Atul Agrawal

I'll be at @NeurIPSConf 2025 in San Diego presenting our new work from @proximafusion: ConStellaration - a dataset of QI-like stellarator boundaries + optimization benchmarks. Poster #2211, Exhibit Hall C/D/E Dec 4, 11am-2pm Paper: openreview.net/forum?id=NQSbG... #fusion #Al #AI4Sci

New paper alert. "Stochastic black-box optimization using multifidelity score function estimator," published in @MLSTjournal (@IOPPublishing ) w\ @mandrakeMojito @SKoutsourelakis prof. Hans Bungartz. iopscience.iop.org/article/10.108… #BlackBoxOptimization #SciML #UQ #ML

ARTICLE: From concrete mixture to structural design—a holistic optimization procedure in the presence of uncertainties ✍️@Atul_Ag07, @SKoutsourelakis (@TU_Muenchen), Erik Tamsen and J.F. Unger (@BAMResearch) 👉bit.ly/4eIo6Jo

Have an optimization problem involving a real-world physics-based simulator? The simulator is stochastic, 💵💵, black-box, multi-modal, and high dimensional? We might have a solution. Check out: hal.science/hal-04659802 (w Kislaya Ravi, @SKoutsourelakis , J.H. Bungartz)

New paper on probabilistic data driven model for turbulence closure with @SKoutsourelakis in @ElsevierPhysics Journal of Computational Physics. Open Source link: sciencedirect.com/science/articl… @TU_Muenchen #RANS #turbulence #DataDriven #SciML

New work with @Atul_Ag07 on a probabilistic, data-driven closure model for RANS equations sciencedirect.com/science/articl…

I will be attending #NeurIPS2023 in person. Would love to chat on probabilistic machine learning + engineering/physics.

(3/3) We proposed a physics-based inductive bias term in a popular ML model for the unclosed term in the Reynolds-Averaged Navier-Stokes #RANS equations, leading to improved predictions. arxiv.org/abs/2311.14576

Our submissions in @NeurIPSConf @ML4PhyS got accepted. (1/3) When a stochastic, high-dimensional, black-box physics-based simulator is involved in constrained optimization, there are not many viable options out there. We attempt to propose one. (collab. with @SKoutsourelakis)

LVM3 M4/Chandrayaan-3 Mission: LVM3 M4 vehicle🚀 successfully launched Chandrayaan-3🛰️ into orbit.

Model uncertainty remains one the most difficult topics in #Uncertainty_Quantification. Here is our attempt to quantify it in the context of the Reynolds-Averaged Navier-Stokes model #RANS, in a physically meaningful manner that still allows probabilistic predictive estimates.

Interested in learning a probabilistic, #data-driven #turbulence closure model from sparse velocity/pressure observations, while quantifying the model form error? (Joint work with prof. @SKoutsourelakis ) #turbulence #RANS #datadriven #probabilisticmachinelearning #UQ

Check out our new #JCP paper about: Simple computational strategies for more effective physics-informed neural networks modeling of turbulent natural convection The paper is freely available for next 50 days, click below. lnkd.in/eArPTE-c #turbulence #AI #PINN #fluid

@RailMinIndia @AshwiniVaishnaw @IRCTCofficial Train 03170 takes 16.5 hours to traverse 560 Kms. Mean speed ~34 kph. Being a customer, I believe I deserve the right to know why so slow even in 21st century.

Interested about efficient surrogate for turbulent thermal convection? Or ML for fluid mechanics in general 👇 Work from my time in @LisnLab ( @UnivParisSaclay) #ML #turbulence #PINNs

Interested in using unlabeled data (i.e. just inputs) and physical constraints in constructing efficient surrogates for PDEs with high-dimensional parametric inputs in the Small-Data regime? More information in the newly-published J. of Comp. Phys. paper authors.elsevier.com/a/1cel5508Hokgj

Congratulations prof @SKoutsourelakis and Sebastian.

@airindiain What about customer service. I didn't get refund of the tickets cancelled between Germany to India flight. Not even a confirmation mail.

#FlyAI : Air India group is proud to have flown a MILLION passengers on 7791 flights till date under Vande Bharat Mission, which is covering 74 destinations in 54 Countries. The Mission continues.....

#RAISE2020 is all set to take place from Oct 5 to 9, 2020 in a virtual avatar. The summit will host some of the world's most renowned AI leaders and decision makers - to understand how AI can be mobilised for greater social good. Register NOW: bit.ly/3cdUBA5 #AIforAll