Hello There!



Email: martinhjelm -- k t h . se
Blog: The NonConditional Beast
Github: github.com/MartinHjelm
Github Blog: martinhjelm.github.io
Publications: scholar.google.com
Stack Overflow: stackoverflow.com
LinkedIn: linkedin.com/in/martin-hjelm

About Me

I'm a Ph.D. student at KTH Royal Institute of Technology in Computer Science in the RPL Lab. My main research interests are robotics, machine learning, and computer vision. Specifically, my main research focus is on robotic grasping - learning robots to recognize patterns in categories of everyday objects that can be exploited to perform more efficient grasps of the objects that belong to the category.

Before being in Academia I was a master student in Engineering Physics. I did my Master Thesis on image segmentation at TTI (Toyota Technological Institute) in Chicago under the supervision of Raquel Urtasun. Prior to that, I was at TU Berlin studying machine learning courses under professor Manfred Opper and professor Klaus-Robert Muller.

And before my engineering studies, at the dawn of time, I was juggling music studies with being a web design freelancer doing stuff like Bookle.

My free time nowadays is mostly focused on the within academia common pursuit of long distance running and triathlon. Trying to get that Marathon time under 3hrs!


(Videos best viewed at 1.5 speed!)

Learning Human Priors for Task-Constrained Grasping

M. Hjelm, C. H. Ek, R. Detry, and D. Kragic, In 10th International Conference Computer Vision Systems, ICVS, 2015.

Representations for Cross-task, Cross-object Grasp Transfer

M. Hjelm, R. Detry, C. H. Ek and D. Kragic, In IEEE International Conference on Robotics and Automation, 2014.

Sparse Summarization of Robotic Grasping Data

M. Hjelm, C. H. Ek, R. Detry, H. Kjellstrom and D. Kragic, In IEEE International Conference on Robotics and Automation, 2013.

Teaching TA Experience

DD2431 Machine Learning
DD2423 Image Analysis and Computer Vision
DD1346 Object-Oriented Program Construction
DD2427 Image Based Recognition and Classification


You can find the code for my various projects at GitHub.