Scheduled presentations:

• Learning Turbulence Models from Data: A Unified Perspective of Data Assimilation and Machine Learning
  X. Zhang (Chinese Academy of Sciences), *H. Xiao (University of Stuttgart), X. Luo (Norwegian Research Centre (NORCE))
• Student Adaptive Correction of a RANS Model for Separated Flow Fields
  *S. Heo (Gwangju Institute of Science and Technology), Y. Yun (Gwangju Institute of Science and Technology), M. Jeong (Gwangju Institute of Science and Technology), S. Jee (Gwangju Institute of Science and Technology)
• Student Reynolds Stress Anisotropy Tensor Predictions using Neural Networks
  *J. Cai (CEA Saclay, Paris-Saclay University), P. Angeli (CEA Saclay, Paris-Saclay University), J. Martinez (CEA Saclay, Paris-Saclay University), G. Damblin (CEA Saclay, Paris-Saclay University ), D. Lucor (CNRS-LISN)
• Student Assessment of a Data-Driven RANS Model for Various Separated Flows
  *Y. Yun (Gwangju Institute of Science and Technology), S. Heo (Gwangju Institute of Science and Technology), M. Jeong (Gwangju Institute of Science and Technology), S. Jee (Gwangju Institute of Science and Technology)
• Active flow control on 2D wings and separation in boundary layers through deep reinforcement learning
  *F. Alcántara-Ávila (FLOW, KTH Royal Institute of Technology), P. Suárez (FLOW, KTH Royal Institute of Technology), A. Miró (Barcelona Super Computing Center), J. Rabault (Norwegian Meteorological Institute), B. Font (Barcelona Super Computing Center), O. Lehmkhul (Barcelona Super Computing Center), R. Vinuesa (FLOW, KTH Royal Institute of Technology)