Big Data Application Experts

Chalmers has recruited a pool of data experts who can support research projects across all of the areas of advance.
 
Contact Pär Strand for more information.
 
 
Oscar Ivarsson
Oscar works as a Research Engineer within the Big Data initiative at Chalmers. He received his M.Sc in Computer Science and Technology from Linköping University in 2015 and has since been at Chalmers.
 
In his role, he supports research projects in various domains by utilizing the broad spectrum of Big Data related technologies such as machine learning, visual analytics, data processing and storage solutions. His key competence is in developing tools and applications around these technologies to offer ways of gaining more knowledge from the large and complex datasets often used within research today.

Vilhelm Verendel
Vilhelm works with big data and machine learning in several research projects connected to the big data group. Vilhelm has a PhD in complex systems (2016) based on simulation and mathematical modeling. His technical background includes 15+ years experience in system administration, network and system programming. Currently he is focused on applying machine learning methods in several research projects.

Two current project are: Using large online datasets to predict traffic flows and congestion in 26 cities around the worlds, and using 30 years of wind data from NASA to study feasibility of wind power around the globe.

 
Muhammad Azam Sheikh

Azam enjoys his position as a Research Engineer within the Big Data initiative at Chalmers. Azam owns a PhD in Algorithms (2013) from Chalmers University. He has 10+ years of research and development experience within the domain of algorithms, machine learning and applied artificial intelligence.

In his present role, Azam is applying combinations of big data related technologies and combinatorial approaches to a variety of research projects for data analysis, visualization and prediction tasks.





 
 

 
 
 
 
 
 

Published: Wed 16 Sep 2015. Modified: Wed 16 Aug 2017