Journal Publications (Google Scholar Profile)
- Raghav Gnanasambandam, Bo Shen, Jihoon Chung, Xubo Yue, and Zhenyu (James) Kong. Self-scalable Tanh (Stan): Faster Convergence and Better Generalization in Physics-informed Neural Networks. IEEE TPAMI (Impact Factor 23.6) (2023).
[Preprint]- Winner for INFORMS Data Mining and Decision Analytics Workshop Poster Competition (2022)
- Winner for IISE QCRE/ProcessMiner Data Challenge Competition (2022)
Raghav Gnanasambandam, Bo Shen, Andrew Chung Chee Law, and Zhenyu (James) Kong. Deep Gaussian Process Upper Confidence Bound for Optimizing Non-Stationary Functions and its Application in Additive Manufacturing. Under review at IISE Transactions (2022).
[Preprint]Rongxuan Wang , Ruixuan Wang , Chaoran Dou , Shuo Yang , Raghav Gnanasambandam, Anbo Wang, and Zhenyu (James) Kong. “Novel Fiber Optic Sensing with Extra High Spatial Resolution Enabled by Machine Learning and its Application for Sub-surface Thermal Measurement in Additive Manufacturing Processes”. Nature Communications (Accepted).
Bo Shen, Raghav Gnanasambandam, Rongxuan Wang, and Zhenyu (James) Kong. Multi-Task Gaussian Process Upper Confidence Bound for Hyperparameter Tuning and its Application for Simulation Studies of Additive Manufacturing. IISE Transactions. (2022).
[Paper] [Code]V Akhil, Raghav Gnanasambandam, N Arunachalam, and DS Srinivas. Image data-based surface texture characterization and prediction using machine learning approaches for additive manufacturing. Journal of Computing and Information Science in Engineering. (2020).
[Paper] [Code]- V Akhil, N Arunachalam, Raghav Gnanasambandam, and DS Srinivas. Surface texture characterization of selective laser melted Ti-6Al-4V components using fractal dimension and lacunarity analysis. Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture. (2020).
[Paper] [Code]