Dr. Anthony Quinn

• A. Quinn, M. Kárny and T.V. Guy, Fully probabilistic design of hierarchical Bayesian models, Information Sciences, 369, 2016, p532 - 547Journal Article, 2016, DOI , URL
• S. Azizi and A. Quinn, Approximate Bayesian filtering using stabilized forgetting, 23rd European Signal Processing Conference, EUSIPCO 2015, Nice, France, 2015, pp2711 - 2715Conference Paper, 2015, DOI , URL
• S. Azizi and A. Quinn, A data-driven forgetting factor for stabilized forgetting in approximate Bayesian filtering, 26th Irish Signals and Systems Conference, ISSC 2015, Carlow, Ireland, 2015, IEEE, 2015, pp6Conference Paper, 2015, DOI , URL
• L. Jirsa, F. Varga and A. Quinn, Identification of Thyroid Gland Activity in Radioiodine Therapy, Informatics in Medicine Unlocked, 7, 2017, p23 - 33Journal Article, 2017, TARA - Full Text
• A. Quinn, M. Kárny and T.V. Guy, Optimal Design of Priors Constrained by External Predictors, International Jour. Approximate Reasoning, 84, 2017, p150 - 158Journal Article, 2017, DOI
• A. Quinn, J. Murphy and A.M. de Paor, 'The Sinusoidal Instantaneous Frequency Extractor for Speech Therapy', Irish Patents Office , 1988Patent, 1988, URL
• A. Quinn and A. Jackson, E3: the Engineering, Energy and Environment Institute of Trinity College Dublin, Trinity College Dublin, June, 2012, 123 pp.Report, 2012
• Lymphoscintigraphy of Upper Limbs: a Bayesian Framework in, Valencia VII, Oxford University Press, 2003, pp543 - 552, [P. Gebouský, M. Karný and A. Quinn ]Book Chapter, 2003
• Bayesian Identification of Non-Linear Parameters in Signal and System Models in, Attractors, Signals and Synergetics, Berlin, Pabst Science Publishers, 2001, pp284 - 294, [A. Quinn]Book Chapter, 2001
• The Objective Admission of Ockham's Razor by Marginalization in Bayesian Model-Based Inference in, Mathematics in Signal Processing III, Oxford University Press, 1994, pp339 - 357, [A. Quinn]Book Chapter, 1994
• V. Smídl and A. Quinn , Mixture-Based Extension of the AR Model and its Recursive Bayesian Identification, IEEE Trans. Sig. Process, 53, (9), 2005, p3530 - 3542Journal Article, 2005
• V. Smídl, A. Quinn, M. Karný and T. V. Guy, Robust Estimation of Autoregressive Processes using a Mixture Based Filter Bank, Sys. And Cont. Letters, 54, (4), 2005, p315 - 323Journal Article, 2005
• A. Quinn, P. Ettler, L. Jirsa, I. Nagy and P. Nedoma, Probabilistic Advisory Systems for Data-Intensive Applications, Int. J. Adapt. Control Signal Process, 17, 2003, p133 - 148Journal Article, 2003
• V. Smídl and A. Quinn , The Variational EM Algorithm for On-line Identification of Extended AR Models, Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Philadelphia, U.S.A, 2005Conference Paper, 2005
• V. Smídl and A. Quinn, Bayesian Estimation of Non-stationary AR Model Parameters via an Unknown Forgetting Factor, Proceedings of the IEEE Workshop on Digital Signal Processing, New Mexico, U.S.A., 2004Conference Paper, 2004
• V. Smídl, A. Quinn and Y. Maniouloux, Fully Probabilistic Model for Functional Analysis of Medical Image Data, Proceedings of the Irish Signals and Systems Conference, Belfast, 2004Conference Paper, 2004
• E. Ranguelova, A. Quinn, 3-D Methods for Difference Estimation in Volumetric Data, Proceedings of the IEEE Workshop on Image and Signal Processing and its Applications, Rome, 2003Conference Paper, 2003
