. 58-72, 2013.
  26. A. Gning, B. Ristic, L. Mihaylova, Bernoulli/ Box-Particle Filters for Detection and Tracking in the Presence of Triple Measurement Uncertainty, IEEE Transactions on Signal Processing, Vol. 60, No. 5, pp. 2138 - 2151, 2012.
  27. L. Mihaylova, A. Hegyi, A. Gning and R. Boel, Parallelized Particle and Gaussian Sum Particle Filters for Large Scale Traffic Systems, IEEE Transactions on Intelligent Transportation Systems, Special Issue on Emergent Cooperative Technologies in Intelligent Transportation Systems, Vol. 13, No. 1, pp. 36–48, 2012.
  28. G. Markarian, L. Mihaylova, D. Tsitserov, A. Zvikhachevskaya, Video Distribution Techniques over IEEE 802.16 Networks for e-Health/m-Health Applications, IEEE Trans. on Information Technology in Biomedicine. Special issue on 4G Health the Long Term Evolution of m-Health, Vol. 16, No. 1, pp. 24-30, 2012.
  29. A. Gning, L. Mihaylova, R. Boel, Interval Macroscopic Models for Traffic Networks, IEEE Transactions on Intelligent Transportation Systems, Vol. 12, No. 2, pp. 523-536, 2011.
  30. A. Gning, L. Mihaylova, S. Maskell, S. K. Pang, S. Godsill, Group Object Structure and State Estimation with Evolving Networks and Monte Carlo Methods, IEEE Transactions on Signal Processing, Vol. 59, No. 4, April, 1383 – 1396, 2011.
  31. L. Mihaylova, D. Angelova, D. Bull, and N. Canagarajah, Localisation of Mobile Nodes in Wireless Sensor Networks with Time Correlated Measurement Noises, IEEE Transactions on Mobile Computing, Vol. 10, No. 1, pp. 44-53, 2011.
  32. D. Angelova, L. Mihaylova, Contour Segmentation in 2D Ultrasound Medical Images with Particle Filtering, Machine Vision & Applications Journal, Springer, Vol. 22, No. 3, pp. 551 - 561, 2011.
  33. H. Bhaskar, L. Mihaylova, A. Achim, Video Foreground Detection Based on Symmetric Alpha-Stable Mixture Models, IEEE Transactions on Systems and Circuits for Video Technology, Vol. 20, No. 8, pp. 1133 – 1138, Aug. 2010.
  34. H. Bhaskar, L. Mihaylova, Combined Data Association and Evolving Population Particle Filter for Tracking of Multiple Articulated Targets, EURASIP Journal on Image and Video Processing, Volume 2011, Article ID 642532, 2011.
  35. A. Loza, L. Mihaylova, N. Canagarajah, D. Bull, Structural Similarity-Based Object Tracking in Multi-Sensor Video Sequences, Machine Vision & Applications Journal, Springer, Vol. 20, No. 2, pp. 71–83, 2009.
  36. D. Angelova, L. Mihaylova, Extended Object Tracking Using Monte Carlo Methods, IEEE Transactions on Signal Processing, vol. 56, issue no. 2, pp. 825-832, Feb. 2008.
  37. L. Mihaylova, D. Angelova, S. Honary, D. Bull, N. Canagarajah, B. Ristic, Mobility Tracking in Cellular Networks Using Particle Filtering, IEEE Transactions on Wireless Communications, Vol. 6, No. 10, pp. 3589- 3599, October, 2007.
  38. L. Mihaylova, R. Boel and A. Hegyi, Freeway Traffic Estimation within Recursive Bayesian Framework, Automatica, Vol. 43, No. 2, pp. 290–300, 2007.
  39. P. Brasnett, L. Mihaylova, N. Canagarajah and D. Bull, Sequential Monte Carlo Tracking by Fusing Multiple Cues in Video Sequences, Image and Vision Computing, Vol. 25, No. 8, pp. 1217-1227, 2007.
  40. R. Boel and L. Mihaylova, A Compositional Stochastic Model for Real-Time Freeway Traffic Simulation, Transportation Research. Part B – Methodological. An International Journal, Elsevier Science, Vol. 40, No. 4, pp. 319-334, May 2006.
  41. D. Angelova, L. Mihaylova, Joint Target Tracking and Classification with Particle Filtering and Mixture Kalman Filtering Using Kinematic Radar Information, Digital Signal Processing, Elsevier Science, Vol. 16, No. 2, pp. 180–204, 2006.
  42. L. Mihaylova, J. De Schutter, H. Bruyninckx, A Multisine Approach for Trajectory Optimization Based on Information Gain, Robotics and Autonomous Systems, Elsevier Science, the Netherlands, Vol. 43, No. 4, pp. 231-243, June 2003.

