Coarse-scale PDEs from fine-scale observations via machine learning. - Seungjoon Lee; Mahdi Kooshkbaghi; Konstantinos G. Spiliotis; Constantinos I. Siettos; Ioannis G. Kevrekidis (CoRR, 2019)

Manifold learning for parameter reduction. - Alexander Holiday; Mahdi Kooshkbaghi; Juan M. Bello-Rivas; C. William Gear; Antonios Zagaris; Ioannis G. Kevrekidis (J. Comput. Phys., 2019)

Emergent Spaces for Coupled Oscillators. - Thomas N. Thiem; Mahdi Kooshkbaghi; Tom Bertalan; Carlo R. Laing; Ioannis G. Kevrekidis (Frontiers Comput. Neurosci., 2020)

On the Parameter Combinations That Matter and on Those That do Not. - Nikolaos Evangelou; Noah J. Wichrowski; George A. Kevrekidis; Felix Dietrich; Mahdi Kooshkbaghi; Sarah McFann; Ioannis G. Kevrekidis (CoRR, 2021)

Characterization of partial wetting by CMAS droplets using multiphase many-body dissipative particle dynamics and data-driven discovery based on PINNs. - Elham Kiyani; Mahdi Kooshkbaghi; Khemraj Shukla; Rahul Babu Koneru; Zhen Li 003; Luis Bravo; Anindya Ghoshal; George Em Karniadakis; Mikko Karttunen (CoRR, 2023)