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S1, EP6 - Prof Juan Alonso - the Future of Computational Science

Summary 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 https://www.luminarycloud.com and Prof Alonso's Stanford research at: https://adl.stanford.edu Spotify version: https://open.spotify.com/episode/7f6Y... Apple version: https://podcasts.apple.com/gb/podcast... Chapters 06:00 Introduction and Background 09:11 Early Interest in Aerospace Engineering 12:13 From Academia to Industry 15:11 Decision to Stay in Academia 17:11 Balancing Fundamental Science and Applied Research 22:14 Early Aims and Focus on High Performance Computing 29:18 Emergence of GPU Computing and Cloud Computing 32:23 Conditions for Innovation and Entrepreneurship 35:01 The Importance of the Bay Area 35:37 Challenges and Requirements in Developing Solvers 41:00 The Role of the Bay Area in Attracting Computational Science Talent 44:16 The Difficulty and Respect for Building High-Quality Commercial Software 47:03 The Transition of the Aerospace Industry towards Commercial Software 49:30 The Potential of Cloud Computing in Revolutionizing CFD 53:59 Progress towards the Goals of the 2030 CFD Vision Report 01:00:53 The Role of Machine Learning and AI in Simulation-Driven Workflows 01:04:01 Applications of ML and AI in Engineering 01:05:36 Optimization and Design Optimization with ML and AI 01:06:04 Outer Loops and Uncertainty Quantification 01:07:04 Digital Twin Frameworks and Constant Retraining 01:12:36 The Value of Open-Source Codes in Academia 01:16:19 Challenges of Integrating Commercial Tools with Research 01:25:20 The Future of Computational-Driven Science 01:29:01 Continued Innovation and Replacement of Physical Experimentation #fluidmechanics #cfd #f1 #tech #cloudcomputing #neilashton #aerodynamics #gpu #stanford #juanalonso