PhD Student at
CVAP,
CAS,
CSC -
KTH Royal Institute of Technology
Room 609, Teknikringen 14, 114 28 Stockholm, Sweden
Phone: +46 8 790 7224
Email: martinhjelm -- k t h . se
Blog: The NonConditional Beast
Github: github.com/MartinHjelm
Google Scholar: scholar.google.com
Curriculum vitae(CV): CV(pdf)
Im a PhD student at CVAP, CSC - KTH Royal Institute of Technology. My main research interest are machine learning, computer vision and robotics; especially non-linear dimensionality reduction and clustering. I also dabbled in segmentation, sampling-methods, Gaussian Processes, variational Bayes, mixture models etc. I have started a blog on machine learning related topics: The NonConditional Beast
Other interests are robot making with Arduino, competing at Kaggle, learning to play as many instruments as possible, anthropology, architecture, food, long distance running, the Arts. The list could go on for a while. I also do a lot of web-programming like most programming literate person I like startups. I created and designed Bookle, a site for selling second hand course literature and I have done several other web projects as a consultant and by myself.
M. Hjelm, R. Detry, C. H. Ek and D. Kragic, In IEEE International Conference on Robotics and Automation, 2014.
bib :: pdf
M. Hjelm, C. H. Ek, R. Detry, H. Kjellstrom and D. Kragic, In IEEE International Conference on Robotics and Automation, 2013.
bib :: pdf
Currently I am or have done TA:ing on DD1346 Object-Oriented Program Construction, on DD2427 Image Based Recognition and Classification and various first year Calculus classes.
I did my Master Thesis on image segmentation at TTI(Toyota Technological Institute) in Chicago under supervision of Raquel Urtasun. Prior to that I was at TU Berlin studying machine learning courses under professor Mannfred Opper and professor Klaus-Robert Muller. I did my undergrad studies and part of my master studies at KTH, at the Engineering Physics section focusing on numerical methods for differential equations.
You can find all my code on GitHub. So far there is some Machine Learning Algorithms that I at various times could not find in Matlab. And NAMT(Not Another Matlab Toolbox) some Matlab helper files that does the stuff you always wanted in Matlab like cascading all your plot windows, putting out a machine beep when your algorithm finishes running, etc. I recently put out some code for capturing Kinect images on keypresses called Kinect-Cap it also contains a small pcd viewer.
It's all in the fractals!