• V. Smídl and A. Quinn, Fast Variational PCA for Functional Analysis of Dynamic Image Sequences, Proceedings of the IEEE Workshop on Image and Signal Processing and its Applications, Rome, 2003Conference Paper, 2003
• V. Smídl and A. Quinn , The Extended AR Model and its Bayesian Identification, Proceedings of the Irish Signals and Systems Conference, Limerick, 2003Conference Paper, 2003
• E. Ranguelova, A. Quinn , Difference Estimation and Compensation via Entropy Minimization in 3-D Image Segmentation, Proceedings of the 2nd International Workshop on Spectral Methods and Multirate Signal Processing, Toulouse, France, 2002Conference Paper, 2002
• E. Ranguelova, A. Quinn, Difference Field Estimation for Enhanced 3-D Texture Segmentation, Proceedings of the British Machine Vision Conference, Cardiff, Wales, 2002Conference Paper, 2002
• V. Smídl and A. Quinn , Variational Methods in Dimensionality Reduction, Workshop on Advances in Information and Control Theory, Slovenia, 2002Conference Paper, 2002
• L. Tesar and A. Quinn , Detection and Removal of Outliers from Multidimensional AR Processes, Proceedings of the Irish Signals and Systems Conference, Maynooth, 2001Conference Paper, 2001
• E. Ranguelova, A. Quinn, Registration Preprocessing for Enhanced 3-D Segmentation, Proceedings of the Irish Signals and Systems Conference, Maynooth, 2001Conference Paper, 2001
• V. Smídl, M. Kárný and A. Quinn , On Prior Information in Principal Component Analysis, Proceedings of the Irish Signals and Systems Conference, Maynooth, 2001Conference Paper, 2001
• L. Jirsa and A. Quinn, Mixture Analysis of Nuclear Medicine Data: Medical Decision Support, Proceedings of the Irish Signals and Systems Conference, Maynooth, 2001Conference Paper, 2001
• L. Tesar and A. Quinn , Method for Artefact Detection and Suppression Using Alpha-Stable Distributions, Proceedings of the International Conference on Artificial Neural Networks and Genetic Algorithms (ICANNGA), Prague, Czech Republic, 2001Conference Paper, 2001
• L. Tesar and A. Quinn , A Survey of Techniques for Pre-Processing in High-Dimensional Data Clustering, PhD Workshop on Cybernetics and Informatics, Marianska, Czech Republic, 2000Conference Paper, 2000
• E. Ranguelova, A. Quinn , Disparity-Compensated Segmentation of 3-D Images, PhD Workshop on Cybernetics and Informatics, Marianska, Czech Republic, 2000Conference Paper, 2000
• E. Ranguelova, A. Quinn, Analysis and Synthesis of Three-Dimensional Gaussian Markov Random Fields, Proceedings of the IEEE International Conference on Image Processing (ICIP), Kobe, Japan, 1999Conference Paper, 1999
• E. Clark and A. Quinn , A Data-Driven Bayesian Sampling Scheme for Unsupervised Image Segmentation, 6, Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Phoenix, U.S.A., 2307, 1999Conference Paper, 1999
• J. Reichel and A. Quinn, A Fast and Fully Unsupervised Scheme for Model-Based Image Segmentation, Proceedings of the SPIE Conference on Bayesian Inference for Inverse Problems, San Diego, U.S.A., 1998, pp82 - 90Conference Paper, 1998
• A. Quinn, Regularization Strategies for Signal Identification, The European Association for Signal Processing (EURASIP), Proceedings of the First European Conference on Signal Analysis and Prediction, Prague, Czech Republic, 1997, pp145 - 148Conference Paper, 1997
