Somdatta Goswami

Somdatta Goswami

Assistant Professor, Department of Civil and Systems Engineering, Johns Hopkins University

Submitted manuscript

  1. Katarzyna Michałowska, Somdatta Goswami, George Em Karniadakis, and Signe Riemer-Sørensen. Neural Operator Learning for Long-Time Integration in Dynamical Systems with Recurrent Neural Networks.
  2. Qianying Cao, Somdatta Goswami, and George Em Karniadakis. LNO: Laplace Neural Operator for Solving Differential Equations.
  3. Ayan Chakraborty, Cosmin Anitescu, Somdatta Goswami, Zhuang Xiaoying, and Timon Rabczuk. Variational energy based XPINNs for phase field analysis in brittle fracture.
  4. Katarzyna Michałowska, Somdatta Goswami, George Em Karniadakis, and Signe Riemer-Sørensen. DON-LSTM: Multi-Resolution Learning with DeepONets and Long Short-Term Memory Neural Networks.
  5. Katiana Kontolati, Somdatta Goswami, George Em Karniadakis, & Michael Shields Learning in latent spaces improves the predictive accuracy of deep neural operators.

Book Chapter

  1. Somdatta Goswami, Annirudha Bora, Yue Yu, George Em Karniadakis. Physics-Informed Deep Neural Operator Networks. In: Rabczuk, T., Bathe, KJ. (eds) Machine Learning in Modeling and Simulation. Computational Methods in Engineering & the Sciences. Springer, Cham (2023).

