inControl

Alberto Padoan

The first podcast on control theory. inControl shop: https://incontrolpodcast.myshopify.com/

  1. 11 hr ago

    The fall of LTCM: Bachelier, Merton, and Black–Scholes ... when stochastic control met Wall Street

    Outline 00:00 - Intro 02:25 - Bachelier and the Théorie de la Spéculation 03:05 - Stochastic processes, Brownian motion, and the heat equation 09:45 - Poincaré's verdict, obscurity, and rediscovery 13:50 - Robert C. Merton: from hot rods to MIT 19:25 - Dynamic programming and Itô calculus 24:35 - Merton's portfolio problem as stochastic optimal control 31:10 - Options, dynamic hedging, and the Black–Scholes–Merton equation 39:50 - LTCM: the dream team 46:30 - August 1998: the crash 49:00 - Fat tails and the ten-sigma defense 51:40 - The ghosts of 2008 and echoes in the AI boom 54:00 - Robustness embraced at last: Hansen and Sargent 57:45 - Outro Links Bachelier's thesis, "Théorie de la Spéculation" (1900): https://www.numdam.org/item/10.24033/asens.476.pdf Courtault et al., "Louis Bachelier on the Centenary of Théorie de la Spéculation": https://doi.org/10.1111/1467-9965.00098 Merton's Nobel autobiography: https://www.nobelprize.org/prizes/economic-sciences/1997/merton/biographical/ Merton's MIT "Infinite History" interview: https://infinite.mit.edu/video/robert-c-merton-phd-%E2%80%9970/ Mandelbrot, "The Variation of Certain Speculative Prices": https://doi.org/10.1086/294632 Merton, "Optimum Consumption and Portfolio Rules in a Continuous-Time Model": https://doi.org/10.1016/0022-0531(71)90038-X Moehle & Boyd, "A Certainty Equivalent Merton Problem": https://doi.org/10.1109/LCSYS.2021.3111534 Brigo & Mercurio, "Interest Rate Models: Theory and Practice": https://doi.org/10.1007/978-3-540-34604-3 Armstrong, Brigo & Hanzon, "Optimal Projection Filters with Information Geometry": https://doi.org/10.1007/s41884-023-00108-x Hu & Zhou, "Constrained Stochastic LQ Control with Random Coefficients, and Application to Portfolio Selection": https://doi.org/10.1137/S0363012904441969 Black & Scholes, "The Pricing of Options and Corporate Liabilities": https://doi.org/10.1086/260062 Merton, "Theory of Rational Option Pricing": https://doi.org/10.2307/3003143 Merton, "Option Pricing When Underlying Stock Returns Are Discontinuous": https://doi.org/10.1016/0304-405X(76)90022-2 Scholes' Nobel lecture: https://www.nobelprize.org/prizes/economic-sciences/1997/scholes/lecture/ Merton's Nobel lecture: https://www.nobelprize.org/prizes/economic-sciences/1997/merton/lecture/ Markowitz, "Portfolio Selection": https://doi.org/10.2307/2975974 Michael Lewis, "Liar's Poker": https://en.wikipedia.org/wiki/Liar%27s_Poker Edwards, "Hedge Funds and the Collapse of Long-Term Capital Management": https://doi.org/10.1257/jep.13.2.189 Lowenstein, "When Genius Failed": https://en.wikipedia.org/wiki/When_Genius_Failed Taleb, "Statistical Consequences of Fat Tails": https://arxiv.org/abs/2001.10488 Taleb & West, "Working with Convex Responses: Antifragility from Finance to Oncology": https://doi.org/10.3390/e25020343 Taleb, "The Black Swan": https://en.wikipedia.org/wiki/The_Black_Swan:_The_Impact_of_the_Highly_Improbable Taleb, "Fooled by Randomness": https://en.wikipedia.org/wiki/Fooled_by_Randomness Man Group, "The AI Bubble: Hidden Risks and Opportunities": https://www.man.com/insights/the-ai-bubble Sen. Warren's remarks at the Vanderbilt Policy Accelerator: https://www.banking.senate.gov/newsroom/minority/warren-remarks-at-vanderbilt-policy-accelerator-event-highlighting-economic-and-financial-risks-of-potential-ai-crash Meng & Chen, "Artificial Intelligence and Systemic Risk": https://arxiv.org/abs/2604.03272 Doyle, "Guaranteed Margins for LQG Regulators": https://doi.org/10.1109/TAC.1978.1101791 Safonov & Athans, "Gain and Phase Margin for Multiloop LQG Regulators": https://doi.org/10.1109/TAC.1977.1101470 Hansen & Sargent, "Robust Control and Model Uncertainty": https://doi.org/10.1257/aer.91.2.60 Hansen & Sargent, "Wanting Robustness in Macroeconomics": http://www.tomsargent.com/research/wanting.pdf Support the show Podcast info Podcast website: https://www.incontrolpodcast.com/ Apple Podcasts: https://tinyurl.com/5n84j85j Spotify: https://tinyurl.com/4rwztj3c RSS: https://tinyurl.com/yc2fcv4y Youtube: https://tinyurl.com/bdbvhsj6 Facebook: https://tinyurl.com/3z24yr43 Twitter: https://twitter.com/IncontrolP Instagram: https://tinyurl.com/35cu4kr4 Acknowledgments and sponsors This episode was supported by the National Centre of Competence in Research on «Dependable, ubiquitous automation» and the IFAC Activity fund. The podcast benefits from the help of an incredibly talented and passionate team. Special thanks to L. Seward, E. Cahard, F. Banis, F. Dörfler, J. Lygeros, ETH studio and mirrorlake . Music was composed by A New Element.