• A. Quinn, Novel Parameter Priors for Bayesian Signal Identification, Speech and Signal Processing (ICASSP), Proceedings of the IEEE International Conference on Acoustics, Munich, Germany, 5, (3909), 3912, 1997Conference Paper, 1997
• O. Schwartz and A. Quinn , Fast and Accurate Texture-Based Image Segmentation, Proceedings of the IEEE International Conference on Image Processing, Lausanne, Switzerland, 3, 1996, pp121 - 124Conference Paper, 1996
• O. Schwartz and A. Quinn , New Approaches to Markov Random Field-Based Image Segmentation, Proceedings of the Irish DSP and Control Conference, Dublin, Ireland, 1996, pp323 - 330Conference Paper, 1996
• A. Quinn, A Mathematical Framework for Signal Identification, Proceedings of the Eighth URSI Symposium on Radio Science, paper No. 7, Royal Irish Academy, Dublin, Ireland, 1996Conference Paper, 1996
• A. Quinn, The Modelling of Signals and Systems amid Uncertainty: a Bayesian Perspective, Proceedings of the EURACO Workshop on Recent Results in Robust and Adaptive Control, Florence, Italy, 1995, pp514 - 531Conference Paper, 1995
• M. C. Musgrave and A. Quinn , Texture Analysis of Terrain Images using a Markov Random Field Model, Proceedings of the Fifth IEE International Conference on Image Processing and its Applications (IPA), Edinburgh, Scotland, 1995, pp781 - 785Conference Paper, 1995
• A. Quinn, A General Complexity Measure for Signal Identification using Bayesian Inference, Proceedings of the IEEE Workshop on Nonlinear Signal and Image Processing, Halkidiki, Greece, 2, 1995, pp843 - 846Conference Paper, 1995
• A. Quinn, Prediction of the Asymptotic and Threshold Behaviour of Bayesian Signal Parameter Estimators, Signal Processing VII: Proceedings of the Seventh European Signal Processing Conference (EUSIPCO), The European Association for Signal Processing (EURASIP). Edinburgh, Scotland, 3, 1994, pp1839 - 1842Conference Paper, 1994
• A. Quinn, A New Objective Measure of Signal Complexity using Bayesian Inference, Proceedings of the Seventh IEEE Signal Processing Workshop on Statistical Signal and Array Processing (SSAP), Quebec City, Canada, 1994Conference Paper, 1994
• A. Quinn, New Lower Bounds to the Variance of Signal Parameter Estimators using Bayesian Inference, Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Adelaide, Australia, 4, 1994, pp493 - 496Conference Paper, 1994
• A. Quinn, A consistent, numerically efficient Bayesian framework for combining the Selection, Detection and Estimation tasks in Model-Based Signal Processing, Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Minneapolis, U.S.A., 4, 1993, pp65 - 68Conference Paper, 1993
• A. Quinn, Censored Marginal a Posteriori Bayesian Inference for Signal Models, Proceedings of the IEEE Winter Workshop on Nonlinear Digital Signal Processing, Section 6.3, Tampere, Finland, 1993, pp5.1 - 5.6Conference Paper, 1993
• A. Quinn, A Unified Approach to Model-Based Signal Processing using Bayesian Marginal Inference, Proceedings of the Sixth IEEE Signal processing Workshop on Statistical Signal and Array Processing (SSAP), Victoria, B.C., Canada, 1992Conference Paper, 1992