Journal Papers

  1. M. L. Taccari, H. Wang, Somdatta Goswami, J. Nuttall, X. Chen, P. K. Jimack (2023). Developing a cost-effective emulator for groundwater flow modeling using deep neural operators Journal of Hydrology, p. 130551.
  2. Qianying Cao, Somdatta Goswami, George Em Karniadakis, and Souvik Chakraborty. Deep neural operators can predict the real-time response of floating offshore structures under irregular waves Computers & Structures 291 (2024), p.107228.
  3. Nikolas Borrel-Jensen, Somdatta Goswami, Allan P. Engsig-Karup, George Em Karniadakis, and Cheol-Ho Jeong. Sound propagation in realistic interactive 3D scenes with parameterized sources using deep neural operators Proceedings of the National Academy of Sciences 120 (2023).
  4. Somdatta Goswami, Ameya D. Jagtap, Hessam Babaee, Bryan T. Susi, and George Em Karniadakis. Learning stiff chemical kinetics using extended deep neural operators Computer Methods in Applied Mechanics and Engineering 419 (2024), p.116674.
  5. Varun Kumar, Somdatta Goswami, Daniel J. Smith, and George Em Karniadakis. Real-Time Prediction of Multiple Output States in Diesel Engines using a Deep Neural Operator Framework Applied Intelligence (2024).
  6. Adar Kahana, Enrui Zhang, Somdatta Goswami, George Em Karniadakis, Rishikesh Ranade, Jay Pathak. On the Geometry Transferability of the Hybrid Iterative Numerical Solver for Differential Equations Computational Mechanics (2023), p.1-14.
  7. Katiana Kontolati *, Somdatta Goswami*, Michael D. Shields, and George Em Karniadakis. On the influence of over-parameterization in manifold based surrogates and deep neural operators Journal of Computational Physics 479(2023), p.112008.
  8. Somdatta Goswami *, Katiana Kontolati *, Michael D. Shields, and George Em Karniadakis. Deep transfer learning for partial differential equations under conditional shift with DeepONet Nature Machine Intelligence 4(2022), p.1-10.
  9. Vivek Oommen, Khemraj Shukla, Somdatta Goswami, Remi Dingreville, and George Em Karniadakis. Learning two-phase microstructure evolution using neural operators and autoencoder architectures npj Computational Materials 8(2022), p.190.
  10. Somdatta Goswami *, David S Li *, Bruno V Rego, Marcos Latorre, Jay D Humphrey, and George Em Karniadakis. Neural operator learning of heterogeneous mechanobiological insults contributing to aortic aneurysms Journal of the Royal Society Interface 19(2022)
  11. Ritukesh Bharali, Somdatta Goswami, Cosmin Anitescu, and Timon Rabczuk. A robust monolithic solver for phase-field fracture integrated with fracture energy based arc-length method and under-relaxation Computer Methods in Applied Mechanics and Engineering 394, p.114587.
  12. Lu, Lu, Xuhui Meng, Shengze Cai, Zhiping Mao, Somdatta Goswami, Zhongqiang Zhang, and George Em Karniadakis. A comprehensive and fair comparison of two neural operators (with practical extensions) based on FAIR data. Computer Methods in Applied Mechanics and Engineering 393, p.114778.
  13. Somdatta Goswami, Minglang Yin, Yue Yu, and George Em Karniadakis. A physics-informed variational DeepONet for predicting the crack path in brittle materials, Computer Methods in Applied Mechanics and Engineering 391 (2022): 114587.
  14. Tanmoy Chatterjee, Souvik Chakraborty, Somdatta Goswami, Sondipon Adhikari, and Michael I Friswell. Robust topological designs for extreme metamaterial micro-structures, Sci Rep 11, 15221 (2021).
  15. Somdatta Goswami, Cosmin Anitescu, and Timon Rabczuk. Adaptive fourth-order phase field analysis using deep energy minimization, Theoretical and Applied Fracture Mechanics 107(2020):102527.
  16. Somdatta Goswami, Cosmin Anitescu, and Timon Rabczuk. Adaptive fourth-order phase field analysis for brittle fracture, Computer Methods in Applied Mechanics and Engineering 361(2020):112808.
  17. E Samaniego, C Anitescu, S Goswami, V M Nguyen-Thanh, H Guo, K Hamdia, X Zhuang, and T Rabczuk. An energy approach to the solution of partial differential equations in computational mechanics via machine learning:Concepts, implementation and applications, Computer Methods in Applied Mechanics and Engineering 362(2020):112790.
  18. Somdatta Goswami, Cosmin Anitescu, Souvik Chakraborty, and Timon Rabczuk. Transfer learning enhanced physics informed neural network for phase-field modeling of fracture. Theoretical and Applied Fracture Mechanics 106(2019):102447.
  19. Somdatta Goswami, Cosmin Anitescu, and Timon Rabczuk. Adaptive phase field analysis with dual hierarchical meshes for brittle fracture. Engineering Fracture Mechanics 218(2019):106608.
  20. Somdatta Goswami*, Souvik Chakraborty*, Rajib Chowdhury, and Timon Rabczuk. Threshold shift method for reliability-based design optimization. Structural and Multidisciplinary Optimization 60(5)(2019):2053–2072.
  21. Somdatta Goswami*, Souvik Chakraborty*, and Timon Rabczuk. A surrogate assisted adaptive framework for robust topology optimization. Computer Methods in Applied Mechanics and Engineering 346(2019):63-84.
  22. Somdatta Goswami, Shyamal Ghosh, and Subrata Chakraborty. Reliability analysis of structures by iterative improved response surface method. Structural Safety 60(2016):56–66.

Conference Papers

  1. Ranjan Mukherjee, Sushant Kumar Meinia, Somdatta Goswami, and Gita Negi. Objective Evaluation of Poor Veins Using Image Processing Technique: An Outcome Analysis. Scientific Session – Finding Solutions for Donor Problems. The 30th regional congress of the International Society of Blood Transfusion (2019):10-11.
  2. Somdatta Goswami, and Subrata Chakraborty. Adaptive Response Surface Method Based Efficient Monte Carlo Simulation. Vulnerability, Uncertainty, and Risk: Quantification, Mitigation, and Management (2014):2043-2052.
  3. Somdatta Goswami, , Subrata Chakraborty, and Shyamal Ghosh. Adaptive response surface method in structural response approximation under uncertainty. International Conference on Structural Engineering and Mechanics (2013):194-202.