Selected Recent Conference Papers

  1. F. Longman, L. Mihaylova, D. Coca, Fusion of Synthetic Aperture Radar Images for Oil SpilL Monitoring, Proc. of the IEEE CEIT Conference, Tunisia, 12-16 Dec. 2016.
  2. A. de Freitas, F. Septier, L. Mihaylova, S. Godsill, How Can Subsampling Reduce Complexity in Sequential MCMC Methods and Deal with Big Data in Target Tracking?, Proceedings of the International Conference on Information Fusion, USA, 2015
  3. M. Hawes, L. Mihaylova, F. Septier, S. Godsill, A Bayesian Compressed Sensing Kalman Filter for Direction of Arrival Estimation and Tracking, Proceedings of the International conference on Information Fusion, USA, 2015
  4. M. W. Khan, A. H. Kemp, N. Salman, L.S. Mihaylova, Tracking of Mobile Nodes in Unknown Path-Loss Models, Proceedings of the International Conference on Information Fusion, USA, 2015
  5. O. Isupova, L. Mihaylova, D. Kuzin, G. Markarian, F. Septier, An Expectation Maximization Algorithm for Behaviour Analysis in Video, Proceedings of the International Conference on Information Fusion, USA, 2015
  6. R. Lamberti, F. Septier, N. Salman, L. Mihaylova, Sequential Markov Chain Monte Carlo for Multi-target Tracking with Correlated RSS Measurements, Proc. of the 10th IEEE International Conference on On Intelligent Sensors, Sensor Networks and Information Processing, 7-9 April, 2015, Singapore, Best ISSNIP paper award
  7. N. Salman, N. Alsindi, L. Mihaylova, A. H. Kemp, Super Resolution WiFi Indoor Localization and Tracking, Proceedings of the IEEE Sensor Data Fusion Workshop, Oct 8-10, 2014, Bonn, Germany
  8. N. Salman, L. Mihaylova, A. H. Kemp, Localization of Multiple Nodes Based on Correlated, Measurements and Shrinkage Estimation, Proceedings of the IEEE Sensor Data Fusion Workshop, Oct 8-10, 2014, Bonn, Germany
  9. T. Alkhaldi, L. Mihaylova, H. Gellersen, QRS Complex Detection Using Centered Cumulative Sums of Squares, Proceedings of the 17th IEEE SPA’2013 Conference Signal Processing Algorithms, Architectures, Arrangements, and Applications, Sept. 26 -28, 2013, Poznan, Poland, pp. 168-171, Best student paper award from the IEEE SPA'2013 Conference
  10. R. Davies, L. Mihaylova, N. Pavlidis, I. Eckley, The Effect of Recovery Algorithms on Compressive Sensing Background Subtraction, Proceedings from the IEEE Sensor Data Fusion Workshop, Bonn, Germany, 3-6 Oct. 2013, Best paper award from the IEEE SDF'2013 Workshop
  11. A. Gning, S. Julier, L. Mihaylova, Non-linear State Estimation using Imprecise Samples, Proceedings of the International Conf. on Information Fusion, Istanbul, Turkey, 9-12 July, 2013.

Organising International Events / on Technical Program Committees/ Session Chair



Reviewer for:

  • Automatica
  • IEEE Transactions on Signal Processing
  • EEE Transactions on Wireless Communications
  • EEE Transactions on Image Processing
  • IEEE Transactions on Aerospace and Electronic Systems
  • IEEE Transactions on Automatic Control
  • IEEE Transactions on Circuits and Systems
  • IEEE Communication Letters
  • International Journal of Adaptive Control and Signal Processing
  • Signal Processing
  • Digital Signal Processing
  • Robotics and Autonomous Systems
  • Computer Vision and Image Understanding
  • Information Fusion. An International Journal on Multi-Sensor, Multi-Source Information Fusion
  • EURASIP Journal on Advances in Signal Processing
  • EURASIP Journal on Wireless Communications and Networking
  • EUSIPCO conferences
  • American Control Conferences
  • International Conferences on Information Fusion
  • IEEE International Conferences on Acoustics, Speech and Signal Processing (ICASSP)
  • IEEE International Conferences on Robotics and Automation (ICRA)

and many other journals and conferences.