Physics-aware deep neural networks for surrogate modeling of turbulent natural convection. - Didier Lucor; Atul Agrawal; Anne Sergent (CoRR, 2021)

A reduced-order modeling framework for simulating signatures of faults in a bladed disk. - Divya Shyam Singh 002; Atul Agrawal; D. Roy Mahapatra (CoRR, 2021)

Simple computational strategies for more effective physics-informed neural networks modeling of turbulent natural convection. - Didier Lucor; Atul Agrawal; Anne Sergent (J. Comput. Phys., 2022)

Multi-fidelity Constrained Optimization for Stochastic Black Box Simulators. - Atul Agrawal; Kislaya Ravi; Phaedon-Stelios Koutsourelakis; Hans-Joachim Bungartz (CoRR, 2023)

Detection of DoS and DDoS Attacks Using Machine Learning and Blockchain in IoMT Networks. - Atul Agrawal; Pashupati Baniya; Esraa Mohammed Alazzawi; Nitin Rakesh; Bharat Bhushan; Akhtar Jamil (AIBThings, 2024)

Particle Swarm Optimization versus Simulated Annealing for 5G and 6G Wireless Networks: A Comparative Study. - Atul Agrawal; Pashupati Baniya; Shraiyash Pandey; Bharat Bhushan; Nitin Rakesh (WPMC, 2024)

A probabilistic, data-driven closure model for RANS simulations with aleatoric, model uncertainty. - Atul Agrawal; Phaedon-Stelios Koutsourelakis (J. Comput. Phys., 2024)

Stochastic black-box optimization using multi-fidelity score function estimator. - Atul Agrawal; Kislaya Ravi; Phaedon-Stelios Koutsourelakis; Hans-Joachim Bungartz (Mach. Learn. Sci. Technol., 2025)

ConStellaration: A dataset of QI-like stellarator plasma boundaries and optimization benchmarks. - Santiago A. Cadena; Andrea Merlo; Emanuel Laude; Alexander Bauer; Atul Agrawal; Maria Pascu; Marija Savtchouk; Enrico Guiraud; Lukas Bonauer; Stuart Hudson; Markus Kaiser 008 (CoRR, 2025)