• A. Quinn, Threshold-Free Bayesian Estimation using Censored Marginal Inference, Signal Processing VI: Proceedings of the Sixth European Signal Processing Conference (EUSIPCO), The European Association for Signal Processing (EURASIP), Brussels, Belgium, 2, 1992, pp677 - 680Conference Paper, 1992
• A. Quinn, The Performance of Bayesian Estimators in the Superresolution of Signal Parameters, Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), San Francisco, U.S.A., 5, 1992, pp297 - 300Conference Paper, 1992
• A. Quinn and M. D. Macleod, A Study of Joint and Marginal Bayesian Estimators for the Parameters of Periodic Signals in Gaussian White Noise, Proceedings of the IEEE International Conference on Communication Systems (ICCS), Section 27, Singapore, 1990, pp1.1 - 1.5Conference Paper, 1990
• A. M. dePaor, A. Quinn and A. J. Murphy, The Sinusoidal Instantaneous Frequency Extractor: A New Instrument for use in Speech Therapy, Innovation et Technologie en Biologie et Médecine, 13, (6), 1992, p635 - 640Journal Article, 1992
• C. Foley and A. Quinn, Fully Probabilistic Design for Knowledge Transfer in a Pair of Kalman Filters, IEEE Signal Processing Letters, 25, (4), 2018, p487 - 490Journal Article, 2018, DOI , URL
• S. Azizi and A. Quinn, Hierarchical fully probabilistic design for deliberator-based merging in multiple participant systems, IEEE Transactions on Systems, Man, and Cybernetics: Systems, 48, (4), 2018, p565 - 573Journal Article, 2018, DOI
• M. Papez and A. Quinn, Dynamic Bayesian Knowledge Transfer between a Pair of Kalman Filters , IEEE Int. Workshop on Machine Learning for Signal Processing, Aalborg, Denmark, September 2018, IEEE, 2018, pp6Conference Paper, 2018, DOI
• Approximate Bayesian Prediction Using a State Space Model with Uniform Noise in, Informatics in Control, Automation and Robotics: Lecture Notes in Electrical Engineering, Springer Lecture Notes in Electrical Engineering, Springer, 2020, pp552 - 568, [L. Jirsa, L. Pavelková and A. Quinn]Book Chapter, 2020
• M. Papez and A. Quinn, Bayesian transfer learning between Student-t filters, Elsevier Signal Processing Journal, 175, (107624), 2020, p1-36Journal Article, 2020, DOI
• L. Pavelková, L. Jirsa and A. Quinn, Bayesian filtering for states uniformly distributed on a parallelotopic support, 19th IEEE International Symposium on Signal Processing and Information Technology (ISSPIT), Ajman, UAE, December, 2019, edited by IEEE , 2019, pp1-6Conference Paper, 2019
• M. Papez and A. Quinn, Bayesian transfer learning between Gaussian process regression tasks, 19th IEEE International Symposium on Signal Processing and Information Technology (ISSPIT), Ajman, UAE, December 2019, edited by IEEE , 2019, pp1-6Conference Paper, 2019
• M. Papez and A. Quinn, Robust Bayesian transfer learning between Kalman filters, 29th IEEE Int. Workshop on Machine Learning for Signal Processing (MLSP), Pittsburg, US, October 2019, edited by IEEE , 2019, pp1-6Conference Paper, 2019
• L. Jirsa, L. Pavelková and A. Quinn, Knowledge transfer in a pair of uniformly modelled Bayesian filters, Proc. 16th International Conference on Informatics in Control, Automation and Robotics (ICINCO), Prague, Czechia, July 2019, 2019, pp1-8Conference Paper, 2019
