Christoffer recently graduated his doctorate education in applied physics, and is particularly interested in programming and problem solving. With years of experience within algorithmic implementation, lab setup automation and data analysis, he excels at solving challening problems with his computer.
During several of his academic projects, his role was focused on making the research process more efficient through automatic data treatment and removing much of the manual labour component from common work tasks. Being a social and outgoing person, he often traded problems with colleagues, taking their programming tasks in exchange for them solving other problems that was not as suited to Christoffer’s abilities. In this way, everyone became a winner and each project could move on at a faster pace.
In short, efficiency is key.
| Languages | Experience | Rating | Last used |
|---|---|---|---|
| Python | 6 years | 5 | 2021 |
| MATLAB | 3 years | 4 | 2019 |
| C# | 1 years | 3 | 2021 |
| C++ | 1 years | 3 | 2021 |
| HTML | 1 years | 3 | 2020 |
| CSS | 1 years | 2 | 2017 |
| Java | 1 years | 3 | 2016 |
| JSON | 1 years | 3 | 2020 |
| LabVIEW | 1 years | 3 | 2014 |
| React | 1 years | 2 | 2021 |
| Javascript | 1 years | 2 | 2021 |
| C | 1 years | 3 | 2021 |
| Tool | Experience | Rating | Last used |
|---|---|---|---|
| Eclipse | 1 years | 2 | 2021 |
| Git | 1 years | 3 | 2021 |
| Matlab | 3 years | 4 | 2019 |
| PyCharm | 1 years | 2 | 2021 |
| QT | 1 years | 2 | 2015 |
| Unity | 1 years | 3 | 2021 |
| Visual Studio | 3 years | 3 | 2021 |
| Tool | Experience | Rating | Last used |
|---|---|---|---|
| Algorithms | 7 years | 5 | 2021 |
| Artificial Intelligence | 2 years | 3 | 2021 |
| Git | 1 years | 3 | 2021 |
| JSON | 1 years | 3 | 2021 |
| Keras | 1 years | 3 | 2021 |
| Machine Learning | 2 years | 3 | 2021 |
| MySQL | 1 years | 2 | 2020 |
| Tensorflow | 1 years | 3 | 2021 |
| Linux | 2 years | 3 | 2021 |
| Language | Skill level |
|---|---|
| Swedish | Native speaker |
| English | Near native / fluent |
| C# | Good working knowledge |
Embedded C++ project using PlatformIO and Arduino environment to emulate a measurement device. In this project, the emulator had to communicate both with SPI with other devices in the setup, but also through the Serial port to a Python script which forwarded it to other devices on the network using UDP.
A project with three components: Signal processing and measurement on a Raspberry Pi, a database back-end written in Python, and a basic webpage interface coded in Javascript and React.
Two modules were coded and integrated into a larger project called DNA Barcoding. The first module is used to calculate the probability that two noisy time series originated from the same underlying data, The second module assembled a thousand-piece jigsaw puzzle of small noisy time series fragments. In this project stochastic optimisation methods were used, as well as data analysis tools like FFT and statistics.
A model time-reduction tool was developed over the course of the project. This tool used a variaty of semi-stochastic methods to calculate optimal selections of differential equations in order to conserve original model performance, while decreasing time usage significantly.
