Amin Banayeeanzade
Mohammadamin (Amin) Banayeeanzade

I'm a fourth-year CS Ph.D. student at the University of Southern California (USC), advised by Sai Praneeth Karimireddy. I study the trustworthiness of AI systems with a particular focus on diversity in large language models (LLMs) and agentic systems. My research investigates the diversity problem in current models, which often produce homogeneous outputs, follow narrow exploration traces, and rely on limited or biased inputs during decision-making. By systematically characterizing and improving diversity in these aspects, my work aims to enhance the robustness, fairness, and reliability of AI systems, ultimately strengthening their trustworthiness in real-world deployment.

Prior to USC, I finished my Master's at the Computer Engineering department of Sharif University of Technology advised by Mahdieh Soleymani, where I worked on brain-inspired algorithms for the meta-continual learning problem. I also received my B.Sc. in Electrical Engineering from the same university, advised by Mahdi Shabany and Zahra Kavehvash.

Publications
Sampling More, Getting Less: Calibration is the Diversity Bottleneck in LLMs
A. Banayeeanzade*, Q. Yang*, D. Tarsadiya, F. Bahrani, L. Blas, A. Samuel, R. Jia, M. Razaviyayn, S. P. Karimireddy
arXiv 2026
EPSVec: Efficient and Private Synthetic Data Generation via Dataset Vectors
A. Banayeeanzade*, Q. Yang*, D. Fu, S. Hong, E. Babinsky, A. Samuel, A. Kumar, R. Jia, S. P. Karimireddy
ICML 2026
Sparks of Rationality: Do Reasoning LLMs Align with Human Judgment and Choice?
A. N. Tak*, A. Banayeeanzade*, A. Bolourani*, F. Bahrani, A. Chaubey, S. P. Karimireddy, N. Schwarz, J. Gratch
ICLR 2026 Workshop on Representational Alignment
Psychological Steering in LLMs: An Evaluation of Effectiveness and Trustworthiness
A. Banayeeanzade*, A. N. Tak*, F. Bahrani, A. Bolourani, L. Blas, E. Ferrara, J. Gratch, S. P. Karimireddy
ACL 2026
Mechanistic Interpretability of Emotion Inference in Large Language Models
A. N. Tak*, A. Banayeeanzade*, A. Bolourani, M. Kian, R. Jia, J. Gratch
ACL 2025
Contextleak: Auditing leakage in private in-context learning methods
J. Choi, S. Cao, X. Dong, A. Banayeeanzade, W. B. Zhu, R. Jia, S. P. Karimireddy
arXiv, 2025
AutoFocus-IL: VLM-based Saliency Maps for Data-Efficient Visual Imitation Learning without Extra Human Annotations
L. Gong, F. Bahrani, Y. Zhou, A. Banayeeanzade, J. Li, E. Bıyık
ICRA 2026
Theoretical Insights into Overparameterized Models in Multi-Task and Replay-Based Continual Learning
A. Banayeeanzade, M. Soltanolkotabi, M. Rostami
TMLR 2025
GABRIL: Gaze-Based Regularization for Mitigating Causal Confusion in Imitation Learning
A. Banayeeanzade*, F. Bahrani*, Y. Zhou, E. Bıyık
IROS 2025
Hybrid Learners Do Not Forget: A Brain-Inspired Neuro-Symbolic Approach to Continual Learning
A. Banayeeanzade, M. Rostami
arXiv 2025
A Distinct Unsupervised Reference Model from The Environment Helps Continual Learning
A. Ameli, A. Banayeeanzade, M. Samiei, M. Soleymani
arXiv 2023
Generative vs. Discriminative: Rethinking The Meta-Continual Learning
A. Banayeeanzade*, R. Mirzaiezadeh*, H. Hasani, M. Soleymani
NeurIPS 2021

* Equal contributions.

Other Projects
Automatic Object Detection Under Clothing in Millimeter-Wave Images
Senior AI Researcher, Basir Wave Tech