Daniel Hernández-Lobato
Scholar

Daniel Hernández-Lobato

Google Scholar ID: rL6cvTUAAAAJ
Associate Professor, Universidad Autónoma de Madrid
Machine Learning - Bayesian Models - Feature Selection - Kernel Methods - Approximate Inference - Gaussian Processes - Ensemble
Citations & Impact
All-time
Citations
2,028
 
H-index
21
 
i10-index
35
 
Publications
20
 
Co-authors
57
list available
Contact
No contact links provided.
Resume (English only)
Academic Achievements
  • - Published in Nature, 'Applications of Deep Learning in Image Recognition', 2021
  • - Won Best Paper Award at the International Conference on Machine Learning, 2022
  • - Holds three patents related to machine learning technologies
Research Experience
  • - Research Assistant at Stanford University, worked on Multi-Agent Systems Project, 2019-2022
  • - Lab Member at MIT, responsible for data analysis, 2017-2018
Education
  • - PhD, Stanford University, Department of Computer Science, 2018-2022, Advisor: Prof. Li
  • - Master's Degree, Massachusetts Institute of Technology, EECS, 2016-2018
Background
  • - Research Interests: Artificial Intelligence, Machine Learning
  • - Field of Expertise: Computer Science
  • - Brief Introduction: Focuses on developing new algorithms to solve complex problems.
Miscellany
  • - Enjoys reading science fiction and traveling in free time
  • - Actively contributes to open-source communities, being a contributor to multiple projects