CV#
Daniel Mo Houshmand. Artist, applied mathematician and founder of QDaria, Oslo.
Education#
Degree |
Institution |
|---|---|
MSc, Applied Mathematics, Mechanics and Numerical Physics |
University of Oslo (UiO) |
BSc, Civil Engineering |
Oslo and Akershus University College of Applied Sciences (HiOA, now OsloMet) |
BA, Design and Modelling Techniques |
ESMOD Bordeaux/Oslo |
Specialisations. Mathematics for machine learning; quantum machine learning (University of Toronto, edX); quantum computer hardware (TU Delft, edX).
Experience#
Period |
Role |
|---|---|
From 2019 |
Founder of QDaria, a quantum-computing company in Oslo; CEO from 2019, elected by the board |
2018 |
CTO of iProud, backed by Xplorico and Malaysian officials: a personal coach built on hybrid machine-learning algorithms |
2022 |
Data handling, infrastructure design and full-stack development at NAV; began Zipminator |
2017 |
Data scientist, NAV AI Lab, one of its first |
Earlier |
Proofreading for Professor Hans Petter Langtangen, including Finite Difference Computing with Partial Differential Equations |
Projects#
Zipminator. Post-quantum encryption software built on NIST FIPS 203 (ML-KEM-768) and real quantum entropy. Source on GitHub.
This site. Notes on quantum mechanics, quantum computer hardware and quantum machine learning, as an interactive Jupyter Book.
Teaching#
Fluid art. Acrylic-pouring courses at tegneskole.no, with course notes in Norwegian (2021).
Art#
Fluid-art paintings: the Bad Bloom series (2021), the Northern Light series (2020) and Rajee’s Torch (2019); and Optimised FEM geometry (2014), a finite-element mesh as a drawing. See the Art part.
Expertise#
Fluid art; fluid mechanics and turbulence; computational fluid dynamics; numerical methods for partial differential equations; data science and statistics; machine learning; quantum computing, quantum hardware and quantum machine learning; post-quantum cryptography; full-stack software.