Keyan Miao (Interfacing Control with Neural ODEs)

In this episode I got to chat with the incredibly wonderful Dr Keyan Miao about the fascinating work she’s done on neural ODEs. We discuss applying control theoretic tools to optimise neural ODEs, as well as their use for both controller and observer design. And in case that wasn’t already enough we also touch on dissipativity, Koopman operators, and reinforcement learning! You can find the transcript for this episode at: https://docs.google.com/document/d/1iI0swQSnNEqgGQgf7og8udRV3IBCXbbfEkLFlolGxEU/edit?usp=sharing Follow the podcast on LinkedIn: https://www.linkedin.com/company/coffee-and-control-podcast/ Or connect with me directly: https://www.linkedin.com/in/lucy-hodgins-733a30175/ Join the live recording on 20th October 2026! https://www.youtube.com/watch?v=2S9X66_Wfzc ( 9:30 PDT, 12:30 ET, 16:30 UTC, 17:30 BST, 18:30 CEST) References Keyan Miao: https://kymiao.github.io/ Richard Vinter: https://profiles.imperial.ac.uk/r.vinter  QianXiao Li from NUS and Wei-Nan Er from Princeton: https://www.jmlr.org/papers/volume18/17-653/17-653.pdf https://link.springer.com/article/10.1007/s40687-018-0172-y https://ems.press/journals/jems/articles/5404458 Book on control theory/ philosophy: https://apac.ee.kntu.ac.ir/publications/books/control-systems-a-historical-and-philosophical-perspective/ Control theory/ philosophy article: https://www.numberanalytics.com/blog/control-theory-philosophical-lens-language NCCR automation fellowship: https://nccr-automation.ch/research-fellowship Andreas Krause: https://las.inf.ethz.ch/krausea Steve Brunton ResNet video: https://www.youtube.com/watch?v=w1UsKanMatM&t=911s Original neural ODE paper: https://proceedings.neurips.cc/paper_files/paper/2018/file/69386f6bb1dfed68692a24c8686939b9-Paper.pdf Speeding up Neural ODE training and inference: https://proceedings.mlr.press/v235/miao24a.html Neural ODE review: https://www.sciencedirect.com/science/article/pii/S2950550X25000263 Review of Neural ODEs in biomedical engineering: https://www.annualreviews.org/content/journals/10.1146/annurev-bioeng-110824-124907 Neural ODEs for observer design paper: https://arxiv.org/abs/2212.00866 Non-linear observer review: https://www.sciencedirect.com/science/article/pii/S1367578821000948 Neural ODEs for control design papers: https://arxiv.org/abs/2504.17139 Survey on CBFs: https://coogan.ece.gatech.edu/papers/pdf/amesecc19.pdf Koopman operator paper: https://arxiv.org/pdf/2509.07294 Combining neural ODEs with RL: https://www.sciencedirect.com/science/article/pii/S0925231225007131 Neural ODE dissipativity paper: https://www.sciencedirect.com/science/article/pii/S0005109826003043 Papers on Neural Network Verification: HuanZhang (UIUC) https://proceedings.neurips.cc/paper_files/paper/2018/file/d04863f100d59b3eb688a11f95b0ae60-Paper.pdf https://proceedings.neurips.cc/paper_files/paper/2021/file/fac7fead96dafceaf80c1daffeae82a4-Paper.pdf https://arxiv.org/pdf/2605.26577 Papers on Direct NN parameterization: Ian Manchester (USyd)and Patricia Pauli (Eindhoven) https://ieeexplore.ieee.org/abstract/document/9319198 https://arxiv.org/abs/2410.22258 https://proceedings.mlr.press/v202/wang23v.html https://ieeexplore.ieee.org/abstract/document/9867842 Ricky Chen: https://rtqichen.github.io/ Flow matching paper: https://arxiv.org/abs/2210.02747 Antonis Papachristoudolou: https://eng.ox.ac.uk/people/antonis-papachristodoulou Carmen Amo Alonso episode: https://open.spotify.com/episode/393QBgVgsQwgh4wKj1bcLy