23 citations · 28 across the 8 of their papers we have counts for
9 papers
Planning or Learning: Reliability and Cost in Multi-Asset Maintenance
Xian Yeow Lee, Chandrasekar Venkatraman, Ahmed Farahat
Industrial maintenance systems involve multiple interacting assets and shared resources, making it challenging to balance reliability and operational cost using a single decision f…
Diagnosing Fine-Grained Inconsistency Classification in Financial Disclosure Text
Aman Kumar, Lasitha Vidyaratne, Dipanjan D Ghosh +2
Financial disclosures may contain numerical, temporal, referential, factual, and policy inconsistencies that require different evidence and reasoning to diagnose. We study fine-gra…
Building Domain-Specific Small Language Models via Guided Data Generation
Aman Kumar, Ekant Muljibhai Amin, Xian Yeow Lee +5
Large Language Models (LLMs) have shown remarkable success in supporting a wide range of knowledge-intensive tasks. In specialized domains, there is growing interest in leveraging…
Weakly-supervised Latent Models for Task-specific Visual-Language Control
Xian Yeow Lee, Lasitha Vidyaratne, Gregory Sin +2
Autonomous inspection in hazardous environments requires AI agents that can interpret high-level goals and execute precise control. A key capability for such agents is spatial grou…
A Hierarchical Agentic Framework for Autonomous Drone-Based Visual Inspection
Ethan Herron, Xian Yeow Lee, Gregory Sin +3
Autonomous inspection systems are essential for ensuring the performance and longevity of industrial assets. Recently, agentic frameworks have demonstrated significant potential fo…
Exploring LLM-based Frameworks for Fault Diagnosis
Xian Yeow Lee, Lasitha Vidyaratne, Ahmed Farahat +1
Large Language Model (LLM)-based systems present new opportunities for autonomous health monitoring in sensor-rich industrial environments. This study explores the potential of LLM…
An ensemble of convolution-based methods for fault detection using vibration signals
Xian Yeow Lee, Aman Kumar, Lasitha Vidyaratne +3
This paper focuses on solving a fault detection problem using multivariate time series of vibration signals collected from planetary gearboxes in a test rig. Various traditional ma…
CDA: Contrastive-adversarial Domain Adaptation
Nishant Yadav, Mahbubul Alam, Ahmed Farahat +3
Recent advances in domain adaptation reveal that adversarial learning on deep neural networks can learn domain invariant features to reduce the shift between source and target doma…
An Offline Deep Reinforcement Learning for Maintenance Decision-Making
Hamed Khorasgani, Haiyan Wang, Chetan Gupta +1
Several machine learning and deep learning frameworks have been proposed to solve remaining useful life estimation and failure prediction problems in recent years. Having access to…