cv

Basics

Name Ignacio Peis
Label Postdoctoral Researcher
Email 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

Education

Teaching

Reviewing

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

Courses

Awards

Publications

  • Jun. 2023
    Variational Mixture of HyperGenerators for Learning Distributions Over Functions
    B. Koyuncu, P. Sánchez, I. Peis, P. M. Olmos, I. Valera. Proceedings of the 40th International Conference on Machine Learning, in Proceedings of Machine Learning Research 202:17660-17683

    pdf |  code |  video |  poster | 

  • Dec. 2022
    Missing Data Imputation and Acquisition with Deep Hierarchical Models and Hamiltonian Monte Carlo
    I. Peis, C. Ma, J. M. Hernández-Lobato. Advances in Neural Information Processing Systems 35 (NeurIPS)

    pdf |  code |  slides |  video |  poster | 

  • 2022
    Unsupervised Learning of Global Factors in Deep Generative Models
    I. Peis, P. M. Olmos, A. Artés-Rodríguez. Pattern Recognition, vol. 134, p. 109130

    pdf |  code | 

  • 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 | 

  • 2019
    Deep Sequential Models for Suicidal Ideation from Multiple Source Data
    I. Peis, P. M. Olmos, C. Vera-Varela, M. L. Barrigón, P. Courtet, E. Baca-García, A. Artés Rodríguez. Journal of Biomedical and Health Informatics, vol. 23, no. 6. IEEE

    pdf |  html | 

  • 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

    html | 

Dissertations

  • 2023
    Advanced Inference and Representation Learning Methods in Variational Autoencoders
    I. Peis. PhD Thesis Dissertation (Probabilistic Machine Learning)

    pdf |  slides | 

  • 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)

Languages

Spanish
Native speaker
English
Fluent