• Bayesian Transfer Learning between Uniformly Modelled Bayesian Filters in, Informatics in Control, Automation and Robotics: Lecture Notes in Electrical Engineering, Springer Lecture Notes in Electrical Engineering, Springer, 2021, pp21 , [L. Pavelková, L. Jirsa and A. Quinn]Book Chapter, 2021
• L. Pavelková, L. Jirsa and A. Quinn, Fully probabilistic design for knowledge fusion between Bayesian filters under uniform disturbances, Elsevier Knowledge-Based Systems, 238, (107879), 2022, p16Journal Article, 2022
• M. Papez and A. Quinn, Transferring model structure in Bayesian transfer learning for Gaussian process regression, Elsevier Knowledge-Based Systems, 2022, p13Journal Article, 2022
• A. Barber and A. Quinn, Robust Bayesian transfer learning between autoregressive inference tasks, 32nd IEEE Irish Signals and Systems Conference (ISSC), Athlone, Ireland, June 2021, IEEE, 2021, pp6Conference Paper, 2021
• S. Murray and A. Quinn, Bayesian selective transfer learning for patient-specific inference in thyroid radiotherapy, 32nd IEEE Irish Signals and Systems Conference (ISSC), Athlone, Ireland, June 2021, IEEE, 2021, pp6Conference Paper, 2021
• M. Papez and A. Quinn, Hierarchical Bayesian transfer learning between a pair of Kalman filter, 32nd IEEE Irish Signals and Systems Conference (ISSC), Athlone, Ireland, June 2021, IEEE, 2021, pp6Conference Paper, 2021
• Tran, V.H. and Quinn, A., The transformed variational Bayes approximation, (5947288), 2011, pp4236-4239Conference Paper, 2011, DOI , URL
• Cogan, B. and de Paor, A.M. and Quinn, A., PI control of first-order lag plus time-delay plants: Root locus design for optimal stability, Transactions of the Institute of Measurement & Control, 31, (5), 2009, p365-379Journal Article, 2009, DOI , URL
• Å mídl, V. and Quinn, A., The restricted variational bayes approximation in Bayesian filtering, (4378860), 2006, pp224-227Conference Paper, 2006, DOI , URL
• Å mídl, V. and Quinn, A., The variational em algorithm for on-line identification of extended AR models, IV, (1415959), 2005, ppIV117-IV120Conference Paper, 2005, DOI , URL
• Clark, E. and Quinn, A., Data-driven Bayesian sampling scheme for unsupervised image segmentation, 6, 1999, pp3497-3500Conference Paper, 1999, URL
• Reichel, J. and Quinn, A., Fast and fully unsupervised scheme for model-based image segmentation, 3459, 1998, pp82-90Conference Paper, 1998, DOI , URL
• Quinn, A., A new objective measure of signal complexity using Bayesian inference, (572444), 1994, pp79-82Conference Paper, 1994, DOI , URL
• Quinn, A.P., A unified approach to model-based signal processing using Bayesian marginal inference, (246857), 1992, pp98-101Conference Paper, 1992, DOI , URL
• Quinn, A.P., The performance of Bayesian estimators in the superresolution of signal parameters, 5, (226624), 1992, pp297-300Conference Paper, 1992, DOI , URL
• Kharman, A.M. and Ferraro, P. and Quinn, A. and Shorten, R., Robust Decentralised Proof-of-Position Algorithms for Smart City Applications, 2023, pp112-119Conference Paper, 2023, DOI , URL
• Gallagher, S. and Quinn, A., A New Non-Separable Kernel for Spatio-Temporal Gaussian Process Regression, 2023Conference Paper, 2023, DOI , URL
• Langbridge, A. and Quinn, A. and Shorten, R., Optimal Transport for Fairness: Archival Data Repair using Small Research Data Sets, 2024, pp237-245Conference Paper, 2024, DOI , URL
