Love Nordling
PhD In Biomedical Image Analysis at Uppsala universitet
Uppsala, Sweden
Summary
👤
Senior🎓
Top SchoolLove Nordling is a PhD candidate in biomedical image analysis at Uppsala University with eight years of experience building machine learning and computer vision solutions for scientific and industrial applications. Their work focuses on developing computational tools to analyze multidimensional cancer tissue images to optimize immunotherapy, combining deep learning research with practical system integration from prior roles at Unibap and GE Healthcare. Trained in image analysis, machine learning, computer science and physics, they bridge strong analytical foundations with hands-on software engineering—automating large data transformations and XML processing early in their career. Comfortable teaching and mentoring, they have also led introductory data courses and tutored mathematics and physics, demonstrating clear communication of complex topics. A detail that sets them apart is a track record of creating automation (macroscripts and Python tools) to replace manual workflows, accelerating data-driven research and production tasks.
8 years of coding experience
1 year of employment as a software developer
Exchange Studies, Computer Science, Exchange Studies, Computer Science at Nanyang Technological UniversityMaster's Programme in Image Analysis and Machine Learning, Master's Programme in Image Analysis and Machine Learning at Uppsala universitetNaturvetenskapsprogrammet, Naturvetenskapsprogrammet at Katedralskolan
Github Skills (18)
representation-learning8
image-registration7
deep-learning6
tensorflow6
multimodal-deep-learning5
python3
java2
multi-task-learning2
data-science2
matplotlib2
visualization2
data-visualization2
classification1
pytorch1
computer-vision1
Programming languages (2)
Github contributions (5)
LoveNordling/garbage-collector
Dec 2017 - Feb 2018
Contributions:65 commits in 1 month
MIDA-group/CoMIR_INSPIRE
Nov 2022 - Aug 2024
Framework for Multimodal Deformable Image Registration. Coordinated equivariant representation learning (CoMIR) combined with robust deformable registration by INSPIRE.
Contributions:2 PRs, 6 pushes, 1 branch in 1 year 9 months
image-registrationmultimodal-deep-learningrepresentation-learning
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