Profile Details

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Hire Henrik K.

Sweden

USD 200 /hr

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

Profile Summary

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.

Subject Matter Expertise

• ☆ 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

Services

• 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

Work Experience

CTO & Co-Founder

IFLAI AB

September 2022 - Present

PhD student

Chalmers Tekniska Högskola

December 2020 - September 2025

Education

PhD (Physics)

Chalmers University of Technology

December 2020 - November 2024

Msc (Complex Adaptive Systems)

Chalmers University of Technology

September 2019 - September 2020

BsC (Engineering Physics)

Chalmers University of Technology

September 2016 - June 2019

Certifications

• Certification details not provided.

Publications

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). p. 751-758.