Welcome

 

Business-minded PhD passionate about data, algorithms and improving the world.

Welcome

 

Business-minded PhD passionate about data, algorithms and improving the world.

  • 2016

    PhD Automatic Control

    Linköping University, Sweden.
    Includes two years of coursework in Engineering, Machine Learning and Statistics.

  • 2011

    MSc Engineering Physics

    Umeå University, Sweden.
    Majors in Risk Management and Industrial Statistics.

  • 2011

    BSc Economics

    Umeå University, Sweden.
    Includes coursework in Marketing, Project Management and Law.

Who am I?

I began life in Enköping, Sweden in 1986. As a young boy, I quickly found an interest in Mathematics and Computer Science, which led me to study Engineering and then to pursue a PhD based on research and coursework.

Research

I received my PhD degree in May 2016 after successfully defending my thesis which contained a total of 17 peer-reviewed papers (13 conference papers and 3 journal papers) published at top conferences and journals in the field. During and after my PhD studies, I have spent time as a visiting academic at the University of New South Wales,  Australia and have been a PostDoc at the division of Signals and Systems at Uppsala University, the division of Statistics and Machine Learning at Linköping University as well as at the School of Engineering at the University of Newcastle, Australia.I have also worked as a Research Scientist at Sectra AB.

Today

I am currently an entrepreneur with my own consultancy company Kotte Consulting which helps out in Artificial Intelligence (AI), Machine learning (ML) and Data Science as well as co-founder in AgriOpt, a startup aiming to revolutionize agriculture with AI.

Who am I?

I began life in Enköping, Sweden in 1986. As a young boy, I quickly found an interest in Mathematics and Computer Science, which led me to study Engineering and then to pursue a PhD based on research and coursework.

Research

I received my PhD degree in May 2016 after successfully defending my thesis which contained a total of 17 peer-reviewed papers (13 conference papers and 3 journal papers) published at top conferences and journals in the field. During and after my PhD studies, I have spent time as a visiting academic at the University of New South Wales,  Australia and have been a PostDoc at the division of Signals and Systems at Uppsala University, the division of Statistics and Machine Learning at Linköping University as well as at the School of Engineering at the University of Newcastle, Australia.I have also worked as a Research Scientist at Sectra AB.

Today

I am currently an entrepreneur with my own consultancy company Kotte Consulting which helps out in Artificial Intelligence (AI), Machine learning (ML) and Data Science as well as co-founder in AgriOpt, a startup aiming to revolutionize agriculture with AI.

  • 2016

    PhD Automatic Control

    Linköping University, Sweden.
    Includes two years of coursework in Engineering, Machine Learning and Statistics.

  • 2011

    MSc Engineering Physics

    Umeå University, Sweden.
    Majors in Risk Management and Industrial Statistics.

  • 2011

    BSc Economics

    Umeå University, Sweden.
    Includes coursework in Marketing, Project Management and Law.

My research

My research is situated somewhere between Computational statistics and Machine learning. Three common themes are:

  • Bayesian inference: using prior information and quantifying uncertainty,
  • Dynamical systems: the behaviour changes over time,
  • Acceleration of methods: decreasing the computational time to get the answer.

I usually work with methods such as:

  • Monte Carlo methods (particle filtering, sequential Monte Carlo and Markov chain Monte Carlo),
  • Gaussian/Dirichlet processes and
  • Mixture models.

A quite general introduction to these themes and methods is found in the introductory chapter of my PhD thesis.

My research

My research is situated somewhere between Computational statistics and Machine learning. Three common themes are:

  • Bayesian inference: using prior information and quantifying uncertainty,
  • Dynamical systems: the behaviour changes over time,
  • Acceleration of methods: decreasing the computational time to get the answer.

I usually work with methods such as:

  • Monte Carlo methods (particle filtering, sequential Monte Carlo and Markov chain Monte Carlo),
  • Gaussian/Dirichlet processes and
  • Mixture models.

A quite general introduction to these themes and methods is found in the introductory chapter of my PhD thesis.

Would you like to know more?

I love to connect with new people for networking and to share experiences and idea. Therefore, do not hesitate to get in touch with me if you have any questions connected to my research, the source code on GitHub or if you would like to discuss a business idea or hire me for a job.