AISRS22 workshop schedule (poster information below talk schedule)

All times US EST

(The talks are not sorted by science domain, in order to promote interdisciplinarity.)

Wednesday February 23					Session Chair
10:00-10:10 am	Scott Dodelson	Carnegie Mellon University	In person	Welcome	Pedram Hassanzadeh
10:10-10:40 am	Brant Robertson	UC Santa Cruz	Probably remote	To Train or To Test?: Physical Simulation vs. Emulation
10:40-11:10am	Claire Monteleoni	University of Colorado Boulder	Probably remote	Deep Unsupervised Learning for Climate Informatics
11:10-11:30am	break
11:30am-12:00pm	Pratyush Tiwary	University of Maryland	Remote	From data to noise to data: mixing physics across temperatures with denoising diffusion probabilistic models	Yueying Ni
12:00pm-12:30pm	Amir Barati Farimani	Carnegie Mellon University	In person	Temporal Point cloud Upsampling GAN (TPU-GAN)	Yueying Ni
12:30-2:00pm	lunch - provided in Connan Room on ground floor
2:00-2:20pm	Francisco Villaescusa-Navarro	Simons Foundation	In person	The role of super-resolution on cosmology and astrophysics	Ben Moews
2:20-2:40pm	Karen Stengel	University of Colorado Boulder	Remote	Super Resolution of Climatological Data with Generative Adversarial Networks
2:40-3:00pm	Shady Ahmed	Oklahoma State University	In person	Towards physics-aware model reduction and data compression
3:00-4:00pm	Break and poster session
4:00-4:20pm	Kai Fukami	University of California, Los Angeles	In person	Reconstructing turbulent flows with machine-learning-based super-resolution analysis	Amir Barati Farimani
4:20-4:40pm	Catherine Bouchard	Université Laval	remote	Super-resolution with GANs : shifting the focus from realism to content-preservation
4:40-5:00pm	Dorit Hammerling	Colorado School of Mines	remote	Nonstationary Spatial Modeling of Massive Global Satellite Data

Thursday February 24					Session Chair
10:00-10:20am	Yin Li	Flatiron Institute	In person	Differentiable cosmological simulation with adjoint method	Francisco Villaescusa-Navarro
10:20-10:40am	Andrew Geiss	Pacific Northwest National Laboratory	Remote	Enforcing Strict Adherence to Conservation Laws in CNN-Based Super-Resolution
10:40-11:00am	Mahdi Pourbagian	K. N. Toosi University of Technology, Iran	Remote	Super-resolution of low-fidelity flow solutions via generative adversarial networks
11:00-11:30am	break
11:30-11:50am	Tom Beucler	University of Lausanne (Switzerland)	Remote	Atmospheric Physics-Guided Machine Learning	Yin Li
11:50-12:10pm	Luzhe Huang	University of California, Los Angeles	Remote	Deep learning-enabled cross-modality super-resolution in optical microscopy
12:10-12:30pm	Biwei Dai	UC Berkeley	In person	Learning effective physical laws for generating cosmological hydrodynamics with Lagrangian Deep Learning
12:30-2:00pm	lunch - provided in Connan Room on ground floor
2:00pm-2:20pm	Pedram Hassanzadeh	Rice University	In person	Improving the representation of subgrid-scale processes in climate models using AI	Mathis Bode
2:20pm-2:40pm	Yuki Yasuda	Tokyo Institute of Technology	Remote	Roto-Translation Equivariant Super-Resolution of Two-Dimensional Fluids Using Convolutional Neural Networks
2:40pm-3:00pm	Tommaso Grassi	Max Planck Institute for Extraterrestrial Physics	Remote	Reducing the complexity of chemical networks via interpretable autoencoders
3:00pm-3:30pm	break
3:30pm-4:00pm	Atılım Güneş Baydin	University of Oxford	In person	Simulation-based Inference and Inverse Problems in Physical Sciences
4:00pm-5:00pm	Social interaction session

Friday February 25					Session Chair
10:00-10:20am	Mathis Bode	RWTH Aachen University	In person	PIESRGAN and CIAO: A super-resolution based subfilter modeling framework for turbulence and combustion	Tiziana Di Matteo
10:20-10:40am	Ryo Onishi	Tokyo Institute of Technology	Remote	Super-resolution simulation of urban micrometeorology for sustainable future society
10:40-11:00am	Rob McGibbon	University of Edinburgh	Remote	Adding complex astrophysics to simple simulations
11:00-11:30am	break
11:30-11:50am	Yueying Ni	Carnegie Mellon University	In person	Super-resolution cosmological simulations	Rupert Croft
11:50am-12:10pm	Jian-Xun Wang	University of Notre Dame	Remote	Physics-informed Deep Learning for Fluid Super-Resolution and Parametric Inversion
12:10-12:30pm	Yingkai Sha	University of British Columbia	Remote	Deep-learning-based gridded downscaling of daily precipitation in British Columbia
12:30pm-	lunch - provided in Connan Room on ground floor

AISRS22 virtual posters

The official poster session will be Wednesday Feb 23 from 3-4pm EST, but the posters will be available during all breaks.

Instructions: The poster session (and social breaks for those not in person) will be virtual and hosted on the Spatial platform. To get started, please go to https://spatial.io/ to create an account and get your face scanned. The link for the virtual poster session venue was given in the conference emails sent to registered participants. If you are presenting a poster, please upload it to one (or more) of the picture frames in the virtual gallery that is accessed by clicking on the link in the emails.

There is room for more posters, even if you didn’t upload a title or abstract by the registration deadline. If you would like to upload a poster please follow the instructions above to do so and your poster will be manually added to the list below.

Poster titles submitted by registration deadline:

Name	Institution	Title (click to view abstract)
Peter Harrington	Lawrence Berkeley National Laboratory	Physically-motivated analogs to super-resolution in multi-physics cosmological simulations
Roi Kugel	Leiden University	Calibrating sub-resolution models with Gaussian process machine learning
Meris Sipp and Patrick Lachance	Carnegie Mellon University	Using Super Resolution to Analyze Fuzzy Dark Matter Models in Cosmological Simulations
Thomas Chen	Academy for Mathematics, Science and Engineering	Climate Adaptation and Disaster Assessment using Deep Learning and Earth Observation
Xiaowen Zhang	Carnegie Mellon University	Generalizing cosmological super-resolution with StyleGAN