3 citations · 8 across the 6 of their papers we have counts for
6 papers
Graph-Based Kirchhoff Modeling of Non-Ohmic Electron Transport in Self-Assembled Nanonecklace Networks
Obed Issakah, Srivathsan Badrinarayanan, Ravi F. Saraf +1
Gold nanonecklace networks exhibit non-Ohmic current--voltage I-V characteristics with a sharp conduction threshold, making them promising for sensing and transistor-like devices.…
Meta-Learning for Cross-Task Generalization in Protein Mutation Property Prediction
Srivathsan Badrinarayanan, Yue Su, Janghoon Ock +3
Protein mutations can have profound effects on biological function, making accurate prediction of property changes critical for drug discovery, protein engineering, and precision m…
Large Language Model Agent for Modular Task Execution in Drug Discovery
Janghoon Ock, Radheesh Sharma Meda, Srivathsan Badrinarayanan +3
We present a modular framework powered by large language models (LLMs) that automates and streamlines key tasks across the early-stage computational drug discovery pipeline. By com…
LLM-guided Chemical Process Optimization with a Multi-Agent Approach
Tong Zeng, Srivathsan Badrinarayanan, Janghoon Ock +2
Chemical process optimization maximizes production efficiency and economic performance, but optimization algorithms, including gradient-based solvers, numerical methods, and parame…
MOFGPT: Generative Design of Metal-Organic Frameworks using Language Models
Srivathsan Badrinarayanan, Rishikesh Magar, Akshay Antony +2
The discovery of Metal-Organic Frameworks (MOFs) with application-specific properties remains a central challenge in materials chemistry, owing to the immense size and complexity o…
Multi-Peptide: Multimodality Leveraged Language-Graph Learning of Peptide Properties
Srivathsan Badrinarayanan, Chakradhar Guntuboina, Parisa Mollaei +1
Peptides are essential in biological processes and therapeutics. In this study, we introduce Multi-Peptide, an innovative approach that combines transformer-based language models w…