A New Dataset Based on Images Taken by Blind People for Testing the Robustness of Image Classification Models Trained for ImageNet Categories. - Reza Akbarian Bafghi; Danna Gurari (CVPR, 2023)

PINNs-TF2: Fast and User-Friendly Physics-Informed Neural Networks in TensorFlow V2. - Reza Akbarian Bafghi; Maziar Raissi (CoRR, 2023)

Parameter Efficient Fine-tuning of Self-supervised ViTs without Catastrophic Forgetting. - Reza Akbarian Bafghi; Nidhin Harilal; Claire Monteleoni; Maziar Raissi (CVPR Workshops, 2024)

Mixing Natural and Synthetic Images for Robust Self-Supervised Representations. - Reza Akbarian Bafghi; Nidhin Harilal; Claire Monteleoni; Maziar Raissi (CoRR, 2024)

Where Did Your Model Learn That? Label-free Influence for Self-supervised Learning. - Nidhin Harilal; Amit Rege; Reza Akbarian Bafghi; Maziar Raissi; Claire Monteleoni (CoRR, 2024)

Aligning to What? Limits to RLHF Based Alignment. - Logan Barnhart; Reza Akbarian Bafghi; Stephen Becker; Maziar Raissi (NAACL (Findings), 2025)

MixDiff: Mixing Natural and Synthetic Images for Robust Self-Supervised Representations. - Reza Akbarian Bafghi; Nidhin Harilal; Claire Monteleoni; Maziar Raissi (WACV, 2025)

Fine Tuning without Catastrophic Forgetting via Selective Low Rank Adaptation. - Reza Akbarian Bafghi; Carden Bagwell; Avinash Ravichandran; Ashish Shrivastava; Maziar Raissi (CoRR, 2025)