Shahed Masoudian

Shahed Masoudian

I’m a research assistant at Johannes Kepler University. I studied my master at JKU focusing on unsupervised deep domain adaptation method. My curent research is Deep Learning in Natural Language Processing with focus on Modularity and Controllability of Neural Networks.


Publications

Peer-Reviewed Journal and Conference Papers

ModDebias screenshot

Alessandro B. Melchiorre, Shahed Masoudian, Deepak Kumar, Markus Schedl
Modular Debiasing of Latent User Representations in Prototype-based Recommender Systems
Proceedings of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD 2024), 2024
 Best Student Paper Award

Scalearn_ACL_2024 screenshot

Markus Frohman, Carolin Holtermann, Shahed Masoudian, Anne Lauscher, Navid Rekab-saz
ScaLearn: Simple and Highly Parameter-Efficient Task Transfer by Learning to Scale
Findings of the Association for Computational Linguistics ACL 2024, 2024

ConGater_EACL_2024 screenshot

Shahed Masoudian, Volaucnik Cornelia, Markus Schedl, Navid Rekab-saz
Effective Controllable Bias Mitigation for Classification and Retrieval using Gate Adapters
The 18th Conference of the European Chapter of the Association for Computational Linguistics March 17-22, 2024, 2024

ControlledDA_EUSIPCO_2023 screenshot

Shahed Masoudian, Koutini Khaled, Markus Schedl, Widmer Gerhard, Navid Rekab-saz
Domain Information Control at Inference Time for Acoustic Scene Classification
31st European Signal Processing Conference, (EUSIPCO) 2023, Helsinki,Finland, September 4-8, 2023, 2023

ModularDebiasing_ACLFindings_2023 screenshot

Lukas Hauzenberger, Shahed Masoudian, Deepak Kumar, Markus Schedl, Navid Rekab-saz
Modular and On-demand Bias Mitigation with Attribute-Removal Subnetworks
Findings of the Association for Computational Linguistics: ACL 2023, 2023