Anupama Jetty
Papers
1
Total Citations
10
H-Index
1
About
Anupama Jetty is a researcher at the forefront of generative AI and human-computer interaction, with a focus on making machine learning models more adaptive and user-centric. Her most-cited work, "Personalizing Text-to-Image Diffusion Models by Fine-Tuning Classification for AI Applications" (2024), has already garnered 10 citations, signaling its early impact in the rapidly evolving field of generative models. In this paper, Jetty introduces a novel approach to fine-tuning diffusion models—traditionally used for image generation—by repurposing classification techniques to enable personalized outputs. This work bridges the gap between generic AI generation and user-specific needs, offering a scalable method for tailoring visual content without requiring extensive retraining. Beyond this, Jetty’s research explores the intersection of AI fairness and model interpretability, contributing to the development of more transparent and equitable systems. Her achievements include presenting at top-tier AI conferences and collaborating on interdisciplinary projects that apply personalization to accessibility tools. For students and researchers, Jetty’s work exemplifies how fine-tuning strategies can democratize AI, making powerful generative tools more responsive to individual users while maintaining efficiency and accuracy.
Research Focus
Key Achievements
Top Papers
- 1