works on

From the 1 of 6 linked papers with an AI index.

activity
20242026
collaborators

6 papers

cs.AI2026

Networked Intelligence: Active Shared Context Graphs for Human-AI Team Science

Sutanay Choudhury, Jeffrey J. Czajka, Lummy M. O. Monteiro +15

The paper presents Mycelium, an active shared workspace that links human researchers and AI agents by capturing observations and hypotheses, maintaining a evolving knowledge model,…

physics.chem-ph2026

Reaction-network reasoning with frontier models for experimentally confirmed catalyst-selectivity hypotheses

Sutanay Choudhury, Anwesha Banerjee, Udishnu Sanyal +7

Catalysts are essential for sustainable chemical manufacturing, yet discovering novel architectures remains a bottleneck dominated by trial-and-error experimentation and computatio…

cs.DC2025

Optimizing Data Distribution and Kernel Performance for Efficient Training of Chemistry Foundation Models: A Case Study with MACE

Jesun Firoz, Franco Pellegrini, Mario Geiger +17

Chemistry Foundation Models (CFMs) that leverage Graph Neural Networks (GNNs) operating on 3D molecular graph structures are becoming indispensable tools for computational chemists…

cs.AI2024

Thinking Fast and Laterally: Multi-Agentic Approach for Reasoning about Uncertain Emerging Events

Stefan Dernbach, Alejandro Michel, Khushbu Agarwal +3

This paper introduces lateral thinking to implement System-2 reasoning capabilities in AI systems, focusing on anticipatory and causal reasoning under uncertainty. We present a fra…

physics.chem-ph2024

ChemReasoner: Heuristic Search over a Large Language Model's Knowledge Space using Quantum-Chemical Feedback

Henry W. Sprueill, Carl Edwards, Khushbu Agarwal +6

The discovery of new catalysts is essential for the design of new and more efficient chemical processes in order to transition to a sustainable future. We introduce an AI-guided co…

cs.AI2024

GLaM: Fine-Tuning Large Language Models for Domain Knowledge Graph Alignment via Neighborhood Partitioning and Generative Subgraph Encoding

Stefan Dernbach, Khushbu Agarwal, Alejandro Zuniga +2

Integrating large language models (LLMs) with knowledge graphs derived from domain-specific data represents an important advancement towards more powerful and factual reasoning. As…