Welcome

Johan Dahlin is a business-minded PhD passionate about improving the world by using Bayesian data analysis and machine learning.

  • 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

    B.Sc. 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. 

I received my PhD in Automatic Control 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 fields of Computational Statistics and System Identification.

Currently, I am developing automated data-driven algorithms for building dynamical models as a PostDoc at the School of Engineering at the University of Newcastle, Australia.

During my research career, I have worked at a number of different companies and universities. I visited Prof. Robert Kohn at he University of New South Wales,  Australia during the autumn of 2014 as part of his PhD studies. I have also worked as a Research Scientist at Sectra AB and as a PostDoc at the division of Statistics and Machine Learning at Linköping University.

Short CV summary

I am passionate about helping people living better and healthier lives using insights gained from data by employing algorithms from Data science, Machine learning and Artificial intelligence. I believe that learning from data is essential in solving big and challenging problems within e.g., healthcare and medicine by enabling improved data-driven decision making and forecasting.
 
My colleagues know me as a resourceful co-worker who delivers good solutions on time. I enjoy being an entrepreneur who facilitates and delivers solutions focusing on the needs of the customer. I love new challenges, especially when it provides me with an opportunity to grow personally, expand my skill set and/or learn about new application areas. I am passionate about sharing my expertise and experience with others and collaborating with them to achieve great things together.

Summary of my research

My research is situated somewhere in the intersection of Computational statistics and Machine learning. Three common themes are Bayesian modelling (using prior information and quantifying uncertainty), dynamical systems (the behaviour changes over time) and the 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 fields and problems with some common applications are found in the introductory chapter of my PhD thesis. More information about my research is found on the pages liked below.

Some of my skills

Data science & Machine learning

Extensive experience in exploratory data analysis and modelling many different types of data using statistical models. Experience in applying, developing and implementing algorithms from Machine learning including deep learning and reinforcement learning to solve real-world problems.

Programming

Full-stack software development using Python/C /R for computational back-end in the cloud and React for front-end on web or mobile devices.

Problem solving

A PhD education teaches you to quickly learn new things and solving problems such as tailoring/improving algorithms for a new application.

Collaboration and communication

Extensive experience at leading and working in teams in developing technical solutions as well as in sports and other organizations. Extensive experience in teaching, presentation and other forms of communications in both technical and more general settings.

Some of my past projects

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Teaching computers to detect cancer

Breast cancer is one of the most common forms of cancers in women with about two million new cases every year. Early detection is the best approach to improve survival. The successful application of deep learning for processing mammograms would enable more extensive screenings of the population. Such algorithms would help by sifting through the gigabytes of data collected to flag abnormalities that require further analysis by an expert.

Photo: Nevit Dilmen.

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Finding survivors in disaster areas

It is often difficult to coordinate and plan the rescue work after a disaster such as an earthquake or a Tsunami. Statistical models can be a help in these situations by combining information from cameras mounted on UAVs, maps, cell tower information, etc. to create a probability map over an area. This map would tell the rescuers where it is most likely to find survivors after a disaster, so that they might focus their effort and resources to save as many people as possible.

Photo: Mark Dixon.

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Finding alternative medical diagnoses

Electronic health records of patients are usually stored on a central server at hospitals. These are a possible gold-mine of information that is currently large under-utilised. However, Machine learning and Natural language processing methods can be used to extract useful information from these records. This can help medical doctors to make better diagnoses by presenting lists of possible diagnoses given certain test results and symptoms.

Photo: NEC Corporation of America.

Consulting

Would you like help with exploring and analyzing a data set? Would you like to have tailored efficient algorithms for your problem? Would you like to have help with training and education? I can help!

I have many years of practical experience in developing and applying methods from Bayesian statistics, Machine learning and Artificial intelligence both in academia and industry. My PhD education has provided me with a deep understanding of these methods, which is essential when tailoring them to specific problem or training others. I have experience in working with numerical, text, image and network data. Get in touch for more information.

Some current hobby projects

I like to keep busy during my spare time with being outdoors, reading books, running, swimming, weight-lifting, yoga, cooking and socializing. Each year, I decide on some special focus areas and the current ones are listed below.

Swedish circuit

Preparing for 90 km cross-country skiing, 300 km biking on country roads, 30 km running over the hills of Lindingö and 3 km swimming in a river.

Self-improvement

Focusing on meditation, Stoicism and Toastmasters International.

Programming

Developing modern apps with cloud-based back-ends for mobile devices using React.

Playing the guitar

Following the awesome course offered by Justin Guitar to learn to play some Foo Fighters!

Photography

Focusing on landscapes and streets using my Nikon D7200. Have a look.

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.