Kalender

Kalenderhändelser saknas för aktuell period.

Kommande kalenderhändelser:

• Modular and tuneable design space exploration in model-driven engineering of embedded systems

  1 nov

  Disputationer

  Elektro- och systemteknik

  fredag 2024-11-01, 13.00

  Plats: Sal A, Kistagången 16, floor 2, Kista

  Videolänk: https://kth-se.zoom.us/j/61167004728

  Respondent: Rodolfo Jordao , Elektronik och inbyggda system, ForSyDe Group

  2024-11-01T13:00:00.000+01:00 2024-11-01T13:00:00.000+01:00 Modular and tuneable design space exploration in model-driven engineering of embedded systems (Disputationer) Sal A, Kistagången 16, floor 2, Kista (KTH, Stockholm, Sweden)Modular and tuneable design space exploration in model-driven engineering of embedded systems (Disputationer)

• Scalable hardware solutions for machine learning: FPGA implementation and methodology analysis

  16 dec

  Disputationer

  Elektro- och systemteknik

  måndag 2024-12-16, 13.00

  Plats: Kista Sal C, Kistagången 16, 164 40 Kista

  Videolänk: https://kth-se.zoom.us/j/66637479462

  Respondent: Gracieth Batista , Elektronik och inbyggda system, Aeronautics Institute of Technology, São José dos Campos, Brasil

  2024-12-16T13:00:00.000+01:00 2024-12-16T13:00:00.000+01:00 Scalable hardware solutions for machine learning: FPGA implementation and methodology analysis (Disputationer) Kista Sal C, Kistagången 16, 164 40 Kista (KTH, Stockholm, Sweden)Scalable hardware solutions for machine learning: FPGA implementation and methodology analysis (Disputationer)

• Efficient Machine Learning for Edge Computing

  28 mar

  Disputationer

  Informations- och kommunikationsteknik

  fredag 2025-03-28, 13.00

  Plats: Ka-Sal B (Peter Weissglas), Kistagången 16, Kista

  Videolänk: https://kth-se.zoom.us/j/63180568741

  Respondent: Wenyao Zhu , Elektronik och inbyggda system

  2025-03-28T13:00:00.000+01:00 2025-03-28T13:00:00.000+01:00 Efficient Machine Learning for Edge Computing (Disputationer) Ka-Sal B (Peter Weissglas), Kistagången 16, Kista (KTH, Stockholm, Sweden)Efficient Machine Learning for Edge Computing (Disputationer)