Daniel Rud Andreasen

Background

About Daniel Rud Andreasen

I'm an algorithm development engineer specializing in image/signal processing and machine learning. My passion lies in exploring the latest technologies, particularly in image and signal processing, and collaborating with teams to develop innovative solutions. Education: I completed my BSc. and MSc. in Medicine and Technology (biomedical engineering) at the Technical University of Denmark (DTU) and Copenhagen University (KU). During my studies, I focused on signal processing and image analysis, completing courses like Medical Image Analysis, Applied Signal Processing, and Advanced Image Analysis. My thesis,"Creating a Pseudo-CT from MRI for MRI-only based Radiation Therapy Planning," received the highest grade. I further pursued my academic interests with a PhD in medical image analysis from the Department of Applied Mathematics and Computer Science at DTU and the Radiotherapy Research Unit at Herlev Hospital. My research focused on developing predictive models to estimate CT scans from MRI data, collaborating with multidisciplinary teams to ensure clinical relevance and accuracy. Professional Experience: Currently, I'm serving as a Senior Algorithm Development Engineer at Egis Technology in Copenhagen. Here, I am working in a talented team to develop algorithms for biometric authentication. My responsibilities revolve around enhancing algorithm performance mainly by addressing image processing challenges like temporal noise, online learning and compensation of fixed pattern noise, and optimizing image components for better accuracy, among others. In my work, I am navigating and meeting stringent algorithm complexity and latency requirements, ensuring optimal performance on diverse sensor and compute platforms. I am also contributing to the creation of Python software tools to aid the algorithm development processes. Additionally, I have gained familiarity with computer vision techniques for image matching and worked with deep learning techniques, particularly in image restoration and enhancement using PyTorch and Keras. With proficiency in programming languages such as Python and C, along with strong skills in data analysis and technical documentation, I'm well-equipped to tackle complex challenges in algorithm development. In addition to my technical expertise, I am used to working within a Continuous Integration/Continuous Deployment (CI/CD) setting. I am accustomed to collaborating with cross-functional teams to ensure seamless integration of algorithms, maintaining high standards of quality and efficiency through code reviews.