• V. Smídl and A. Quinn , The Variational Bayes Method in Signal Processing , Berlin, Heidelberg, Springer-Verlag, 2006, 247 pagesppBook, 2006
• Senan Doyle, Anthony Quinn and Petr Gebousky, Bayesian Inference of Optimal Lymphoscintigraphic Sampling Times, IFMBE Proceedings EMBEC'05, 3rd European Medical and Biological Engineering Conference, Prague, Czech Republic, November 20-25, edited by Peter Kneppo and Jiri Hozman , 11, (1), International Federation for Medical and Biological Engineering, 2005, pp3255 - 3259Conference Paper, 2005, URL
• A. Das and A. Quinn, A Variational Bayes Approach to Decoding in a Phase-Uncertain Digital Receiver, IET Irish Signals and Systems Conference, Trinity College Dublin, 23-24 June 2011, 2011Conference Paper, 2011, URL , TARA - Full Text
• Identification of Thyroid Gland Activity in Radiotherapy in, Bayesian Statistics VIII, Oxford University Press, 2007, pp613 - 618, [L. Jirsa, A. Quinn, F, Varga]Book Chapter, 2007
• A. Quinn, Recursive Inference for Inverse Problems using Variational Bayes Methodology, Proc. 5th Int. ICST Conf. on Performance Evaluation Methodologies and Tools (VALUETOOLS), Cachan, France, 2011Conference Paper, 2011
• A. Quinn, J.P. Barbot and P. Larzabal, The Bayesian Inference of Phase, Proc. IEEE Int. Conf. Acoust., Speech, Sig. Process. (ICASSP), Prague, 2011, pp4Conference Paper, 2011
• V.H. Tran and A. Quinn, The Transformed Variational Bayes Approximation, Proc. IEEE Int. Conf. Acoust., Speech, Sig. Process. (ICASSP), Prague, 2011Conference Paper, 2011
• V.H. Tran and A. Quinn, Variational Bayes Variants of the Viterbi Algorithm, Proc. 22nd IET Irish Signals and Systems Conference (ISSC), Dublin, 2011Conference Paper, 2011
• V.H. Tran and A. Quinn, Online Bayesian Inference for a Mixture of Known Components, Proc. Irish Signals and Systems Conf. (ISSC), Cork, 2010Conference Paper, 2010
• B. Cogan, A. de Paor and A. Quinn, PI Control of First-Order Lag plus Time-Delay Plants: Root Locus Design for Optimal Stability, Trans. Institute of Measurement and Control, 31, (5), 2009, p365 - 379Journal Article, 2009
• V. Smídl and A. Quinn, Variational Bayesian Filtering, IEEE Trans. Sig. Processing, 56, (10), 2008, p5020 - 5030Journal Article, 2008
• A. Quinn and M. Kárný, Learning for Nonstationary Dirichlet Processes, Jour. Adaptive Control and Signal Processing, 21, (10), 2007, p1 - 29Journal Article, 2007
• V. Smídl and A. Quinn, On Bayesian Principal Component Analysis, Jour. of Computational Stats. and Data Analysis, 51, (9), 2007, p4101 - 4123Journal Article, 2007
• V. Smídl and A. Quinn, Accelerated Particle Filtering using the Variational Bayes Approximation, Proc. IEEE Int. Conf. on Acoust., Speech and Sig. Process. (ICASSP), Hawaii, 2007Conference Paper, 2007
• Regularized Signal Identification using Bayesian Techniques in, Attractors, Signals and Synergetics, Boston, Birkhäuser , 1998, pp151 - 162, [A. Quinn]Book Chapter, 1998
• V. SmÍdl and A. Quinn, The Variational Bayes Approximation in Bayesian Filtering, Proc. IEEE Int. Conf. on Acoust., Speech and Sig. Process. (ICASSP), Toulouse, 3, 2006, pp137 - 140Conference Paper, 2006
• V. SmÍdl and A. Quinn, The Restricted Variational Bayes Approximation in Bayesian Filtering, Proc. IEEE Statist. Sig. Process. Workshop, Cambridge, (83), 2006, pp1 - 4Conference Paper, 2006

