OK Physics

Homepage of physicist Oliver Sølund Kirsebom

Oliver Sølund Kirsebom
PhD Physics
Lead Data Scientist at Open Ocean Robotics and Adjunct Professor in the Faculty of Computer Science at Dalhousie University
Academic CV
LinkedIn: linkedin.com/in/okayphysics
ORCID ID: 0000-0001-5843-7465
email:
code: github.com/oliskir

Bio

I have a PhD in nuclear physics from Aarhus University, Denmark. For more than a decade, I was a frequent visitor at particle accelerator laboratories such as CERN in Switzerland, performing experiments to advance our understanding of the nuclear astrophysical processes that have shaped our Universe. Nowadays, however, my focus has shifted to a more applied realm. As the Lead Data Scientist at Open Ocean Robotics, I help making sense of a wide range of ocean sensor data collected by unmanned surface vessels, building data analysis pipelines, for example, automating the detection and classification of marine mammal vocalisations. I am also actively involved in the HALLO research project and a member of ONC’s Ocean Observatory Council and the NoiseTracker Technical Committee.

On this page you will find an overview of my scientific contributions, which include open-source software, research papers, feature articles & media coverage, and presentations given at various conferences and workshops.

Software

I am currently the lead developer on two open-source Python packages: ketos, which helps you develop deep learning models for analyzing underwater sound (for example, detecting whale calls), and kadlu, which provides tools for modelling underwater sound propagation.

I have also developed a fair amount of specialized code in C++ and Fortran for analyzing nuclear-physics data and simulating various atomic and nuclear processes. Some of this code is publicly available (simX, Open R-matrix, DCAP, VeikonKone, bedepe), but the majority remains behind locked doors on the code repository of my old research group in Aarhus.

On my github page you will find a few personal coding projects including numerical solutions to the time-dependent and time-independent Schrodinger equations implemented in Python.

Research papers

I do my best to keep my ORCID profile up to date, and I also have a Google Scholar profile that Google kindly keeps up to date for me. Below, is a selection of recent or noteworthy papers.

Feature articles and media coverage

Presentations