Dr Mauricio Álvarez
MEng, PhD
Department of Computer Science
Visiting lecturer
mauricio.alvarez@sheffield.ac.uk
Full contact details
Dr Mauricio Álvarez
Department of Computer Science
Department of Computer Science
- Profile
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Dr. Álvarez López received a degree in Electronics Engineering (B. Eng.) with Honours, from Universidad Nacional de Colombia in 2004, a master degree in Electrical Engineering (M. Eng.) from Universidad Tecnológica de Pereira, Colombia in 2006, and a Ph.D. degree in Computer Science from The University of Manchester, UK, in 2011.
After finishing his Ph.D., Dr. Álvarez López joined the Department of Electrical Engineering at Universidad Tecnológica de Pereira, Colombia, where he was appointed as an Associate Professor until Dec 2016.
From January, 2017 to April 2022, Dr. Álvarez López was appointed as Lecturer in Machine Learning at the Department of Computer Science.
- Research interests
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Dr. Álvarez López is interested in machine learning in general, its interplay with mathematics and statistics, and its applications. In particular, his research interests include probabilistic models, kernel methods and stochastic processes. He works on the development of new approaches and the application of Machine Learning in areas that include applied neuroscience, systems biology, and humanoid robotics.
He is a member of the Machine Learning group.
- Publications
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Journal articles
- Correlated chained Gaussian processes for datasets with multiple annotators. IEEE Transactions on Neural Networks and Learning Systems.
- Bayesian inversion of a diffusion model with application to biology. Journal of Mathematical Biology, 83(2).
- A Support Vector Machine Based Method for Parameter Estimation of an Electric Arc Furnace Model. Electric Power Systems Research.
- Physically-inspired Gaussian process models for post-transcriptional regulation in Drosophila. IEEE/ACM Transactions on Computational Biology and Bioinformatics, 18(2), 656-666. View this article in WRRO
- Learning Nonparametric Volterra Kernels with Gaussian Processes.. CoRR, abs/2106.05582.
- A machine learning approach to support deep brain stimulation programming. Revista Facultad de Ingeniería(95), 20-33. View this article in WRRO
- Recyclable Gaussian Processes.. CoRR, abs/2010.02554.
- Machine Learning for a Low-cost Air Pollution Network.. CoRR, abs/1911.12868.
- Variational Bridge Constructs for Grey Box Modelling with Gaussian Processes.. CoRR, abs/1906.09199.
- Adversarial Vulnerability Bounds for Gaussian Process Classification.. CoRR, abs/1909.08864. View this article in WRRO
- Gaussian Process Latent Force Models for Learning and Stochastic Control of Physical Systems. IEEE Transactions on Automatic Control, 64(7), 2953-2960. View this article in WRRO
- Tensor decomposition processes for interpolation of diffusion magnetic resonance imaging. Expert Systems with Applications. View this article in WRRO
- Bayesian Probabilistic Power Flow Analysis Using Jacobian Approximate Bayesian Computation. IEEE Transactions on Power Systems. View this article in WRRO
- Gaussian Process Regression for Binned Data.. CoRR, abs/1809.02010. View this article in WRRO
- Physically-inspired Gaussian processes for transcriptional regulation in Drosophila melanogaster.. CoRR, abs/1808.10026.
- Dynamic Facial Landmarking Selection for Emotion Recognition using Gaussian Processes. Journal on Multimodal User Interfaces, 11(4), 327-340. View this article in WRRO
- Short-term time series prediction using Hilbert space embeddings of autoregressive processes. Neurocomputing, 266, 595-605. View this article in WRRO
- Switched latent force models for reverse-engineering transcriptional regulation in gene expression data. IEEE/ACM Transactions on Computational Biology and Bioinformatics. View this article in WRRO
- Multi-task learning for subthalamic nucleus identification in deep brain stimulation. International Journal of Machine Learning and Cybernetics. View this article in WRRO
- Accelerating the computation of the volume of tissue activated during deep brain stimulation using Gaussian processes. Revista Facultad de Ingenieria, 2017(84), 17-26.
