World's Best Scientists 2026 revealed!
Fernando Perez-Cruz

Fernando Perez-Cruz

D-Index & Metrics

Computer Science

D-Index
39
Citations
7485
World Ranking
9665
National Ranking
173

Overview

Fernando Perez-Cruz is affiliated with ETH Zurich in Switzerland and has a diverse research portfolio primarily in the fields of Computer Science and Engineering. Their work spans multiple subfields including Artificial Intelligence, Civil and Structural Engineering, Computer Vision and Pattern Recognition, Signal Processing, and Global and Planetary Change.

The scientist's research topics focus on areas such as Infrastructure Maintenance and Monitoring, Gaussian Processes and Bayesian Inference, Structural Health Monitoring Techniques, Generative Adversarial Networks and Image Synthesis, Traffic Prediction and Management Techniques, Hydrology and Watershed Management Studies, and Computational Drug Discovery Methods.

Fernando Perez-Cruz has contributed to a number of recent publications, including the following papers:

  • Facilitated machine learning for image-based fruit quality assessment, 2022, Journal of Food Engineering
  • Generating LOD3 building models from structure-from-motion and semantic segmentation, 2022, Automation in Construction
  • Integration and calibration of non-dispersive infrared (NDIR) CO 2 low-cost sensors and their operation in a sensor network covering Switzerland, 2020, Atmospheric Measurement Techniques
  • TOPO-Loss for continuity-preserving crack detection using deep learning, 2022, Construction and Building Materials
  • Data-driven automated predictions of the avalanche danger level for dry-snow conditions in Switzerland, 2022, Natural Hazards and Earth System Sciences

The scientist has frequently published in venues such as:

  • arXiv (Cornell University), 25 publications
  • Zenodo (CERN European Organization for Nuclear Research), 11 publications
  • bioRxiv (Cold Spring Harbor Laboratory), 4 publications
  • Repository for Publications and Research Data (ETH Zurich), 3 publications
  • Automation in Construction, 2 publications

Among book contributions, Fernando Perez-Cruz has published three titles with Springer Science+Business Media under the series "Machine Learning and Knowledge Discovery in Databases. Research Track" in 2021, with citation counts of 15, 8, and 3 respectively.

The scientist has collaborated extensively with several co-authors, including:

  • Nathanaël Perraudin, 12 joint publications
  • Lilian Gasser, 9 joint publications
  • Romana Rust, 8 joint publications
  • Gonzalo Casas, 8 joint publications
  • Matthias Köhler, 8 joint publications

Best Publications

  • Deep Models Under the GAN: Information Leakage from Collaborative Deep Learning

    Briland Hitaj;Giuseppe Ateniese;Fernando Perez-Cruz

  • Kullback-Leibler divergence estimation of continuous distributions

    F. Perez-Cruz

  • Multioutput Support Vector Regression for Remote Sensing Biophysical Parameter Estimation

    D. Tuia;J. Verrelst;L. Alonso;F. Perez-Cruz

  • SVM multiregression for nonlinear channel estimation in multiple-input multiple-output systems

    M. Sanchez-Fernandez;M. de-Prado-Cumplido;J. Arenas-Garcia;F. Perez-Cruz

  • Multi-dimensional function approximation and regression estimation

    Fernando Perez-Cruz;Gustavo Camps-Valls;Emilio Soria-Olivas;Juan José Perez-Ruixo

  • Expectation Propagation Detection for High-Order High-Dimensional MIMO Systems

    Javier Cespedes;Pablo M. Olmos;Matilde Sanchez-Fernandez;Fernando Perez-Cruz

  • Wireless RSSI fingerprinting localization

    Simon Yiu;Marzieh Dashti;Holger Claussen;Fernando Perez-Cruz

  • PassGAN: A Deep Learning Approach for Password Guessing

    Briland Hitaj;Paolo Gasti;Giuseppe Ateniese;Fernando Perez-Cruz

  • MIMO Gaussian Channels With Arbitrary Inputs: Optimal Precoding and Power Allocation

