@ChaopengShen

Prof @PennStateCEE. Solving water and resilience problems with AI & physc-informed AI. Streams, soil moisture, groundwater, landslide, etc. Rethink h2o

 State College, PA
mhpi.info
Joined March 2019
  • Tweets2.3K
  • Following543
  • Followers3.5K
273Media
Excited to share new paper on Nature Reviews @NatRevEarthEnv. Want to discover relationships from data? Or answer questions in #Geosci? Or obtain ML-level performance with interpretable processes? Differentiable Modelling could be your answer! rdcu.be/dgzYj (1/n)
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Chaopeng Shen retweeted
Dipankar@DipankarDw0819 Jul 2025
Deadline approaching soon! Submit your abstract to #AGU25 Session H038: Advancing #Watershed Science Through #Hybrid #ML and #Physical #Modeling @ChaopengShen @pkumar3691 @charuleka @berkeley_ai @BerkeleyLab
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Penn State researchers, including @ChaopengShen and @yalan_song from @PennStateCEE, developed an innovative water model that uses #AI to create highly-accurate #flood predictions with data gathered from rivers around the U.S. psu.edu/news/engineering/sto…

Improving predictions of flood severity, place and time with AI | Penn State University

A research group, including several Penn State researchers, developed a computational model to streamline flood prediction in the continental United States. Their model, which they call a different...

psu.edu
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At @iclr_conf the AI conf today. Anyone in Singapore? My presentation is tmr.
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Excited to share our new paper in Journal of Hydrology! We developed a differentiable model that fuses multiple precipitation datasets to boost streamflow prediction — especially for high flows. Grateful to my mentors @ChaopengShen & @yalan_song! 📄 doi.org/10.1016/j.jhydrol.20…
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A massive paper and a generational leap in national-scale high-resolution seamless hydrologic simulation. We published the continental-scale simulation dataset. If you have interests, please inquire! doi.org/10.1029/2024WR038928 /run
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Dear all, we are extending the abstract submission deadline to April 1. After this date, we will evaluate the situation. Therefore, we kindly ask that you refrain from booking travel until you hear from us regarding the next steps.
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New paper alert "Hydrogeological Modeling With an Integrated Latent Diffusion Framework" with @reza_soltanian, Chuanjun Zhan, Zhenxue Dai, Jiu Jimmy Jiao, Huichao Yin, @nmsu, @nmsu_aces, @PES_NMSU : agupubs.onlinelibrary.wiley.…

Toward Artificial General Intelligence in Hydrogeological Modeling With an Integrated Latent...

Latent Diffusion Framework enables hydrogeological modeling across multiple tasks The integrated framework achieves diverse hydrogeological objectives without task-specific designs The multi-tas...

agupubs.onlinelibrary.wiley.com
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From. The. Rooftops. You're not going to find a magic money-printing machine anywhere else that will give you these types of reliable returns year-after-year. @NOAA and @NWS don't just keep us safe - they create immense value for the American taxpayer.
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Dear all, Since many are here, the news is here. HydroML 2025 will be hosted at UC Irvine and held at the UCLA Lake Arrowhead Lodge near Los Angeles. It is the week of May 26 - 30 (likely May 27 - 29) Final dates TBD. Check out hydroml.org.
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meanwhile please follow me on Linked Internally and Ciel Bleu
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Great opportunity with CIROH 👇👇👇
CIROH at The University of Alabama@UA_CIROH3 Feb 2025
🚀 Want to research AI & hydrology this summer? The 2025 Summer Research Program offers: 💰 $5,680 stipend + FREE housing 🌊 Work on AI-driven water forecasting 📍 UA campus w/ NOAA & USGS mentors 🔗 Apply by Mar. 1 → slate.ua.edu/register/UAREU2… @AlabamaWater
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Please come and evaluate our continental-scale seamless streamflow simulation (1990-1999 more is being uploaded) using hybrid physics-informed ML ("differentiable") hydrologic model. Could be a blast! zenodo.org/records/14292069 This comes with our preprint doi.org/10.22541/essoar.1727…

Streamflow datasets from the high-resolution, multiscale, differentiable HBV hydrologic models

This dataset is from the high-resolution, multiscale, differentiable HBV hydrologic models, provided by the Multi-scale Hydrology, Processes, and Intelligence (MHPI) team from The Pennsylvania State...

zenodo.org
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Just post some news until other platfms are setup. Our paper  “Sensitivity-Constrained Fourier Neural Operators for Forward and Inverse Problems” has been accepted into ICLR 2025 main, a premier AI conference. It is so hard and rare for domain people to publish here.
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This is our first submission to a generic AI conference. Can't wait to bring our unique perspectives into the main AI realm. @Ambehroozi is the first author of the paper. Stay tuned for the paper --- will make some minimum edits for the camera-ready version! #ICLR2025
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meanwhile, please follow me where sky is bluer. I'm gonna be on both sides through the transition.
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We are release the Differentiable Modeling - Generic (δMG) framework, a domain-agnostic, PyTorch-based framework for developing models that can train neural networks with process-based equations together on big data. It unifies many DM research activities mhpi.github.io/codes/framewo…
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dMG is not a model. Rather, it is a framework to uniformly support differentiable models (training neural networks together with process equations together) while integrating an ecosystem of services. Should be very easy learning curve. Pick up differentiable modeling in hours!
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Examples and tutorials are given for doing differentiable hydrologic modeling, soon ecosystem modeling, water temperature modeling, and more… this is the framework to build on! Ongoing work will add data assimilation, multiscale modeling, unique surrogate models, etc…
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Don’t know why but whenever I type in these text boxes on my phone there can be lots of typos and grammar bugs that i failed to detect….darn it… sorry folks, but the dMG framework is one true gem!
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