- Optimal state selection and tuning parameters for a degradation model in bearings using Mel-Frequency Cepstral Coefficients and Hidden Markov Chains. Ingeniare, 24(4), 570-580.
- Modeling and behavior of the simulation of electric propagation during deep brain stimulation. DYNA (Colombia), 83(198), 49-58. View this article in WRRO
- Gaussian process dynamical models for multimodal affect recognition. 2016 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC).
- Multi-output Gaussian processes for enhancing resolution of diffusion tensor fields. 2016 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC).
- Estimation of the neuromodulation parameters from the planned volume of tissue activated in deep brain stimulation. Revista Facultad de Ingeniería Universidad de Antioquia, 79, 9-18. View this article in WRRO
- SVM-based feature selection methods for emotion recognition from multimodal data. Journal on Multimodal User Interfaces.
- Generalized Wishart processes for interpolation over diffusion tensor fields.. CoRR, abs/1606.07968.
- Short-term wind speed prediction based on robust Kalman filtering: An experimental comparison. Applied Energy, 156, 321-330.
- Volume of Tissue Activated in Patients with Parkinson’s Disease from West-Center Region of Colombia Treated with Deep Brain Stimulation, 182-185.
- Sparse representation of MER signals for localizing the Subthalamic Nucleus in Parkinson's disease surgery. 2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society.
- Multiple-output support vector machine regression with feature selection for arousal/valence space emotion assessment. 2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society.
- Latent force models for describing transcriptional regulation processes in the embryo development problem for the Drosophila melanogaster. 2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society.
- Tensor-product kernel-based representation encoding joint MRI view similarity. 2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society.
- A latent force model for describing electric propagation in deep brain stimulation: A simulation study. 2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society.
- Linear Latent Force Models Using Gaussian Processes.. IEEE Trans Pattern Anal Mach Intell.
- Optimal sampling frequency in wavelet-based signal feature extraction using particle swarm optimization. 2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC).
- Feature selection for multimodal emotion recognition in the arousal-valence space. 2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC).
- Unsupervised learning applied in MER and ECG signals through Gaussians mixtures with the Expectation-Maximization algorithm and Variational Bayesian Inference. 2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC).
- Dynamic physiological signal analysis based on Fisher kernels for emotion recognition. 2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC).
- Linear Latent Force Models Using Gaussian Processes. IEEE Transactions on Pattern Analysis and Machine Intelligence, 35(11), 2693-2705. View this article in WRRO
- NEUROZONE: On-line recognition of brain structures in stereotactic surgery - application to Parkinson's disease. 2012 Annual International Conference of the IEEE Engineering in Medicine and Biology Society.
- Multi-patient learning increases accuracy for Subthalamic nucleus identification in deep brain stimulation. 2012 Annual International Conference of the IEEE Engineering in Medicine and Biology Society.
- Kernels for Vector-Valued Functions: A Review.
- Kernels for Vector-Valued Functions: A Review. Foundations and Trends® in Machine Learning, 4(3), 195-266. View this article in WRRO
- Computationally Efficient Convolved Multiple Output Gaussian Processes. JOURNAL OF MACHINE LEARNING RESEARCH, 12, 1459-1500.
- Computationally efficient convolved multiple output gaussian processes. Journal of Machine Learning Research, 12, 1459-1500.
- Kernel Principal Component Analysis through Time for Voice Disorder Classification. 2006 International Conference of the IEEE Engineering in Medicine and Biology Society.
- Identification of Spike Sources using Proximity Analysis through Hidden Markov Models. 2006 International Conference of the IEEE Engineering in Medicine and Biology Society.
- A Discriminative Multi-Output Gaussian Processes Scheme for Brain Electrical Activity Analysis. Applied Sciences, 10(19), 6765-6765.
- A Fully Natural Gradient Scheme for Improving Inference of the
Heterogeneous Multi-Output Gaussian Process Model.
