-
Notifications
You must be signed in to change notification settings - Fork 2
Commit
This commit does not belong to any branch on this repository, and may belong to a fork outside of the repository.
Merge pull request #6 from khoffschlag/patch-1
Fill Kevin's profile with information
- Loading branch information
Showing
1 changed file
with
60 additions
and
1 deletion.
There are no files selected for viewing
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
Original file line number | Diff line number | Diff line change |
---|---|---|
@@ -1 +1,60 @@ | ||
# Kevin Hoffschlag | ||
# Kevin Hoffschlag | ||
|
||
::::{grid} 2 | ||
|
||
:::{image} ../figures/kevin-hoffschlag.* | ||
:alt: Kevin Hoffschlag | ||
:width: 400px | ||
:align: left | ||
::: | ||
|
||
::: {card} Hello 👋 I'm a research assistant with a passion for AI, computer vision and medicine. | ||
My research is about deep learning based harmonization of MRI data. | ||
|
||
email: kevin.hoffschlag@uk.essen.de | ||
::: | ||
|
||
:::: | ||
|
||
|
||
::: {card} | ||
At the Predictive Neuroscience Lab, I’m excited about contributing to our team's efforts in leveraging AI to tackle complex neuroscience challenges. | ||
|
||
My research focuses on developing deep learning-based methods for harmonizing MRI data across different sites. | ||
This harmonization process is designed to address batch effects — variations in data that arise from differences in scanner equipment or imaging protocols. | ||
These batch effects can introduce significant biases into multi-site MRI studies, making it challenging to draw reliable conclusions from downstream analyses. | ||
By mitigating these effects, we aim to enhance the generalizability and reproducibility of analysis findings in multi-site MRI studies. | ||
|
||
::: | ||
|
||
:::{dropdown} Experience | ||
:close: | ||
1. **Research Assistant**<br> | ||
Predictive Neuroscience Lab<br> | ||
Essen, NRW, Germany<br> | ||
July 2024 - Present<br> | ||
Researching about deep learning based harmonization of MRI data. | ||
<br><br> | ||
|
||
2. **Student Assistant**<br> | ||
Predictive Neuroscience Lab<br> | ||
Essen, NRW, Germany<br> | ||
October 2020 - June 2024<br> | ||
Co-developed the neuroimaging workflow management system PUMI and applied machine learning techniques in the field of neuroscience (e.g., brain age prediction, MRI harmonization). | ||
<br><br> | ||
::: | ||
|
||
|
||
:::{dropdown} Education | ||
:close: | ||
1. **University of Duisburg-Essen**<br> | ||
Master's degree in Applied Computer Science<br> | ||
2023 - Present<br> | ||
<br><br> | ||
|
||
2. **University of Duisburg-Essen**<br> | ||
Bachelor's degree in Applied Computer Science<br> | ||
2019 - 2023<br> | ||
Thesis: Implementation of a Data Augmentation System for Image Datasets | ||
<br><br> | ||
::: |