Keynotes and Invited Talks

2024

  • Actor JA. “Data-Driven Reduced Models using Radial Basis Functions,” 9th European Congress on Computational Methods in the Applied Sciences, June 2024, Lisbon, Portugal. (Invited)
  • Owhadi H. “Computational Hypergraph Discovery,” SIAM UQ24, Feb 27–Mar 1, 2024. (Plenary Lecture)
  • Perego M. "Hybrid finite-element /neural operator modeling for ice-sheet dynamics," World Congress on Computational Mechanics, Vancouver, Canada, July 24, 2024.

2023

  • Actor JA. "Data-Driven Structure Preservation for Scientific Machine Learning," 3rd Sandia Machine Learning and Deep Learning Conference (MLDL), Virtual, July 17–20, 2023. (Invited Talk)
  • Actor JA. "Structure-Preserving Machine Learning via Whitney Forms," S. Scott Collis Advanced Modeling and Simulation Seminar Series, University of Texas at El Paso, El Paso, TX (virtual), October 2023. (Invited Talk)
  • Actor JA, A Huang, N Trask. "Machine-Learned Finite Element Exterior Calculus for Linear and Nonlinear Problems," ICERM Mathematical and Scientific Machine Learning Workshop, Providence, RI, June 5–9, 2023. (Invited Talk)
  • Actor JA, A Huang, N Trask. "Machine-Learned Whitney Forms for Structure Preservation," 10th International Congress on Industrial and Applied Mathematics (ICIAM), Waseda University, Tokyo, Japan, August 20–25, 2023. (Invited Talk)
  • Aimone B. “The Pursuit of the Brain’s Ubiquitous Stochasticity," 2023 International Conference on Neuromorphic, Natural and Physical Computing, October 2023 (Keynote Talk)
  • Cyr EC. “Exploiting “time-domain” parallelism to accelerate neural network training and PDE constrained optimization,” CCAM seminar at Purdue, West Lafayette, IN, April 2023. (Invited Talk)
  • Cyr EC. “A Layer-Parallel Approach for Training Deep Neural Networks,” SIAM CSE, Amsterdam, Netherlands, February 2023. (Invited Talk)
  • Cyr EC. “Exploiting “time-domain” parallelism to accelerate neural network training,” Banff Workshop on Scientific Machine Learning, Banff, Alberta, Canada, June 18–June 23, 2023. (Invited Talk)
  • Howard, A. “High Performance Computing for Multiphase Flows,” Spelman College Senior Seminar, Atlanta, GA, 2023. (Invited Talk)
  • Howard A. "Multifidelity Deep Operator Networks," ICERM Mathematical and Scientific Machine Learning Workshop, Providence, RI, June 5–9, 2023. (Invited Talk)
  • Karniadakis GE. "Physics-Informed Machine Learning: Blending data & physics for fast predictions," Chemical Engineering Colloquium, Lehigh University, February 2023. (Invited Talk)
  • Karniadakis GE. "BINNs: Biophysics-Informed Neural Networks," IBS Biomedical Mathematics, April 2023. (Invited Talk)
  • Karniadakis GE. "From Physics-Informed Machine Learning to Physics-Informed Machine Intelligence: Quo Vadimus?" FAU MoD Lecture Series, May 2023. (Invited Talk)
  • Karniadakis GE. "NeuralUQ: A Comprehensive Library for Uncertainty Quantification in Scientific Machine Learning," 5th International Conference on Uncertainty Quantification in Computational Science and Engineering, June 2023. (Plenary Lecture)
  • Karniadakis GE. "Neural PDEs and Neural Operators for Fluid Mechanics and Reactive Transport," Stanford FLAME AI Workshop, September 2023. (Invited Talk)
  • Karniadakis GE. "Scaling up Physics-Informed Machine Learning to Real World Applications," HPC Day, University of Massachusetts Dartmouth, October 2023. (Plenary Lecture)
  • Karniadakis GE. "Neural PDEs and Neural Operators for Physics-Informed Learning," AI/ML in Physics 2023, October 2023. (Invited Talk)
  • Karniadakis GE. "Physics-Informed Neural Networks (PINNs) & Deep Operator Network (DeepOnet)," SciML@Simula Workshop, December 2023. (Invited Talk)
