4 papers
AdditiveLLM: Large Language Models Predict Defects in Additive Manufacturing
Peter Pak, Amir Barati Farimani
In this work we investigate the ability of large language models to predict additive manufacturing defect regimes given a set of process parameter inputs. For this task we utilize…
IDP-Bert: Predicting Properties of Intrinsically Disordered Proteins (IDP) Using Large Language Models
Parisa Mollaei, Danush Sadasivam, Chakradhar Guntuboina +1
Intrinsically Disordered Proteins (IDPs) constitute a large and structure-less class of proteins with significant functions. The existence of IDPs challenges the conventional notio…
FaultFormer: Pretraining Transformers for Adaptable Bearing Fault Classification
Anthony Zhou, Amir Barati Farimani
The growth of global consumption has motivated important applications of deep learning to smart manufacturing and machine health monitoring. In particular, analyzing vibration data…
BeadSight: An Inexpensive Tactile Sensor Using Hydro-Gel Beads
Abraham George, Yibo Chen, Atharva Dikshit +2
In robotic manipulation, tactile sensors are indispensable, especially when dealing with soft objects, objects of varying dimensions, or those out of the robot's direct line of sig…