  2. 15 Jun

    ep45 - Peter Caines: from stochastic and adaptive control to mean field games, graphons, and beyond!

    Outline 00:00 - Intro 02:10 - London in the 1960s 12:40 - From Oxford to Imperial College: David Mayne and the discrete-time Riccati equation 18:05 - The "global tour": Montenegro roads, hitch-hiking to Istanbul, and the San Francisco waterfront 22:30 - Feedback and causality between stochastic processes 31:15 - The system identification years 40:50 - Model complexity, the bias–variance trade-off, and concentration inequalities 52:05 - Adaptive control: living through a golden era 1:00:30 - McGill, George Zames, and CIFAR's "institute without walls," and COCOLOG 1:09:45 - Mean field games: the China connection, the cell-phone problem, and Nash Certainty Equivalence 1:20:15 - The Lasry–Lions simultaneous discovery 1:24:40 - From graphons to graphexons: sparse networks, Laplexions, and geometry 1:31:00 - Linear Stochastic Systems, Popper, and falsifiability 1:35:20 - Advice to young researchers 1:38:00 - Outro Links Peter Caines' website: https://www.mcgill.ca/cim/caines Linear Stochastic Systems: https://epubs.siam.org/doi/book/10.1137/1.9781611974713   On the discrete-time matrix Riccati equation of optimal control: https://doi.org/10.1080/00207177008931892 Feedback between stationary stochastic processes: https://doi.org/10.1109/TAC.1975.1101008 Prediction-error identification methods for stationary stochastic processes: https://doi.org/10.1109/TAC.1976.1101304 Asymptotic normality of prediction-error estimators for approximate system models: https://doi.org/10.1109/CDC.1978.268066 Discrete-time multivariable adaptive control (Axelby Award): https://doi.org/10.1109/TAC.1980.1102363 Discrete-time stochastic adaptive control: https://doi.org/10.1137/0319052 25 seminal control papers of the 20th century: https://books.google.ca/books/about/Control_Theory.html?id=eVhGAAAAYAAJ COCOLOG: A conditional observer and controller logic for finite machines: https://epubs.siam.org/doi/10.1137/S0363012992226636 Hierarchical hybrid control systems: https://doi.org/10.1109/9.664153 On the hybrid optimal control problem: https://ieeexplore.ieee.org/document/4303244 Bode Lecture: https://ieeecss.org/presentation/bode-lecture/mean-field-stochastic-control The cell-phone problem - Large population stochastic wireless power control: https://doi.org/10.1109/CDC.2003.1272542 Large-population stochastic dynamic games - McKean-Vlasov and the Nash Certainty Equivalence principle: https://projecteuclid.org/journals/communications-in-information-and-systems/volume-6/issue-3/Large-population-stochastic-dynamic-games--closed-loop-McKean-Vlasov/cis/1183728987.full Large-population cost-coupled LQG with nonuniform agents and decentralized ε-Nash equilibria: