activity
20242026
collaborators

8 papers

cs.LG2026

Physics-Distilled Neural Network enabled by Large Language Models for Manufacturing Process-Property Predictive Modeling

Ge Song, Kiarash Naghavi Khanghah, Anandkumar Patel +2

Predicting process-property relationships in manufacturing is often challenged by high experimental costs and the limited interpretability of complex 'black-box' models. This paper…

cs.LG2026

GPT-Micro: A large language paradigm for accelerated, inexpensive, and thermodynamics-consistent discovery of constitutive models in manufacturing

Soumik Dutta, Kiarash Naghavi Khanghah, Sania Shree +4

Constitutive modeling of the relationship between process-imposed material states and fundamental material properties is critical to control of material microstructure in manufactu…

cs.LG2026

LLM-ADAM: A Generalizable LLM Agent Framework for Pre-Print Anomaly Detection in Additive Manufacturing

Ahmadreza Eslaminia, Chuhan Cai, Cameron Smith +5

Additive manufacturing (AM) continues to transform modern manufacturing by enabling flexible, on-demand production of complex geometries across diverse industries. Fused filament f…

cs.LG2025

Hyperdimensional Computing for Sustainable Manufacturing: An Initial Assessment

Danny Hoang, Anandkumar Patel, Ruimen Chen +2

Smart manufacturing can significantly improve efficiency and reduce energy consumption, yet the energy demands of AI models may offset these gains. This study utilizes in-situ sens…

cs.LG2025

Domain-Aware Hyperdimensional Computing for Edge Smart Manufacturing

Fardin Jalil Piran, Anandkumar Patel, Rajiv Malhotra +1

Smart manufacturing requires on-device intelligence that meets strict latency and energy budgets. HyperDimensional Computing (HDC) offers a lightweight alternative by encoding data…

cs.AI2025

Multimodal RAG-driven Anomaly Detection and Classification in Laser Powder Bed Fusion using Large Language Models

Kiarash Naghavi Khanghah, Zhiling Chen, Lela Romeo +4

Additive manufacturing enables the fabrication of complex designs while minimizing waste, but faces challenges related to defects and process anomalies. This study presents a novel…