Research Publications
Contributions to Machine Learning, AI Alignment, and Network Science
Published Work
Peer-reviewed publications in top-tier conferences
Metatuning: A Novel Lightweight Adaptation Framework for Aligning Large Language Models
Aniruddha Chattopadhyay, Kaushik Roy (Asst. prof University of Alabama)
First-author long paper on Metatuning, a novel lightweight adaptation framework for aligning large language models (LLMs) with symbolic reasoning objectives. Introduces metatuning as a middle ground between few-shot prompting and full fine-tuning, enabling efficient structural alignment on consumer hardware.
EduTree: An Academic Genealogy Graph (AGG) Modeling Mentorship Lineages
Aniruddha Chattopadhyay, et al.
Presented EduTree, an academic genealogy graph (AGG) modeling mentorship lineages and institutional influence within the field of education. Applied graph-theoretic centrality measures and topic modeling to quantify researcher impact and trace the evolution of research clusters. Identified high-centrality mentors, pioneering institutions, and thematic trajectories shaping the discipline's academic network.
Research Interests
Current Focus
- •Multimodal AI systems combining vision, language, and audio modalities
- •Efficient adaptation methods for large language models
- •AI safety and alignment in generative systems
- •Real-time inference optimization for edge deployment
Future Directions
I'm particularly interested in pursuing graduate research that bridges the gap between theoretical advances in AI and practical deployment challenges. My goal is to contribute to making AI systems more efficient, reliable, and accessible for real-world applications.