CV

Assistant Professor and industry-experienced researcher specializing in computer vision, image reconstruction, and computational photography. Blend of academic rigor and real-world impact from roles at Aalborg University, Milestone Systems, Intel, and HSA Systems. Track record across super-resolution, low-light/thermal imaging, and multi-object detection. Comfortable operating end-to-end, from problem framing and dataset design to model development, deployment on embedded/GPU platforms, and teaching and mentoring students/engineers.

Core Strengths

• Computer Vision: Real-world super-resolution, low-light/thermal enhancement, object detection & segmentation, image formation modeling
• Deep Learning: Model design, training & evaluation; PyTorch, TensorFlow; distributed training, multi-task learning; transformers; Mixture-of-Experts
• Deployment & Systems: Real-time CV on embedded platforms (e.g., NVIDIA Jetson), GPU optimization, MLOps, CI/CD, unit testing
• Data & HPC: Dataset curation, annotation strategy, experiment tracking; DGX, Slurm, Singularity; Python scientific stack
• Leadership: Lab co-management, HPC governance, course design and teaching, supervision and mentoring

Experience

Research Consultant — Milestone Systems
Oct 2024 – Present
Bridging research and industry.

Assistant Professor, Visual Analysis & Perception Lab (VAP) — Aalborg University
Nov 2023 – Present
Teaching Deep Learning, Image Processing & Computer Vision, Machine Vision & Machine Learning, and MLOps; course design and examination. Supervision of BSc/MSc/PhD students and research assistants; co-lead research projects. Service & leadership: lab management; HPC governance board member (Pioneer Centre for AI, P1).

Research Assistant, VAP — Aalborg University
Jun 2023 – Nov 2023
Supported ongoing projects in computer vision; contributed to dataset design and benchmarking.

PhD Fellow (Milestone Research Programme), VAP — Aalborg University
May 2020 – May 2023
Focus: Image Super-Resolution for real-world applications; emphasis on surveillance imagery, low-light imaging, and task-aware SR.
Collaborations: IVRL at EPFL (Switzerland) and Milestone Systems (Denmark).

Software Developer & Deep-Learning Specialist — HSA Systems
Jul 2017 – May 2020
Development engineer on intelligent-camera products: built AI-based barcode-reader software, a Linux MIPI camera driver, and customer-facing SDKs, with prototype hardware and embedded implementations across STM32/ARM (ST CubeMX) and Lattice FPGA.
Project manager on an intelligent-camera project; administered Linux server infrastructure including a GPU-based deep-learning server.
Supervised university students on the camera team and demonstrated products publicly (HI-Messen 2019).

Student Software Developer — Intel Mobile Communications
2014 – 2017
Built automated test-automation software and frameworks for RF driver verification, integrated into CI/CD pipelines for continuous regression testing. Worked in an Agile development environment applying DevOps practices across build, test, and deployment.

Earlier Roles
2016 – 2017

• Computer Vision Intern, HSA Systems (2016)
• Student Researcher, Aalborg University — Super-Resolution with CNNs (2016)
• Student Programmer, Aalborg University — SmartC2Net (2014)
• Automotive Technician, Uggerhøj Frederikshavn — engine management & CAN bus diagnostics (2001–2011)

Education & Training

• University Pedagogical Programme, Aalborg University — 2024
• PhD, Image Super-Resolution for Real-World Applications, Aalborg University — 2020–2023
• MSc, Vision, Graphics & Interactive Systems, Aalborg University — 2015–2017
• BSc, Computer Engineering (Communication Systems), Aalborg University — 2012–2015
• Bridging Course for Engineering Studies, Aalborg University — 2011–2012
• Automotive Technician, Autobranchens Udviklingscenter Frederikshavn — Earlier

Selected Publications

• WACV 2024: PDA-RWSR: Pixel-Wise Degradation Adaptive Real-World Super-Resolution
• SCIA 2023: RELIEF: Joint Low-Light Image Enhancement & Super-Resolution with Transformers
• IET IP 2022: Real-world super-resolution of face images from surveillance cameras
• NeurIPS 2021: RELLISUR: A Real Low-Light Image Super-Resolution Dataset

Patents

• Patent (2024): A method of training a neural network, apparatus and computer program for carrying out the method — US Patent Application 18/595,002
• Patent (2023): Image processing method, apparatus, and non-transitory computer-readable medium — US Patent Application 18/069,089

Teaching & Supervision

• Courses: Deep Learning; Image Processing & Computer Vision; Machine Vision & Machine Learning; MLOps; AI Programming; Perception & Acquisition of Data
• Supervision: 30+ BSc and MSc thesis projects plus PhD co-supervision (Aalborg University, 2021–Present); supervision of university students during industry role at HSA Systems (2017–2020)

Dissemination & Academic Service

• Workshop & Challenge: Co-organiser, Real-World Surveillance (RWS) Workshop at IEEE/CVF WACV; host of the associated Real-World Surveillance challenge (vap.aau.dk/rws/)
• Peer Review: Reviewer for leading computer-vision venues, including NeurIPS and CVPR
• Governance: Member, HPC Governance Board, Pioneer Centre for AI (P1)
• External Examiner: BSc and MSc of Science in Engineering, appointed by the Danish Agency for Higher Education and Science
• Lab: Member, VAP Lab Management, Aalborg University

Invited Talks & Media

• Conference talk (WACV 2026): From Lab to Street: Real-World Super-Resolution for Surveillance Applications — Real-World Surveillance Workshop, Tucson, USA
• Seminar talk (DIREC 2022): Fine-Grained Image Generation with Super-Resolution — Denmark
• TV — TV 2 Danmark (2025): Interview on image enhancement for the documentary Hvem chikanerer Tove?
• TV — TV 2 Nord (2023): Interview on AI education and public interest in AI
• TV — Discovery+/Kanal 5 (2022): Contribution on image analysis, documentary series Forbrydelser der rystede Danmark — Mia-sagen

Technical Toolbox

• Programming: Python, C/C++, Java, Bash
• ML/CV: PyTorch, TensorFlow, OpenCV, SciPy, NumPy, Pandas, Matplotlib
• HPC/DevOps: NVIDIA DGX, Slurm, Singularity, Jenkins, Git, CI/CD, unit tests
• Embedded/Linux: Jetson TX2, STM32/ARM, Embedded Linux, kernel drivers, device trees
• Other: Advanced Linux, Scrum/Agile, Matlab

Languages

Danish (fluent), English (fluent), German (basic)

References

Available upon request.