With the success of Machine Learning (ML) in computer vision, natural language processing, autonomous vehicles, and many other disciplines, it is not surprising to witness its popularity within the computational science and engineering community. Both conventional machine learning and the state of the art deep learning methods have proven effective in transport phenomena, and it is expected that the rate of progress would be even faster in the near future.
The objective of this workshop is to assess the state of progress in development, implementation and application of ML in transport phenomena. Of particular interest are applications in fluid dynamics, including turbulence, heat & mass transfer, multi-phase flows, biological transport, combustion and other reactive flows. Considering the complexity of such phenomena, the question is to what to expect from ML and to what extend such learnings can assist in modeling and inference of transport phenomena.
Distinguished scholars with expertise in both machine learning and transport phenomena are invited to discuss their recent results, and to identify the paths to be taken in future to merge ML into transport modeling. Audience participation in daily panel discussions is encouraged, and poster presentations are welcome.
|Michael Brenner||Harvard University|
|Steven Brunton||University of Washington||Please click here to download presentation|
|Kevin Carlberg||University of Washington||Please click here to download presentation|
|Sharath Girimaji||Texas A&M University||Please click here to download presentation|
|Gianluca Iaccarino||Stanford University||Please click here to download presentation|
|George Karniadakis||Brown University||Please click here to download presentation|
|Michael Mahoney||University of California, Berkeley||Please click here to download presentation|
|Mujeeb Malik||NASA Langley Research Center||Please click here to download presentation|
|Zhuyin(Linau) Ren||Tsinghua University||Please click here to download presentation|
|Justin Sirignano||University of Illinois at Urbana-Champaign||Please click here to download presentation|
|Karen Willcox||University of Texas at Austin||Please click here to download presentation|
Dallas is served by two airports. The nearest one to SMU is Dallas Love Field (DAL), which is 4 miles to the SMU Campus with an approximate drive time of 20 minutes. DAL is a smaller airport, which mainly serves Southwest Airlines in addition to Delta Airlines. The second airport is Dallas-Fort Worth International Airport (DFW) which is about 23 miles from the hotel, with an approximate drive time of 40 minutes. DFW is a hub for American Airlines and serves almost all major airlines in the US.
We will have technical presentations, with subsequent publication of the workshop proceedings.
Registration Closed. We are at the Capacity Limit.
The workshop will be held at Martha Proctor Mack Ballroom, located on the third floor of the Umphrey Lee Center at 3300 Dyer Street, Dallas, TX in Southern Methodist University.
The following hotels are within waking distances from the Umphrey Lee Center, and are recommended: