Promoting Green Fashion Consumption in Recommender Systems

The fashion industry is a significant contributor to global carbon emissions, water consumption, and waste generation. My Ph.D. project explores two approaches to promote sustainability in fashion recommender systems. First, I aim to develop algorithms and user interfaces that nudge users towards more sustainable and ethical fashion choices by incorporating relevant data into the recommendation process and item presentation. This involves balancing user preferences with sustainability considerations and exploring effective ways to present this complex information to users. Second, I seek to make the recommendation algorithms themselves more environmentally sustainable by reducing their computational cost without compromising recommendation quality. To achieve these goals, I plan to leverage multimodal item representations, multi-criteria recommendation techniques, and novel algorithmic approaches. I expect to complete my Ph.D. in October, 2025.