Mohammadamin (Amin) Banayeeanzade


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I am a third-year CS Ph.D. student at the University of Southern California (USC), working with Sai Praneeth Karimireddy. I am currently interested in the intersection of optimization theory and modern deep learning, particularly investigating certain phenomena in deep learning models such as generalization, memorization, and feature learning. Prior to USC, I received my Master's at computer engineering department of Sharif University of Technology under the supervision of Mahdieh Soleymani, where I did research on developing brain-inspired algorithms for the meta-continual learning problem. Additionally, I got my B.Sc. in electrical engineering from the same university where I was jointly supervised by Mahdi Shabany and Zahra Kavehvash.

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Publications

Mechanistic Interpretability of Emotion Inference in Large Language Models
A. N. Tak, M. Banayeeanzade, A. Bolourani, M. Kian, R. Jia, J. Gratch
under review at ACL
Theoretical Insights into Overparameterized Models in Multi-Task and Replay-Based Continual Learning
M. Banayeeanzade, M. Soltanolkotabi, M. Rostami
under review at TMLR
GABRIL: a Gaze-Based Regularization Method for Mitigating Causal Confusion in Imitation Learning
M. Banayeeanzade, F. Bahrani, Y. Zhou, E. Biyik
to be submitted to IROS 2025
Hybrid Learners Do Not Forget: A Brain-Inspired Neuro-Symbolic Approach to Continual Learning
M. Banayeeanzade, M. Rostami
under prepration
A Distinct Unsupervised Reference Model from The Environment Helps Continual Learning
A. Ameli, M. Banayeeanzade, Mahdi Samiei, Mahdieh Soleymani
arXiv, 2023
Generative vs. Discriminative: Rethinking The Meta-Continual Learning
M. Banayeeanzade, Rasoul Mirzaiezadeh, Hosein Hasani, Mahdieh Soleymani
NeurIPS, 2021

Other Projects

Automatic Detection of Objects Concealed Under Clothing in the Millimeter-Wave Images
Employing deep learning to detect, localize and unveal concealed objects at MMW body scanners.
Accomplished project as senior AI researcher at BasirWave Tech