I have a deep understanding and experience of using AI for almost two decades both in theory and practice.

My PhD studies gave we a wide and deep understanding of the underpinning of modern AI algorithms. This together with my life long interest in coding and software development gives me a solid foundation for brining your data to life and to get true value from it.

Check out myLinkedIn profileor myresearch pagefor more information.

  • PhD, Artificial Intelligence

    Developed efficient computational methods for Bayesian statistical inference in 16 peer-reviewed publications. Thesis title: Accelerating Monte Carlo methods for Bayesian inference in dynamical models. Two years of postgraduate coursework in statistics, probability theory, machine learning and automatic control.

    Machine LearningBayesian StatisticsMarkov Chain Monte CarloSequential Monte CarloBayesian Optimization

    Read my PhD Thesis

  • Google Cloud Professional Machine Learning Engineer

    A Professional Machine Learning Engineer builds, evaluates, productionizes, and optimizes ML models by using Google Cloud technologies and knowledge of proven models and techniques. The ML Engineer handles large, complex datasets and creates repeatable, reusable code. The ML Engineer considers responsible AI and fairness throughout the ML model development process, and collaborates closely with other job roles to ensure long-term success of ML-based applications.

    Vertex AIAutoMLMLOpsMachine Learning

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  • Google Cloud Professional Data Engineer

    A Professional Data Engineer makes data usable and valuable for others by collecting, transforming, and publishing data. This individual evaluates and selects products and services to meet business and regulatory requirements. A Professional Data Engineer creates and manages robust data processing systems. This includes the ability to design, build, deploy, monitor, maintain, and secure data processing workloads.

    BigTableBigQueryCloud SQLDataflowSparkSQLData GovernanceMachine LearningTensorflow

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I am passionate about helping my customers getting the most out of their data.

These are some projects that I have been working on together with customers and the technologies which were used.

Check out myLinkedIn profilefor more information.

  • Data Architect and Engineer

    Developing a data model and data architecture to harmonize agriculture data from many different sources.

    Data modellingSQL


  • Cloud Developer and Machine Learning Engineer

    Migrated state-of-the-art GenAI solution to Google Cloud to enable production level scale for thousands of users. Implemented best-practice DevOps and MLOps workflows.

    GenAIGoogle CloudFirebaseVertex AIPyTorchTorchServeOryMixpanel


  • Technical Product Owner

    Spearheaded the creation of a new Smart Machines division at Väderstad, focusing on machine connectivity and cloud computing. Responsible for identifying new technologies, planning the product strategy, and delivering the first working prototype of a connected machine. Successfully transitioned the project to an internal product management team.

    Data EngineeringCybersecurityAzureIoT HubCosmos DBPython


  • AI Innovation Engineer

    Developed proof-of-concepts and technological demonstrators that applied computer vision, deep learning, and reinforcement learning to solve problems in agriculture.

    Nvidia JetsonStereo CamerasPythonOpenCVC++scikit-learnxgboost


  • 12-week intensive course in Data Science/AI

    Developed an intensive course in Data Science and AI which is offered to companies who wants to up-skill their employees. Created the course curriculum and assisted in the sales process and recruitment of teachers.

    Course DesignPythonpandasscikit-learnData AnalyticsSQL


  • Machine learning-based search and recommendation system

    Developed a data-efficient and energy-efficient solution for a mobile application where no data leaves the smartphone during either training or prediction.

    Pythonscikit-learnxgboostLearning to RankReact.js
  • Algorithm development for time series prediction

    Algorithm development for estimating statistical models with a focus on computational efficiency.



  • Deep learning solution for screening mammography images

    Developed a state-of-the-art solution based on convolutional neural networks trained on only a small amount of real data for detecting anatomical landmarks.