activity
20242026
most citedRUL forecasting for wind turbine predictive maintenance based on deep learning

26 citations · 26 across the 4 of their papers we have counts for

collaborators

6 papers

cs.AI2026

Uncertainty and Fairness Awareness in LLM-Based Recommendation Systems

Chandan Kumar Sah, Xiaoli Lian, Li Zhang +2

Large language models (LLMs) enable powerful zero-shot recommendations by leveraging broad contextual knowledge, yet predictive uncertainty and embedded biases threaten reliability…

cs.CY2025

PerFairX: Is There a Balance Between Fairness and Personality in Large Language Model Recommendations?

Chandan Kumar Sah

The integration of Large Language Models (LLMs) into recommender systems has enabled zero-shot, personality-based personalization through prompt-based interactions, offering a new…

cs.CV2025

CleanMAP: Distilling Multimodal LLMs for Confidence-Driven Crowdsourced HD Map Updates

Ankit Kumar Shaw, Kun Jiang, Tuopu Wen +5

The rapid growth of intelligent connected vehicles (ICVs) and integrated vehicle-road-cloud systems has increased the demand for accurate, real-time HD map updates. However, ensuri…

cs.IR2025

FairEval: Evaluating Fairness in LLM-Based Recommendations with Personality Awareness

Chandan Kumar Sah, Xiaoli Lian, Tony Xu +1

Recent advances in Large Language Models (LLMs) have enabled their application to recommender systems (RecLLMs), yet concerns remain regarding fairness across demographic and psych…

cs.CV2025

Advancing Autonomous Vehicle Intelligence: Deep Learning and Multimodal LLM for Traffic Sign Recognition and Robust Lane Detection

Chandan Kumar Sah, Ankit Kumar Shaw, Xiaoli Lian +5

Autonomous vehicles (AVs) require reliable traffic sign recognition and robust lane detection capabilities to ensure safe navigation in complex and dynamic environments. This paper…

eess.SP202426 cited

RUL forecasting for wind turbine predictive maintenance based on deep learning

Syed Shazaib Shah, Tan Daoliang, Sah Chandan Kumar

Predictive maintenance (PdM) is increasingly pursued to reduce wind farm operation and maintenance costs by accurately predicting the remaining useful life (RUL) and strategically…