The Neil Ashton Podcast

Prof. Juan Alonso — The future of computational science

Season 1, episode 6 01:27:06

Prof. Juan Alonso — The future of computational science — The Neil Ashton Podcast

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Prof. Juan Alonso — The future of computational science

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Episode overview

In this episode I speak to Prof Juan J. Alonso on his vision of the future of computational science as well as his journey from academia to entrepreneurship - founding Luminary Cloud. He reflects on the revolutions in computational science and the different ways of developing software throughout his career.

Alonso emphasizes the importance of academia in creating and perpetuating knowledge, as well as the value of innovation and new ideas. He also discusses the changes in the CFD world, the emergence of new technologies like GPU computing and cloud computing, and the potential for advancements in computational simulations for analysis and design. We also touch on the transition of the aerospace industry towards commercial software and the potential for cloud computing to revolutionize CFD.

The conversation concludes with a discussion on the progress made towards achieving the goals outlined in the 2030 CFD vision report and the role of machine learning and AI in simulation-driven workflows. In this final part of the conversation, Juan discusses the potential applications of ML and AI in engineering. He identifies four main areas where these technologies can be beneficial, but emphasizes that these applications will always be based on high-fidelity simulations.

He concludes by envisioning the future of computational-driven science and the continued innovation in the field. You can check out Luminary Cloud at

Chapters

  1. 06:00 Introduction and Background
  2. 09:11 Early Interest in Aerospace Engineering
  3. 12:13 From Academia to Industry
  4. 15:11 Decision to Stay in Academia
  5. 17:11 Balancing Fundamental Science and Applied Research
  6. 22:14 Early Aims and Focus on High Performance Computing
  7. 29:18 Emergence of GPU Computing and Cloud Computing
  8. 32:23 Conditions for Innovation and Entrepreneurship
  9. 35:01 The Importance of the Bay Area
  10. 35:37 Challenges and Requirements in Developing Solvers
  11. 41:00 The Role of the Bay Area in Attracting Computational Science Talent
  12. 44:16 The Difficulty and Respect for Building High-Quality Commercial Software
  13. 47:03 The Transition of the Aerospace Industry towards Commercial Software
  14. 49:30 The Potential of Cloud Computing in Revolutionizing CFD
  15. 53:59 Progress towards the Goals of the 2030 CFD Vision Report
  16. 01:00:53 The Role of Machine Learning and AI in Simulation-Driven Workflows
  17. 01:04:01 Applications of ML and AI in Engineering
  18. 01:05:36 Optimization and Design Optimization with ML and AI
  19. 01:06:04 Outer Loops and Uncertainty Quantification
  20. 01:07:04 Digital Twin Frameworks and Constant Retraining
  21. 01:12:36 The Value of Open-Source Codes in Academia
  22. 01:16:19 Challenges of Integrating Commercial Tools with Research
  23. 01:25:20 The Future of Computational-Driven Science
  24. 01:29:01 Continued Innovation and Replacement of Physical Experimentation

References and links

Transcript

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