- Differentially Private Regression and Classification with Sparse
Gaussian Processes. View this article in WRRO
- Continual Multi-task Gaussian Processes.
- Black-Box Inference for Non-Linear Latent Force Models.
- Modelado y comportamiento de la simulación de propagación eléctrica durante la estimulación cerebral profunda. DYNA, 83(198), 49-49.
- Variational bridge constructs for approximate Gaussian process
regression.
Conference proceedings papers
- Multi-task causal learning with Gaussian processes. Advances in Neural Information Processing Systems, Vol. 2020-December
- Heterogeneous Multi-output Gaussian Process Prediction.. Advances in Neural Information Processing Systems 31 (NIPS 2018), Vol. 31 (pp 6711-6720), 2 December 2018 - 8 December 2018. View this article in WRRO
- Sparse Gaussian Process Audio Source Separation Using Spectrum Priors in the Time-domain. ICASSP 2019 - 2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 12 May 2019 - 17 May 2019.
- Information Potential Variability for Hyperparameter Selection in the MMD Distance (pp 279-286)
- Sparse Gaussian Process Audio Source Separation Using Spectrum Priors in the Time-domain.. ICASSP (pp 995-999)
- Multi-task Learning for Aggregated Data using Gaussian Processes.. NeurIPS (pp 15050-15060)
- Non-linear process convolutions for multi-output Gaussian processes.. AISTATS, Vol. 89 (pp 1969-1977)
- Nonlinear Probabilistic Latent Variable Models for Groupwise Correspondence Analysis in Brain Structures. 2018 IEEE 28th International Workshop on Machine Learning for Signal Processing (MLSP), 17 September 2018 - 20 September 2018.
- Fast Kernel Approximations for Latent Force Models and Convolved Multiple-Output Gaussian processes. Uncertainty in Artificial Intelligence: Proceedings of the Thirty-Fourth Conference (2018), 6 August 2018 - 10 August 2018. View this article in WRRO
- Differentially Private Regression using Gaussian Processes. Proceedings of the 21st International Conference on Artificial Intelligence and Statistics (AISTATS) 2018, Vol. 84 (pp 1195-1203-1195-1203), 9 April 2018 - 11 April 2018. View this article in WRRO
- Shape Classification Using Hilbert Space Embeddings and Kernel Adaptive Filtering (pp 245-251)
- Non-stationary Multi-output Gaussian Processes for Enhancing Resolution over Diffusion Tensor Fields (pp 168-176)
- Impulse Response Estimation of Linear Time-Invariant Systems Using Convolved Gaussian Processes and Laguerre Functions (pp 281-288)
- Heterogeneous Multi-output Gaussian Process Prediction.. NeurIPS (pp 6712-6721)
- Fast Kernel Approximations for Latent Force Models and Convolved Multiple-Output Gaussian processes.. UAI (pp 835-844)
- Non-stationary Generalized Wishart Processes for Enhancing Resolution over Diffusion Tensor Fields (pp 371-381)
- Efficient Modeling of Latent Information in Supervised Learning using Gaussian Processes. Proceedings of the Neural Information Processing Systems Conference View this article in WRRO
- Bayesian optimization for fitting 3D morphable models of brain structures. Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications. CIARP 2016., Vol. 10125 (pp 291-299), 8 November 2016 - 11 November 2016. View this article in WRRO
- Definition and composition of motor primitives using latent force models and hidden Markov models. Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications. CIARP 2016., Vol. 10125 (pp 249-256), 8 November 2016 - 11 November 2016. View this article in WRRO
- Efficient Modeling of Latent Information in Supervised Learning using Gaussian Processes.. NIPS (pp 5131-5139)
- Analysis of the Geometry and Electric Properties of Brain Tissue in Simulation Models for Deep Brain Stimulation (pp 493-501)
- A Kernel-Based Approach for DBS Parameter Estimation (pp 158-166)
- Approximate Probabilistic Power Flow (pp 43-53)
- A Hierarchical K-Nearest Neighbor Approach for Volume of Tissue Activated Estimation (pp 125-133)
- Non-parametric Source Reconstruction via Kernel Temporal Enhancement for EEG Data (pp 443-450)
- Spatial Resolution Enhancement in Ultrasound Images from Multiple Annotators Knowledge (pp 502-510)
- Sparse Linear Models Applied to Power Quality Disturbance Classification (pp 521-529)
- Groupwise shape correspondences on 3d brain structures using probabilistic latent variable models. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Vol. 9474 (pp 491-500)
- Magnetic Resonance Image Selection for Multi-Atlas Segmentation Using Mixture Models (pp 391-399)
- Discriminative Training for Convolved Multiple-Output Gaussian Processes (pp 595-602) View this article in WRRO
- Indian Buffet Process for Model Selection in Latent Force Models (pp 635-642)
- Peripheral nerve segmentation using Nonparametric Bayesian Hierarchical Clustering. 2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 25 August 2015 - 29 August 2015.
