Calendar
Mon 04 October
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Public defences of doctoral theses
Electrical Engineering
Monday 2021-10-04, 10:00
Doctoral student: Fabian Hohn , Elkraftteknik
2021-10-04T10:00:00.000+02:00 2021-10-04T10:00:00.000+02:00 Distributed Signal Processing in Digital Substations (Public defences of doctoral theses) Kollegiesalen Zoom: https://kth-se.zoom.us/j/61033307653?pwd=ZFc0anNrWi8yamVYZzdpK1p2NzY3UT09, Brinellvägen 8, Stockholm (English) (KTH, Stockholm, Sweden)Distributed Signal Processing in Digital Substations (Public defences of doctoral theses) -
Public defences of doctoral theses
Physics Theoretical Physics
Monday 2021-10-04, 11:45
Location: FP21 och via Zoom, Roslagstullsbacken 33, Stockholm (English)
Doctoral student: Filipp N. Rybakov , Fysik
2021-10-04T11:45:00.000+02:00 2021-10-04T11:45:00.000+02:00 Topological excitations in field theory models of superconductivity and magnetism (Public defences of doctoral theses) FP21 och via Zoom, Roslagstullsbacken 33, Stockholm (English) (KTH, Stockholm, Sweden)Topological excitations in field theory models of superconductivity and magnetism (Public defences of doctoral theses) -
Workshop and drop-in with E-learning
Monday 2021-10-04, 13:00 - 15:00
Participating: E-learning
Location: Zoom
2021-10-04T13:00:00.000+02:00 2021-10-04T15:00:00.000+02:00 Drop-in support by E-learning (4/10) (Workshop and drop-in with E-learning) Zoom (KTH, Stockholm, Sweden)Drop-in support by E-learning (4/10) (Workshop and drop-in with E-learning) -
Public defences of doctoral theses
Information and Communication Technology
Monday 2021-10-04, 14:00
Doctoral student: Zainab Abbas , Programvaruteknik och datorsystem, SCS
2021-10-04T14:00:00.000+02:00 2021-10-04T14:00:00.000+02:00 Scalable Streaming Graph and Time Series Analysis Using Partitioning and Machine Learning (Public defences of doctoral theses) https://kth-se.zoom.us/meeting/register/u5Uof-2gqzsvGNdRddTW4DKuhwT5hwiqKPUo, Sal C Electrum, Kistagången 16, Stockholm (English) (KTH, Stockholm, Sweden)Scalable Streaming Graph and Time Series Analysis Using Partitioning and Machine Learning (Public defences of doctoral theses)