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Camilla Lingjærde

Postdoctoral Fellow - Statistics and Data Science
Image of Camilla Lingjærde
Room 804
Username
Visiting address Moltke Moes vei 35 Niels Henrik Abels hus 0851 Oslo
Postal address Postboks 1053 Blindern 0316 Oslo

Marie Skłodowska-Curie Actions COFUND Postdoctoral Fellow

Integreat Postdoctoral Fellow
University of Oslo, Department of Mathematics

Academic interests

The development of statistical and machine learning methods with increased accuracy, reliability, and applicability. Some key topics include:

  • High-dimensional statistics

  • Scalable inference

  • Graphical modelling

  • Integrative/multi-task learning

  • Causal learning

  • Statistical machine learning

  • Statistical omics

Background

Camilla finished her PhD in Statistics at the University of Cambridge in 2023, under the supervision of Prof. Sylvia Richardson and Dr. Hélène Ruffieux. Her thesis, “Joint Network Modelling of Omics Data for Understanding Complex Diseases”, is focused on the development of novel Bayesian methodology for integrative modelling of conditional dependencies in extremely high-dimensional data, with applications in autoimmune disease and cancer omics.

Postdoctoral project

MSCA co-funded project “CLEVER” (Causal multi-task machine Learning for Enhanced Versatility, Equity and Robustness)

The project is aimed at advancing the field of machine learning by developing new supervised learning methods that, by integrating causal inference principles, exhibit enhanced robustness, particularly in their ability to generalize adequately to new domains. Robust algorithms are essential for mitigating errors in critical applications, such as healthcare and environmental monitoring, and ensuring Artificial Intelligence (AI)'s equitable performance across diverse populations.

Collaborators

Awards

  • NR Master Thesis Award for the best thesis within the fields of mathematics and IT at the University of Oslo (2019)

  • AKER Scholarship for full PhD at the University of Cambridge (2019-2023)

  • NORAM Scholarship for semester at UC Berkeley (2018)

  • Abelstipend from the Norwegian Mathematical Society for semester at UC Berkeley (2018)

Publications

For a complete list, see Camilla’s Google Scholar profile.

Tags: Statistics, statistics and data science, data science, Machine Learning

Publications

  • Hellton, Kristoffer Herland; Lingjærde, Camilla & Bin, Riccardo De (2024). Influence of single observations on the choice of the penalty parameter in ridge regression. Journal of Statistical Computation and Simulation. ISSN 0094-9655. doi: 10.1080/00949655.2024.2440542. Full text in Research Archive

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Published Sep. 27, 2024 11:46 AM - Last modified Sep. 27, 2024 2:58 PM