プロフィール詳細

プロジェクトを作成

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Henrik K.に依頼

Sweden

CTO & AI Scientist | Data efficient deep learning for imaging, medtech, security and manufacturing

プロフィール概要

I am an AI scientist and CTO who builds reliable, data efficient models for imaging and scientific data. I have a PhD in AI and Physics and lead projects from feasibility to deployed systems. My focus is computer vision for microscopy, medical and industrial sensors, with strong attention to reproducibility, speed and low annotation cost. Recent work includes developing next generation imaging models with a global pharmaceutical company, building automated screening tools for a European border and security context, and creating data discovery workflows for materials and life science labs. I also help teams modernize their ML stack, cut training time and move models into production with clear metrics and documentation. Details and references are available under NDA. Core skills: Python, PyTorch, computer vision, self supervised learning, active learning, evaluation design, MLOps and deployment (Docker, CUDA, model serving), vector search, and analytics across microscopy, spectroscopy and time series. I work comfortably in Swedish and English. MSc in AI, BSc in Engineering Physics, PhD in AI and Physics.

専門分野

• ☆ Catalysis
• ☆ Molecular Engineering
• ☆ Microscopy
• ☆ Light Microscopy
• ☆ Electron Microscopy
• ☆ Fluorescence Microscopy
• ☆ Scanning Probe Microscopy
• ☆ Data Collection
• ☆ Applied Mechanics
• ☆ Thermodynamics
• ☆ Quantum Mechanics
• ☆ Computational Physics
• ☆ Applied Physics
• ☆ Information & Knowledge Management
• ☆ Data Storage
• ☆ Python
• ☆ Matlab
• ☆ SQL
• ☆ Excel
• ☆ Java
• ☆ Tensorflow
• ☆ Scikit-learn

サービス

• Writing
• Research
• Consulting
• Data & AI
• Product Development

Writing Technical Writing

Research Market Research, Feasibility Study, Fact Checking, Scientific and Technical Research, Systematic Literature Review

Consulting Go-to-Market Strategy Consulting, Digital Strategy Consulting, Scientific and Technical Consulting

Data & AI Predictive Modeling, Statistical Analysis, Image Processing, Image Analysis, Algorithm Design-Non ML, Algorithm Design-ML, Data Visualization, Big Data Analytics, Text Mining & Analytics, Data Mining, Data Cleaning, Data Processing, Data Insights

Product Development Formulation, Product Evaluation, Product Validation, Quality Assurance & Control (QA/QC), Product Launch Support, Packaging Design, Prototyping

職務経験

CTO & Co-Founder

IFLAI AB

9月 2022 - 現在

PhD student

Chalmers Tekniska Högskola

12月 2020 - 9月 2025

学歴

PhD (Physics)

Chalmers University of Technology

12月 2020 - 11月 2024

Msc (Complex Adaptive Systems)

Chalmers University of Technology

9月 2019 - 9月 2020

BsC (Engineering Physics)

Chalmers University of Technology

9月 2016 - 6月 2019

認定資格

• 認定資格の詳細は未入力です。

出版物

JOURNAL ARTICLE

Henrik Klein Moberg, Giuseppe Abbondanza, Ievgen Nedrygailov, David Albinsson, Joachim Fritzsche, Christoph Langhammer (2025). Deep-learning-enabled online mass spectrometry of the reaction product of a single catalyst nanoparticle . Nature Communications.

Henrik Klein Moberg, Viktor Martvall, Athanasios Theodoridis, David Tomeček, Pernilla Ekborg-Tanner, Sara Nilsson, Giovanni Volpe, Paul Erhart, Christoph Langhammer (2025). Accelerating Plasmonic Hydrogen Sensors for Inert Gas Environments by Transformer-Based Deep Learning . ACS Sensors.

Henrik Klein Moberg, Dana Hassan, Jesús Domínguez, Benjamin Midtvedt, Jesús Pineda, Christoph Langhammer, Giovanni Volpe, Antoni Homs Corbera, Caroline B. Adiels (2024). Cross-modality transformations in biological microscopy enabled by deep learning . Advanced Photonics.

Henrik Klein Moberg, David Tomeček, Sara Nilsson, Athanasios Theodoridis, Iwan Darmadi, Daniel Midtvedt, Giovanni Volpe, Olof Andersson, Christoph Langhammer (2024). Neural network enabled nanoplasmonic hydrogen sensors with 100 ppm limit of detection in humid air . Nature Communications.

Špačková, B., Klein Moberg, H., Fritzsche, J., Tenghamn, J., Sjösten, G., Šípová-Jungová, H., Albinsson, D., Lubart, Q., van Leeuwen, D., Westerlund, F., et al.(2022). Label-free nanofluidic scattering microscopy of size and mass of single diffusing molecules and nanoparticles . Nature Methods. 19. (6). Microsoft.AspNetCore.Mvc.Localization.LocalizedHtmlString 751-758.