6 citations · 10 across the 4 of their papers we have counts for
4 papers
Exploring Different Time-series-Transformer (TST) Architectures: A Case Study in Battery Life Prediction for Electric Vehicles (EVs)
Niranjan Sitapure, Atharva Kulkarni
In recent years, battery technology for electric vehicles (EVs) has been a major focus, with a significant emphasis on developing new battery materials and chemistries. However, ac…
Introducing Hybrid Modeling with Time-series-Transformers: A Comparative Study of Series and Parallel Approach in Batch Crystallization
Niranjan Sitapure, Joseph S Kwon
Most existing digital twins rely on data-driven black-box models, predominantly using deep neural recurrent, and convolutional neural networks (DNNs, RNNs, and CNNs) to capture the…
Require Process Control? LSTMc is all you need!
Niranjan Sitapure, Joseph S Kwon
Over the past three decades, numerous controllers have been developed to regulate complex chemical processes, but they have certain limitations. Traditional PI/PID controllers ofte…
CrystalGPT: Enhancing system-to-system transferability in crystallization prediction and control using time-series-transformers
Niranjan Sitapure, Joseph S. Kwon
For prediction and real-time control tasks, machine-learning (ML)-based digital twins are frequently employed. However, while these models are typically accurate, they are custom-d…