    F. Perez-Cruz;M.R.D. Rodrigues;S. Verdu

  • Joint Source and Channel Coding

    Maria Fresia;Fernando Peréz-Cruz;H Vincent Poor;Sergio Verdú

  • Methods for feature selection in a learning machine

    Jason Aaron Edward Weston;André Elisseeff;Bernhard Schoelkopf;Fernando Pérez-Cruz

  • Gaussian Processes for Nonlinear Signal Processing: An Overview of Recent Advances

    F. Perez-Cruz;S. Van Vaerenbergh;J. JoseMurillo-Fuentes;M. Lazaro-Gredilla

  • Kernel methods and their potential use in signal processing

    F. Perez-Cruz;O. Bousquet

  • Estimating GARCH models using support vector machines

    Fernando Pérez-cruz;Julio A Afonso-rodríguez;Javier Giner

  • Feature selection and transduction for prediction of molecular bioactivity for drug design.

    Jason Weston;Fernando Pérez-Cruz;Olivier Bousquet;Olivier Chapelle

  • Gaussian Processes for Nonlinear Signal Processing

    Fernando Pérez-Cruz;Steven Van Vaerenbergh;Juan José Murillo-Fuentes;Miguel Lázaro-Gredilla

  • Machine learning and data mining: strategies for hypothesis generation

    M A Oquendo;E Baca-Garcia;A Artés-Rodríguez;F Perez-Cruz;F Perez-Cruz

  • Weighted least squares training of support vector classifiers leading to compact and adaptive schemes

    A. Navia-Vazquez;F. Perez-Cruz;A. Artes-Rodriguez;A.R. Figueiras-Vidal

  • An IRWLS procedure for SVR

    F. Perez-Cruz;A. Navia Vazquez;P. L. Alarcon-Diana;A. Artes-Rodriguez

  • Estimation of Information Theoretic Measures for Continuous Random Variables

    Fernando Pérez-Cruz

Frequent Co-Authors

Jason Weston
Jason Weston Facebook (United States)
Bernhard Schölkopf
Bernhard Schölkopf Max Planck Institute for Intelligent Systems
Ignacio Santamaria
Ignacio Santamaria University of Cantabria
Sergio Verdu
Sergio Verdu Princeton University
Miguel R. D. Rodrigues
Miguel R. D. Rodrigues University College London
Isabelle Guyon
Isabelle Guyon University of Paris-Saclay
Sancho Salcedo-Sanz
Sancho Salcedo-Sanz University of Alcalá
Giuseppe Ateniese
Giuseppe Ateniese George Mason University
Aníbal R. Figueiras-Vidal
Aníbal R. Figueiras-Vidal Carlos III University of Madrid
Howard Huang
Howard Huang Nokia (United States)

If you think any of the details on this page are incorrect, let us know.

Report an issue

We appreciate your kind effort to assist us to improve this page, it would be helpful providing us with as much detail as possible in the text box below:

Related Online Degrees & Career Pathways

The landscape of computer science education in the USA now offers more flexible options than ever before. Prospective students can access a variety of degree levels online, catering to different academic backgrounds and career plans. For those just starting out or seeking a foundation, online associates degree programs provide a convenient entry point into the field, often at a lower cost and with a shorter time commitment.

Many learners are concerned about tuition costs. Fortunately, there are affordable online colleges that make studying computer science more accessible without sacrificing quality. Additionally, those with previous academic challenges are not left behind—numerous online colleges that accept low gpa provide pathways for students to prove themselves and advance in the tech industry.

For career advancement, students often consider most in demand masters degrees in computer science and related tech fields. These advanced credentials unlock specialized opportunities and higher earning potential. No matter your starting point, there are flexible, reputable online degree programs to help you achieve your computer science career goals.

Best Scientists Citing Fernando Perez-Cruz

Trending Scientists

Recently Published Articles