• A. Quinn, Randomized Design of Bayesian Conditionals, 2018 Workshop on Bayesian Nonparametrics for Signal and Image Processing (BNPSI), Bordeaux, France, 2018, Université de BordeauxInvited Talk
• M. Papez and A. Quinn, Hierarchical Bayesian transfer learning between a pair of Kalman filters, IEEE Signal Processing Letters, 2019, p1 - 4Journal Article
• S. Nugent and A. Quinn, Transferring improved local kernel design in multi-source Bayesian transfer learning, with an application in air pollution monitoring in India, 2392, Czech Academy of Sciences, Institute of Information Theory and Automation, January, 2022, 23Report
• Á. Hoffmann and A. Quinn, Ockham's Razor from a fully probabilistic design perspective, 2391, Czech Academy of Sciences, Institute of Information Theory and Automation, January , 2022, 9Report

I am an expert in Bayesian methods (i.e. knowledge representation & inference via probability) for signal processing & machine learning, for 34 years. I work at the interface between electrical engineering (EE), probability & statistics, being among the few internationally with formal grounding jointly in EE, and advanced statistical methodology. My 1-year Fulbright research scholar position ('16-'17) at the renowned Michael Jordan group in the Stats Department, UC Berkeley, reflects this, as do invited lectures (UC Berkeley, UC Santa Cruz and UW Madison), at Université de Bordeaux (2018), Linköping (2008), SUNY NY (1997), etc., as well as international appointments in Prague and Paris (Section 3.2). I seek (a) fuller understanding of the assumptions underlying classical & empirical statistical signal processing solutions (what I call the `auditing property' of Bayesian methods), and (b) new designs arising out of Bayesian analysis (the `prescriptive property'). Major contexts include: (i) Bayesian transfer learning: major recent papers address machine learning and decision making problems, dynamically processing broad knowledge specifications. Designs are randomized, conferring model robustness and replacing selection with exploration strategies. A major context is probabilistic knowledge processing in distributed sensor networks. (ii) Design of recursive computational algorithms. These can be hosted by mobile computing hardware, providing attractive cost-accuracy trade-offs, a central focus of my (widely cited) 2006 Springer monograph, the first in the topic. (iii) Objective assessment of parametric model complexity, leading to optimal parsimony-prediction trade-offs. (iv) Nonparametric Bayesian methods for flexible model-robust inference, obviating finite degrees-of-freedom constraints. Published applications: Bayesian transfer learning allows external data from a patient population to improve the design of radio-iodine therapies for individual thyroid cancer patients. I have also published applications in reconstruction of noisy functional scintigraphic images of the human kidney; a variational Bayes (VB) method for smoothing impulsively corrupted speech; a high-performing VB variant of the state-of-the-art Viterbi algorithm for iterative symbol detection in a mobile digital receiver; and, recently, improved atmospheric pollutant (PM2.5) prediction in India via Bayesian knowledge transfer between nonparametrically modelled sensors. Key research achievements: . My international reputation is recognized by award of a 1-year Fulbright senior research fellowship, hosted by Michael Jordan at UC Berkeley. As part of my Fulbright sabbatical, I delivered a series of invited lectures across America in 2017. . I co-wrote the first book-length treatment (Springer, 2006) of the variational Bayes (VB) approximation in signal processing, which continues to be highly cited. . I was pioneering in migrating Bayesian methods into the arena of signal processing and system analysis, writing the first PhD thesis on the subject (1992) in the Cambridge Signal Processing Laboratory. In recent years, these same Bayesian methods are being widely uptaken within the deep learning toolset. . Important results on performance bounds of Bayesian estimators, contrasting these with classical techniques that have dominated the signal processing state-of-the-art. . New computational flows, implementable on digital computers, for recursive and adaptive signal processing, free from many of the restrictive (linear, Gaussian) assumptions of the implemented state-of-the-art. . I have a long-term (4.5-year) funded appointment as a research scientist in the Czech Academy of Sciences (Section 3.2), employing three postdocs, plus 4 interns from TCD, working on topics ranging from radio-iodine metabolism in thyroid cancer treatment, to pollution prediction in India.

