Humboldt-Universität zu Berlin - Mathematisch-Naturwissenschaftliche Fakultät - Institut für Informatik

Vergangene Termine

  • 2023-07-12T15:00:00+02:00
  • 2023-07-12T23:59:59+02:00
  • RUD25 Humboldt-Kabinett
Juli 12 Mittwoch 2023

Zeit: 15:00

RUD25 Humboldt-Kabinett

Hybrid Methods for the Analysis and Synthesis of Human Faces

  • 2023-07-10T17:00:00+02:00
  • 2023-07-10T23:59:59+02:00
  • RUD25 HU-Kabinett 3.116
Juli 10 Montag 2023

Zeit: 17:00

RUD25 HU-Kabinett 3.116

"Zirkus Empathico 2.0: A Serious Game to Foster Emotional and Collaborative Skills in Children with Autism Spectrum Disorder (ASD)"

  • 2023-07-04T13:15:00+02:00
  • 2023-07-04T23:59:59+02:00
  • zoom: https://hu-berlin.zoom.us/j/67094983031?pwd=bVhYVldzZXJkT0dlWC9QZ3ZXRnp1QT09
Juli 4 Dienstag 2023

Zeit: 13:15

zoom: https://hu-berlin.zoom.us/j/67094983031?pwd=bVhYVldzZXJkT0dlWC9QZ3ZXRnp1QT09

“Multimodal Learning Companions”

  • 2023-06-30T14:00:00+02:00
  • 2023-06-30T23:59:59+02:00
  • RUD25 Humboldt-Kabinett; online Zoom
Juni 30 Freitag 2023

Zeit: 14:00

RUD25 Humboldt-Kabinett; online Zoom

Anonymization Techniques for Privacy-preserving Process Mining

  • 2023-06-28T13:00:00+02:00
  • 2023-06-28T23:59:59+02:00
  • RUD25 Humboldt-Kabinett
Juni 28 Mittwoch 2023

Zeit: 13:00

RUD25 Humboldt-Kabinett

Process Mining Applications in Manufacturing: Case Studies in South Korea

  • 2023-06-16T13:00:00+02:00
  • 2023-06-16T23:59:59+02:00
  • RUD 25, Raum 3.328
Juni 16 Freitag 2023

Zeit: 13:00

RUD 25, Raum 3.328

"Data Structures and Algorithmic Building Blocks for Dynamic Hypersparse Graphs"

  • 2023-06-13T14:00:00+02:00
  • 2023-06-13T23:59:59+02:00
  • Zoom
Juni 13 Dienstag 2023

Zeit: 14:00

Zoom

"Vergleich von Methoden zur Erhebung von mentalen Modellen von Internetsicherheit"

  • 2023-06-09T13:00:00+02:00
  • 2023-06-09T23:59:59+02:00
  • Humboldt-Kabinett, Adlershof
Juni 9 Freitag 2023

Zeit: 13:00

Humboldt-Kabinett, Adlershof

Phillip Wenig: "Anomaly Analysis on Very Large Time Series" Sebastian Schmidl: "AutoTSAD: Unsupervised Holistic Anomaly Detection for Time Series Data"