Summary
Machine learning researcher and practitioner with academic project experience: Carl completed undergraduate and graduate ML projects and reports (including an unsupervised anomaly-detection project and a GP-LVM implementation), and completed a master's thesis during his Machine Learning studies at KTH. uppsatser+2
Startup founder focused on applying AI to ecommerce product data: as a co-founder and Head of AI at Emfas, Carl works on an AI-native PIM that automates product-catalog workflows, enriches and localizes product data, and integrates with ecommerce platforms to streamline merchant onboarding. emfas+1
Experienced backend/software engineer transitioning from product engineering to leadership: Carl held backend and software engineering roles at Hedvig and Pedago Labs and worked as a software developer at THS Consulting before co-founding Emfas. theorg+1
Practitioner with a blend of academic collaboration and course-based project work: Carl participated in exchange coursework and project work at EPFL's Applied Data Analysis course and contributed to collaborative GitHub projects and course repositories. github+1
Work
Education
Projects
Writing
Classification of Transcribed Voice Recordings : Determining the Claim Type of Recordings Submitted by Swedish Insurance Clients
January 1, 2021Master's thesis work on building and comparing text classification models (e.g., BERT, LSTM) for transcribed voice recordings to determine claim types.
Gaussian Process Latent Variable Models for Dimensionality Reduction (project report)
January 1, 2020Project report detailing implementation and evaluation of GP-LVM for dimensionality reduction, co-authored with collaborators.
Unsupervised anomaly detection in time series with recurrent neural networks
January 1, 2019A project/report on using neural-network-based methods for unsupervised anomaly detection in time series data; co-authored work demonstrating approaches and experiments.