• Title

  Robust Signal and Information Processing Using Bayesian Nonparametrics
  Summary
  Funding Agency

  Fulbright Commission
  Date From

  26th September 2016
  Date To

  25th September 2017
• Title

  Optimal Distributional Design for External Stochastic Knowledge Processing
  Summary
  Funding Agency

  Czech Science Foundation (GACR)
  Date From

  1st January 2018
  Date To

  31st December 2020
• Title

  Medical Imaging
  Summary
  Funding Agency

  Provost's Fund
  Date From

  1999
  Date To

  1999
• Title

  ProDaCTool (Phase II)
  Summary
  Funding Agency

  ESPRIT (E.U. Fifth Framework)
  Date From

  2000
  Date To

  2002
• Title

  Visit S.U.N.Y.
  Summary
  Funding Agency

  Forbairt
  Date From

  1997
• Title

  Bayesian Nonparametrics in Signal Processing
  Summary
  Funding Agency

  SFI
  Date From

  1st October 2010
  Date To

  30th September 2014
• Title

  ICT 2013- Vilnius
  Summary
  Funding Agency

  Enterprise Ireland
  Date From

  31st October 2013
  Date To

  30th April 2014
• Title

  Collaboration with Univ. Paris V
  Summary
  Funding Agency

  Forbairt/CNRS
  Date From

  1995
  Date To

  1998
• Title

  Knowledge Processing in Distributed Software Systems
  Summary
  Funding Agency

  SFI
  Date From

  1st September 2011
  Date To

  31st March 2017
• Title

  Bayesian Design for Iterative Turbo-Receivers
  Summary
  Funding Agency

  École Normale Supérieure de Cachan, France
  Date From

  1st September 2011
  Date To

  30th September 2011
• Title

  Variational Bayes Methods for Iterative Telcommunications Receiver Design
  Summary
  Funding Agency

  SFI
  Date From

  1st September 2008
  Date To

  31st August 2012
• Title

  Variational Bayesian Signal Processing
  Summary
  Funding Agency

  École Normale Supérieure de Cachan, France
  Date From

  1st September 2009
  Date To

  30th September 2009
• Title

  Computer-Aided Diagnosis
  Summary
  Funding Agency

  Forbairt
  Date From

  1998
  Date To

  1998
• Title

  Rationality and Deliberation
  Summary
  Funding Agency

  Czech National Funding Agency (GACR)
  Date From

  1st January 2016
  Date To

  31st December 2018
• Title

  ProDaCTool (Phase I)
  Summary
  Funding Agency

  ESPRIT (E.U.)
  Date From

  1998
  Date To

  1998
• Title

  Research Incentive Grant
  Summary
  Funding Agency

  T.C.D.
  Date From

  2001
  Date To

  date
• Title

  Hierarchical Fully Probabilistic Design for Decision Making and Machine Learning
  Summary
  Funding Agency

  Czech Academy of Sciences
  Date From

  1st July 2014
  Date To

  31st December 2016
• Title

  High-Performance Computing Scholarship
  Summary
  Funding Agency

  T.C.D./Queen's
  Date From

  1998
  Date To

  1998

• Fellow of Trinity College Dublin (FTCD) 2008
• Fulbright (Senior) Research Scholar, and Visiting Scholar at the Statistics Department, University of California, Berkeley 2016-17
• First Prize for the best publication in the Theory of Information and Automation, Czech Academy of Sciences, for the monograph: 'The Variational Bayes Method in Signal Processing', Smidl, V. and Quinn, A., Springer 2006 2007

• Member of the IEEE 2013
• Member of the International Society for Bayesian Analysis (ISBA) 2022
• Irish Fulbright Alumni Association 2020

• Appointment as the University Observer for the Leaving Certificate Technology examinations (Department of Education) 2017-2022
• Active reviewer for many top-flight international journals and publishers 1993-date
• Invited review work for international research funding Agencies 2009-2016
• Extensive international technical/scientific programme committee membership and service 1998-date
• Chair of the Irish Signals and Systems Conference, Trinity College Dublin, 2011 2011
• External PhD Examinerships, in the French language, at the École Normale Supérieure (Supélec), Paris 2010, 2012