- Fall Detection Algorithm Based on Thresholds and Residual Events (pp 575-583)
- Automatic segmentation of nerve structures in ultrasound images using Graph Cuts and Gaussian processes. 2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 25 August 2015 - 29 August 2015.
- Spatial-Dependent Similarity Metric Supporting Multi-atlas MRI Segmentation (pp 300-308)
- A Gaussian Process Emulator for Estimating the Volume of Tissue Activated During Deep Brain Stimulation (pp 691-699)
- Convolved Multi-output Gaussian Processes for Semi-Supervised Learning (pp 109-118)
- Automatic assessment of voice quality in the context of multiple annotations. 2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 25 August 2015 - 29 August 2015.
- Kernel Centered Alignment Supervised Metric for Multi-Atlas Segmentation (pp 658-667)
- Improving Diffusion Tensor Estimation Using Adaptive and Optimized Filtering Based on Local Similarity (pp 612-620)
- Peripheral Nerves Segmentation in Ultrasound Images Using Non-linear Wavelets and Gaussian Processes (pp 603-611)
- Peripheral Nerve Segmentation Using Speckle Removal and Bayesian Shape Models (pp 387-394)
- A Parzen-Based Distance Between Probability Measures as an Alternative of Summary Statistics in Approximate Bayesian Computation (pp 50-61) View this article in WRRO
- Dynamic Hand Gesture Recognition Using Generalized Time Warping and Deep Belief Networks (pp 682-691)
- Generalized Wishart Processes for Interpolation Over Diffusion Tensor Fields (pp 499-508) View this article in WRRO
- NEURONAV: A Tool for Image-Guided Surgery - Application to Parkinson’s Disease (pp 349-358)
- Gaussian Processes for Slice-Based Super-Resolution MR Images (pp 692-701)
- Global and Local Gaussian Process for Multioutput and Treed Data (pp 161-171)
- 3D brain atlas reconstruction using deformable medical image registration: Application to deep brain stimulation surgery. 2014 XIX Symposium on Image, Signal Processing and Artificial Vision, 17 September 2014 - 19 September 2014.
- Comparison of preprocessing methods for diffusion tensor estimation in brain imaging. 2014 XIX Symposium on Image, Signal Processing and Artificial Vision, 17 September 2014 - 19 September 2014.
