cv
Basics
Name | Ignacio Peis |
Label | Postdoctoral Researcher |
ipeaz@dtu.dk | |
Url | https://ipeis.github.io/ |
Summary | Passionate about AI and ML with a PhD in Probabilistic Machine Learning; enthusiasted about bridging the gap between fundamental research and real-world applications |
Work
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2023.10 - Present Copenhagen, Denmark
Postdoctoral Researcher
Technical University of Denmark (DTU)
Research in Deep Generative Modelling, Approximate Inference and its applications. Working within Jes Frellsen's group at the Section for Cognitive Systems. Awarded with postdoctoral fellowship by the Danish Data Science Academy (DDSA), funded by the Novo Nordisk Foundation.
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2021.02 - 2022.02 Cambridge, UK
Research Visitor
University of Cambridge
Research visitor in the Machine Learning Group under the supervision of Prof. José Miguel Hernández-Lobato.
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2020.12 - Present Madrid, Spain
Course Instructor
Fundación UC3M
Instructor for Fundamental, Intermediate, and Advanced Machine Learning courses for BBVA employees.
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2019.10 - 2023.09 Madrid, Spain
Predoctoral Researcher
Universidad Carlos III de Madrid (UC3M)
Research in Deep Generative Modelling, Approximate Inference and Representation Learning, supervised by Prof. Antonio Artés-Rodríguez and Dr. Pablo M. Olmos from the Signal Processing Group.
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2017.02 - 2019.09 Madrid, Spain
Research Associate
Universidad Carlos III de Madrid (UC3M)
Research Associate role under the supervision of Prof. Antonio Artés-Rodríguez.
Education
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2019.10 - 2023.10 Madrid, Spain
PhD
Universidad Carlos III de Madrid
Probabilistic Machine Learning
Cum Laude
Outstanding Thesis Award
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2016.09 - 2018.07 Madrid, Spain
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2016.09 - 2018.07 Madrid, Spain
MSc
Universidad Carlos III de Madrid
Multimedia and Communications
One course with honors
Dissertation with highest mark
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2012.09 - 2016.07 Granada, Spain
Awards
- 2023.12.01
Outstanding Thesis Award
Universidad Carlos III de Madrid
Recognition of the quality of doctoral research work based on their scientific and technological contributions.
- 2023.05.01
Postdoctoral Fellowship
Danish Data Science Academy (DDSA), Novo Nordisk Foundation
Postdoctoral Fellowship awarded for exceptional research work.
Grants
- 2021.09.01
- 2019.09.01
Talks
- 2023-12
Variational Mixture of HyperGenerators for Learning Distributions Over Functions
Andaluz.IA forum at Universidad Pablo de Olavide, Sevilla, Spain
slides - 2023-06
Information Acquisition and Distributions of Functions with Deep Generative Models
Pioneer Centre for Artificial Intelligence, Copenhagen, Denmark
slides - 2022-12
Missing Data Imputation and Acquisition with Deep Hierarchical Models and Hamiltonian Monte Carlo
Oral (video) and poster presentation
NeurIPS22, New Orleans, USA
slides | video | poster - 2022-06
Missing Data Imputation and Acquisition with Deep Hierarchical Models and Hamiltonian Monte Carlo
Signal Processing Group, Universidad Carlos III de Madrid
- 2018-07
Deep Sequential Models for Suicidal Ideation from Multiple Source Data
Signal Processing Group, Universidad Carlos III de Madrid
Teaching
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2020 - Present Course in Machine Learning Fundamentals
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2022 - Present Course in Intermediate Machine Learning and Feature Engineering
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2023 - Present Course in Advanced Machine Learning
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2020.09 - 2023.01 Machine Learning II
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2022.01 - 2022.06 -
2022.01 - 2022.06 Neural Networks
Reviewing
Publications
- Jun. 2024
Scalable physical source-to-field inference with hypernetworks
B. Janes, S. Pollok, I. Peis, J. Frellsen, R. Bjørk. arXiv preprint arXiv:2405.05981
pdf |
- Jun. 2023
- 2020
Actigraphic recording of motor activity in depressed inpatients: a novel computational approach to prediction of clinical course and hospital discharge
I. Peis, J. D. López-Moríñigo, M. M. Pérez-Rodríguez, M. L. Barrigón, M. Ruiz-Gómez, A. Artés-Rodríguez, E. Baca-García. Scientific reports, 10. Nature
pdf |
- 2017
A Heavy Tailed Expectation Maximization Hidden Markov Random Field Model with Applications to Segmentation of MRI
D. Castillo-Barnes, I. Peis, F. J. Martínez-Murcia, F. Segovia, I. A. Illán, J. M. Górriz, J. Ramírez, D. Salas-Gonzalez. Frontiers in Neuroinformatics, 11, 66
pdf |
- 2016
MRI brain segmentation using hidden Markov random fields with alpha-stable distributions
I. Peis, I. A. Illán, F. J.Martínez-Murcia, F. Segovia, J. M. Górriz, J. Ramírez, E. W. Lang, D. Salas-Gonzalez. IEEE Nuclear Science Symposium, Medical Imaging Conference and Room-Temperature Semiconductor Detector Workshop (NSS/MIC/RTSD) (pp. 1-3). IEEE
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Dissertations
- 2018
Activity monitoring in depressed patients in the hospital setting: a pilot study testing new methods of actigraphy data analysis for predicting clinical progress and date of hospital discharge
I. Peis. M.Sc. Thesis Dissertation (Telecommunications Engineering)
- 2018
Deep sequential models with attention for psychiatric patients clinical assessment
I. Peis. M.Sc. Thesis Dissertation (Multimedia and Communications)
- 2016
Hidden Markov Random Fields with alpha-stable distributions for brain Magnetic Resonance Images
I. Peis. B.Sc. Thesis Dissertation (Telecommunications Engineering)
Courses
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2022.09 - 2022.09 Cambridge, UK
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2020.09 - 2020.09 Sheffield, UK
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2019.09 - 2019.09 Basel, Switzerland
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2019.09 - 2019.09 Moscow, Russia
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2018.09 - 2018.09 Madrid, Spain
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2017.09 - 2017.09 Sheffield, UK