Mark Cheung

I am searching for postdocs interested in developing a deeper scientific understanding of any aspect of AI and using this understanding to improve AI systems. If interested please email me materials by Jan 10th 2026: a CV, 3 letters of reference, and a statement of research interests (can be short, just indicating what you would like to work on). The positions are generously funded by grants from @schmidtsciences and @SimonsFdn. You will have the opportunity to collaborate with many labs across @StanfordHAI and also the Simons Collaboration on the Physics of Learning and Neural Computation (physicsoflearning.org).

This is a fantastic review. We are entering an era of discovering rare cosmic phenomena. cambridge.org/core/journals/…

Today, we’re showing off our favorite pictures of culpeo foxes we’ve spotted around Cerro Pachón, home of NSF–DOE Rubin Observatory. 🦊 📸 💡Fun fact: While these little guys look like foxes (and are called foxes), they’re actually more closely related to wolves and jackals!

🚀We’re looking for 2026 interns at @PolymathicAI (NYC)! Want to work on scientific foundation models + ML for physics, biology, astronomy, & more? Want to contribute to frontier research with a brilliant, fun, and friendly team? Please sign up on our interest form 👉 forms.gle/hxXPCv3qssEkEQ… #Hiring #Internship #MachineLearning

SPICE -- modelling synthetic spectra of stars with non-homogeneous surfaces. arxiv.org/abs/2511.10998

Susumu Kitagawa, Richard Robson and Omar M. Yaghi have been awarded the 2025 #NobelPrize in Chemistry for the development of a new type of molecular architecture. In 1989, chemistry laureate Richard Robson tested utilising the inherent properties of atoms in a new way. He combined positively charged copper ions with a four-armed molecule; this had a chemical group that was attracted to copper ions at the end of each arm. When they were combined, they bonded to form a well-ordered, spacious crystal. It was like a diamond filled with innumerable cavities.

Thanks to everyone who came to our Australia Telescope Users Committee open meeting today!

Registrations are now open for our next Australia Telescope User Committee meeting (ATUC). ATUC is a chance to discuss issues that impact users of the ATNF. 16 September, online and in-person in Sydney. Register: forms.office.com/r/hdP8QspixN

⚠️ Tsunami Warning: Japan’s East Coast A powerful magnitude 8.7 earthquake struck off the Russian coast, north of Hokkaido, this morning. Tsunami waves are now moving south across the Pacific and may impact Japan’s eastern coastline. If you’re in the affected regions, stay away from the sea. Follow official evacuation advice for your safety.

BREAKING: The state of Hawaii is now under a Tsunami Warning. Here's the latest:

TSUNAMI WARNING 3: See tsunami.gov for alert areas.  M8.7 080mi SE Petropavlovsk, Kamchatka 1625PDT Jul 29:

Air travel fuels ~$400B of U.S. GDP, but space weather like solar flares & winds can disrupt navigation, comms, & passenger safety. @NWSSWPC tracks the Sun’s activity and provides warnings and predictions in real-time, helping the United States’ 700,000 pilots make the most informed decisions in the air. Learn more at swpc.noaa.gov/communities/av… #SpaceWeather #Aviation

The Academy’s new 10-year plan for astronomy is being launched today in Adelaide at the annual meeting of Australia’s astronomers. Read more: science.org.au/news-and-event…

The @AstroSocAus honours six astronomers at its Annual Scientific Meeting in Adelaide this week, including our Dr Joshua Preston Pritchard - winner of the Emerging Leaders in Astronomy Software Development Prize. Read about all the winners: scienceinpublic.com.au/media-releases…

Can AI help solve Millennium Math problem in Fluid dynamics? We take an important step in this direction in our recent paper with physics-informed learning: High-Precision PINNs in Unbounded Domains: Application to Singularity Formulation in PDEs We develop a modular and a robust framework for training Physics-Informed Neural Networks (PINNs) to high precision on unbounded domains. This is a key step toward using AI in rigorous PDE analysis and computer-assisted proofs of singularities. Highlights: 1. Enforcing far-field asymptotics and non-degeneracy via hard constraints Leveraging self-scaled BFGS optimizers for stable convergence. 2. Achieving 4-digit improvement over state-of-the-art for 2D Boussinesq with fewer training steps. 3. Applicable to both smooth and non-smooth self-similar blowup profiles We believe this is a significant step toward integrating machine learning into the toolbox for tackling open problems in fluid dynamics and singularity formation (e.g. Navier-Stokes). arxiv.org/abs/2506.19243 @Caltech

"Training deep learning models on petabyte-scale Earth observation (EO) data requires separating compute resources from data storage. However, standard PyTorch data loaders cannot keep modern GPUs utilized when streaming GeoTIFF files directly from cloud storage. In this work, we benchmark GeoTIFF loading throughput from both cloud object storage and local SSD, systematically testing different loader configurations and data parameters. We focus on tile-aligned reads and worker thread pools, using Bayesian optimization to find optimal settings for each storage type. Our optimized configurations increase remote data loading throughput by 20× and local throughput by 4× compared to default settings. On three public EO benchmarks, models trained with optimized remote loading achieve the same accuracy as local training within identical time budgets. We improve validation IoU by 6–15% and maintain 85–95% GPU utilization versus 0–30% with standard configurations. Code is publicly available at github.com/microsoft/pyto…"

One of the first radio astronomers, Ruby Payne-Scott, was recently recognised with a ferry named in her honour! Read more about Ruby and how she made waves at CSIRO: csiro.au/en/news/All/Ar…

Who knew dust could be so pretty! 😍 New images from NASA’s recently launched PUNCH (Polarimeter to Unify the Corona and Heliosphere) mission show the beauty of zodiacal light, the faint glow of sunlight reflecting off dust surrounding our Sun. At left, a combined image from one of PUNCH's three Wide Field Imagers (WFIs) shows the zodiacal light. The light has been colorized based on its angle, or polarization. The Sun's position is marked by the star icon. At right, an image from PUNCH’s Narrow Field Imager (NFI) shows a new Moon against a blocked SUn. A new Moon would normally appear completely dark against the bright light of the Sun, but PUNCH’s NFI instrument has an occulter (the dark circle covering the Sun) that blocks the Sun’s disk to image the Sun’s faint surroundings. In this much dimmer setting, mere Earthshine (sunlight reflected off of Earth) is enough to illuminate the Moon. View these images and more: go.nasa.gov/3S2N5Oq

@AdamF_Astro You’re doing great work!

Looking forward to the next step of my academic journey! All the way from @CongletonHS to @LancasterUni and @UniofExeter then @CEAParisSaclay and now starting in November @esascience. 😍🚀☀️

Biomass antenna deployment selfie 👇 esa.int/Applications/O…