PhD (Computational Science) @ Shanghai Jiao Tong University • PIML/CFD • Foundation Models for Science
Acta non Verba
-@Samsomyajit-111111?logo=x&logoColor=white){kind=icon}
I am a doctoral researcher at Shanghai Jiao Tong University (SJTU) focusing on Physics-Informed Machine Learning (PIML), Computational Fluid Dynamics (CFD), and foundation models/LLMs for scientific computing. Broader interests include network science, computational intelligence, optimization, and decision-making. Always open to ideas and collaborations!
- PDE/CFD Surrogates: Physics-informed transformers & operators; stability, conservation, and OOD robustness
- Foundation Models for Science: Instruction-tuned LLMs and agents for simulation workflows and literature-grounded reasoning
- Complex Networks: Collaboration networks, scientometrics, re-entry/comeback dynamics in early careers
- Trust@Health: A Trust-Based Multilayered Network for Scalable Healthcare Service Management — IEEE Access, 2025 (Corresponding Author)
DOI: 10.1109/ACCESS.2025.3613326 · Preprint: arXiv:2508.11942 - Comeback or dropout: study of discontinued researchers at early career stage — Scientometrics, 2025
DOI: 10.1007/s11192-025-05243-z - Influence of Multi-dimensional Social Capital on Structure of Scientific Collaboration Networks (MDSC@SciCoNet) — SN Computer Science, 2025
DOI: 10.1007/s42979-025-03945-y - LLMPR: A Novel LLM-Driven Transfer Learning based Petition Ranking Model — arXiv, 2025
DOI: 10.48550/arXiv.2505.21689
Highlights
- PhD focus: Physics-informed systems for CFD and scientific ML
- Early-career work on researcher dropout vs. comeback dynamics
- Open to collaborations in PIML/CFD, operator learning, and agentic science
- Academic Collaboration Networks & scientometrics
- Physics-informed ML surrogates for CFD / PDEs
- Foundation models & agentic AI for scientific computing
- Optimization and decision-making in complex systems