  • Panda P. AAAI 2023 Workshop on Practical Deep Learning in the Wild, February 2023. (Keynote)
  • Panda P. “Algorithm-Hardware Co-design with Neuromorphic Computing,” Rhine-Westphalia Technical University of Aachen, March 2023. (Invited Talk)
  • Panda P. “Bio-plausible Algorithm-Hardware Co-Design with Spiking Neural Networks,” Brown University, April 2023. (Invited Talk)
  • Panda P. “Bio-plausible Algorithm-Hardware Co-Design with Spiking Neural Networks,” Princeton University, April 2023. (Invited Talk)
  • Panda P. “Neuromorphic Computing: Opportunities and Challenges for Edge Intelligence,” Eindhoven University of Technology, April 2023. (Invited Talk)
  • Panda P. "Bio-plausible Algorithm-Hardware Co-Design for Efficient and Robust AI,” Talk Link, May 2023. (Invited Talk)
  • Panda P. “Spiking Neural Networks: Opportunities and Challenges,” ICERM 2023 Meeting on Mathematical and Scientific Machine Learning, Providence, RI, June 2023. (Invited Talk)
  • Panda P. "Hardware Accelerators for Spiking Neural Networks for Energy-efficient Edge Computing," 4th ROAD4NN Workshop: Research Open Automatic Design for Neural Networks, 60th Annual Design Automation Conference, San Francisco, CA, July 2023. (Invited Talk)
  • Panda P. “Computational Needs for Lifelong Learning," DARPA 2023 Electronics Resurgence Initiative 2.0 Summit, August 2023. (Keynote)
  • Perego M. “Computational Aspects of Ice-Sheet Modeling,” Pitt Mathematics-Naval Nuclear Laboratory Joint Seminar, Pittsburgh, PA, March 14, 2023. (Invited Talk)
  • Perego M. “A Hybrid Operator Network/Finite Element Method for Ice-Sheet Modeling,” 17th U. S. National Congress on Computational Mechanics, Albuquerque, NM, July 23-27, 2023. (Invited Talk)
  • Perego M. “Machine Learning modeling for accelerated uncertainty quantification in projections of ice sheets' mass change,” American Geophysical Union Fall Meeting, San Francisco, CA, Dec 10-15, 2023. (Invited Talk)
  • Stinis P. “Machine-learning custom-made basis functions for partial differential equations,” University of Arizona Applied Mathematics Colloquium, Tucson, AZ, March 2023. (Invited Talk)
  • Stinis P. “Spiking Neural Network Representation of Partial Differential Equation Evolution Maps,” SIAM Conference on Computational Science and Engineering, Amsterdam, Netherlands, March 2023. (Invited Talk)
  • Stinis P. “Multi-fidelity Scientific Machine Learning,” BIRS Scientific Machine Learning Workshop, Banff, Canada, June 2023. (Invited Talk)
  • Stinis P. “Multi-fidelity Scientific Machine Learning,” Georgia Tech Applied & Computational Math Seminar, Atlanta, GA, November 2023. (Invited Talk)

2022

  • Actor JA, Huang, A, Trask, N. "Polynomial-Spline Networks with Exact Integrals and Convergence Rates," 2022 IEEE Symposium Series on Computational Intelligence (SSCI), Singapore, December 4–7, 2022. (Invited Talk)
  • Howard A. “Multifidelity Machine Learning Methods.” CMIT Seminar, Liverpool, UK, November 2022. (Invited Talk)
  • Karniadakis G. "From PINNs to Deep Neural Operators to Digital Twins: Quo Vadimus?" Digital Twins Information Gathering Session #1, Joint National Academies on the Foundational Research Gaps and Future Directions for Digital Twins. December 2022. (Invited Talk)
  • Panda P. “Exploring Robustness and Efficiency in Neural System with Spike-based Machine Intelligence,” ICCAD HALO 2022. November 2022. (Invited Talk)
  • Panda P. “Algorithm-Hardware Co-design for Efficient and Robust Spiking Neural Networks,” SNUF 2022. November 2022. (Invited Talk)
  • Panda P. “TCS Forum: Thought Leadership Conversations: Neuromorphic Computing for Transformation of the Industrial Future,” TCS Thought Forum on Neuromorphic. November 2022. (Invited Talk)