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research [2017/10/19 17:46]
Joos Buijs
research [2017/10/23 07:29] (current)
Joos Buijs
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 I'm currently supervising 2 PhDs as daily supervisor: I'm currently supervising 2 PhDs as daily supervisor:
  
-1. **Bart Hompes**: Bart is looking into tackling process complexity found in healthcare processes by not considering ​the process. Bart for instance developed a trace clustering technique that clusters similar ​traces ​together. ​Key feature here is that the number of clusters does not need to be specified beforehand and that the clusters can be unbalanced. Bart also developed a technique to find relations between ​a context ​(e.g. 'when Joos executes activity repair...') and a performance measure ​(e.g. 'case duration'). Currently Bart is working on verifying SLAs on event logs. +1. **Bart Hompes**: Bart is looking into tackling process complexity found in healthcare processes by not considering process ​models as a necessity. Bart for instance developed a trace clustering technique that clusters similar ​cases together. ​The key feature here is that the number of clusters does not need to be specified beforehand and that the clusters can be unbalanced. Bart also developed a technique to find relations between ​performance measures ​(e.g. 'case duration') and context ​(e.g. 'when Joos executes activity repair'). Currently Bart is working on verifying SLAs on event logs.
  
 2. **Alok Dixit**: Alok is tackling process complexity by making process discovery semi-supervised. By assisting the user in building a (sound) process model, the user's knowledge is combined with data observations. Alok demonstrated that this approach is very powerful by winning the [[https://​www.win.tue.nl/​ieeetfpm/​doku.php?​id=shared:​process_discovery_contest|BPI 2017 Discovery contest]]. Currently Alok is working on speeding up process-event log alignment calculations,​ using domain knowledge to fix data issues in the event log, and of course on improving his interactive user interface. 2. **Alok Dixit**: Alok is tackling process complexity by making process discovery semi-supervised. By assisting the user in building a (sound) process model, the user's knowledge is combined with data observations. Alok demonstrated that this approach is very powerful by winning the [[https://​www.win.tue.nl/​ieeetfpm/​doku.php?​id=shared:​process_discovery_contest|BPI 2017 Discovery contest]]. Currently Alok is working on speeding up process-event log alignment calculations,​ using domain knowledge to fix data issues in the event log, and of course on improving his interactive user interface.