- Bayesian Shape Models with Shape Priors for MRI Brain Segmentation (pp 851-860)
- Gaussian Process Dynamical Models for Emotion Recognition (pp 799-808)
- Automatic Recognition of Microcalcifications in Mammography Images through Fractal Texture Analysis (pp 841-850)
- Efficient multioutput gaussian processes through variational inducing kernels. Journal of Machine Learning Research, Vol. 9 (pp 25-32)
- Switched latent force models for movement segmentation. Advances in Neural Information Processing Systems 23: 24th Annual Conference on Neural Information Processing Systems 2010, NIPS 2010
- Latent force models. Journal of Machine Learning Research, Vol. 5 (pp 9-16)
- Sparse convolved Gaussian processes for multi-output regression. Advances in Neural Information Processing Systems 21 - Proceedings of the 2008 Conference (pp 57-64)
- Myocardial ischemia detection using Hidden Markov principal component analysis. IFMBE Proceedings, Vol. 18 (pp 99-103)
- Probabilistic Kernel Principal Component Analysis Through Time (pp 747-754)
- Kernel principal component analysis through time for voice disorder classification. 2006 28TH ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY, VOLS 1-15 (pp 2620-+)
- Identification of spike sources using proximity analysis through hidden markov models. 2006 28TH ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY, VOLS 1-15 (pp 2562-+)
- Multi-task Learning for Aggregated Data using Gaussian Processes. Proceedings of the Conference on Advances in Neural Information Processing Systems 32 (2019) View this article in WRRO
- Differentially Private Regression with Gaussian processes. Proceedings of the 21st International Conference on Artificial Intelligence and Statistics, Vol. 84 (pp 1195-1203). Playa Blanca, Lanzarote, Canary Islands, 9 April 2018 - 11 April 2018. View this article in WRRO
Reports
- Sparse Convolved Multiple Output Gaussian Processes
- Variational Inducing Kernels for Sparse Convolved Multiple Output Gaussian Processes
Working papers
- Non-linear process convolutions for multi-output Gaussian processes. AISTATS 2019 - 22nd International Conference on Artificial Intelligence and Statistics.
- A Three Spatial Dimension Wave Latent Force Model for Describing
Excitation Sources and Electric Potentials Produced by Deep Brain Stimulation.
- Indian Buffet process for model selection in convolved multiple-output
Gaussian processes.
- Correlated chained Gaussian processes for datasets with multiple annotators. IEEE Transactions on Neural Networks and Learning Systems.
- Grants
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Current grants
- Transfer learning of pharmacogenomic information across disease types and preclinical models for drug sensitivity prediction. EPSRC, 04/2021 - 03/2024, £461,757, as Co-PI
- Design, modelling and analysis for longitudinal population studies involving high-dimensional molecular measurements, Wellcome Trust, 10/2020 - 09/2023, £192,246, as PI
Previous grants
- Physically-informed probabilistic modelling of air pollution in Kampala using a low cost sensor network, EPSRC, 10/2019 - 03/2022, £409,195, as Co-PI
- PUBLIC: Powering Urban Smart Mobility with Data Analytics, InnovateUK, 09/2019 - 11/2020, £348,381, as PI
- Machine learning prediction of uncertainty in cancer therapy, RoseTrees Trust, 04/2019 - 10/2020, £181,470, as Co-PI
- Learning to move as a human: one-shot learning of human motion, EPSRC, 08/2018 - 09/2020, £219,757, as PI
- Deep Probabilistic Models for Making Sense of Unstructured Data, EPSRC, 04/2016 - 09/2019, £506,767, as PI
- Hilbert Space Embeddings of Autoregressive Processes. British Council, and COLCIENCIAS, Colombia, 05/2015 - 05/2016, £8,300, as PI
- Probabilistic spatio-temporal models based on partial dierential equations for the description of the regulatory dynamics for the Bicoid protein in the Drosophila melanogaster body segmentation problem. ECOS-NORD, France, and COLCIENCIAS, Colombia, 01/2015 - 12/2016, £13,000 as PI
- Parameter estimation for neuro-modulation in deep brain stimulation therapy for patients with Pakinson's disease from the volume of tissue activated planned. COLCIENCIAS, Colombia, 02/2014 - 12/2016, £120,000, Co-PI
- Sparse Latent Force Models for Reverse Engineering of Multiple Transcription Factors. British Council, and COLCIENCIAS, Colombia, 02/2014 - 12/2015, £8,300, as PI
- Development of an appropriate and effective system for the estimation of the volume of tissue activated for the improvement of the therapeutic results in patients with Parkinson's disease. COLCIENCIAS, Colombia, 02/2013 - 12/2015, £183,613, as Co-PI.