September 2021 – Present

Senior Consultant


Equinor Scientific Computing Team

  • Refactoring data-assimilation algorithms for reservoir engineering.
  • Developed the GraphSPME sparse precision estimation library.
  • Developed the Ensemble Information Filter and Smoother algorithms.

Norwegian Hull Club

  • Workshop on automatic and adaptive gradient tree boosting
January 2021 – Present

Adjunct Associate Professor

University of Bergen, Department of Mathematics

  • Research: Developing information theory for automatic ML-algorithms.
  • Teaching and seminars: Course development for actuarial and data-science courses.
  • Master student supervision.
September 2020 – August 2021

Data Scientist & Actuary


  • Translate business needs into mathematical (optimization) problems.
  • Advocate version control, code-standards, packaging, CI/CD, containerisation.
  • Introduced advanced regression techniques such as GBM and mixed effects GAM.
September 2017 – August 2020

PhD Candidate

University of Stavanger

Research areas:

  • Information theoretic gradient tree boosting: aGTBoost
  • Saddlepoint addjusted inversion of characteristic functions
June 2016 – August 2017



Responsibilities include:

  • Extraction, preprocessing, and analysis of large amounts of data
  • Pricing of products and risks
  • Analysis of customer behaviour
January 2015 – December 2017

Research assistant

University of Bergen

Hosted seminars in the “Kaggle club” at UiB

Teaching assistant:

  • STATLEARN: Statistical Learning
  • STAT220: Stochastic Processes
  • MAT102: Elementary Calculus II
  • STAT101: Elementary Statistics





Coffee & Code


Recent Posts

In my previous post, I mentioned my friend and previous co-worker at Tryg, Ole Schei, that is wonderfully meticulous, and has for some …

Student acceptance Lately I got to play with some very interesting data, relating to student acceptance (and ranking) into applied …

I was intending to write a longer blog-post about my favourite dataset of all time: the internet surf-times of a previous co-worker …

We seek to employ the framework of the R package Template Model Builder TMB (Kristensen et al. 2016) which approximately “integrates …

Four years ago, back in 2014, a friend from HKUST, that had started working in the finance industry, asked me about the VIX. He could …




Adaptive and automatic gradient boosting computations


Using TMB to build the saddlepoint approximation.


Saddlepoint adjusted inversion of characteristic functions.

Recent Publications

For certain types of statistical models, the characteristic function (Fourier transform) is available in closed form, whereas the …

This thesis considers the problem of likelihood- based parameter estimation for time-homogeneous jump-diffusion processes. The problem …

Recent Talks

More Talks

Gradient boosting has been highly successful in machine-learning competitions for structured/tabular data since the introduction of …

Gradient boosting has been highly successful in machine-learning competitions for structured/tabular data since the introduction of …

In gradient tree boosting, the functional form of the ensemble repeatedly changes during training. To select a sensible functional …