https://doi.org/10.1109/TAC.2007.904450 Social optima in mean field LQG control: https://doi.org/10.1109/TAC.2012.2183439 ε-Nash mean field games with major and minor agents: https://arxiv.org/abs/1209.5684 Graphon mean field games and their equations: https://doi.org/10.1137/20M136373X Mean field games on large sparse network limits - Laplexion dynamics on graphexons: https://www.sciencedirect.com/science/article/pii/S240589632500388X Murray Wonham oral history: https://www.youtube.com/watch?v=8IBZyRo0vDk Support the show Podcast info Podcast website: https://www.incontrolpodcast.com/ Apple Podcasts: https://tinyurl.com/5n84j85j Spotify: https://tinyurl.com/4rwztj3c RSS: https://tinyurl.com/yc2fcv4y Youtube: https://tinyurl.com/bdbvhsj6 Facebook: https://tinyurl.com/3z24yr43 Twitter: https://twitter.com/IncontrolP Instagram: https://tinyurl.com/35cu4kr4 Acknowledgments and sponsors This episode was supported by the National Centre of Competence in Research on «Dependable, ubiquitous automation» and the IFAC Activity fund. The podcast benefits from the help of an incredibly talented and passionate team. Special thanks to L. Seward, E. Cahard, F. Banis, F. Dörfler, J. Lygeros, ETH studio and mirrorlake . Music was composed by A New Element.

  3. 15 May

    ep44 - Mario di Bernardo: From Circuits to Cells and Swarms — Control meets Complexity

    Outline 00:00 - Intro 01:30 - Origin story: Naples, electrical engineering, and the fascination with chaos 08:00 - What is chaos? 15:00 - DC-DC converters and discontinuity-induced bifurcations 22:00 - Piecewise-smooth dynamical systems 26:55 - Complex networks, synchronization, and pinning control 40:30- Synthetic biology: from gene regulatory networks to multicellular control 58:00 - COVID-19: a network epidemic model for Italy 1:02:00 - Multiscale control, statistical mechanics, and physics-informed control 1:19:10 - State of the field and the IEEE CSS 1:26:35 - Advice to young researchers 1:29:00 - Outro Links Mario's website: https://sites.google.com/site/dibernardogroup/home Scuola Superiore Meridionale: https://www.ssm.unina.it/ Chaos by James Gleick: https://en.wikipedia.org/wiki/Chaos:_Making_a_New_Science Control of chaos:https://en.wikipedia.org/wiki/Control_of_chaos Erasmus programme: https://en.wikipedia.org/wiki/Erasmus_Programme An Adaptive Approach to the Control and Synchronization of Continuous-time Chaotic Systems: https://doi.org/10.1142/S0218127496000254 Piecewise-smooth Dynamical Systems: Theory and Applications: https://doi.org/10.1007/978-1-84628-708-4  Bifurcations in nonsmooth dynamical systems: https://doi.org/10.1137/050625060 Controllability of complex networks via pinning: https://doi.org/10.1103/PhysRevE.75.046103  Criteria for global pinning-controllability of complex networks: https://doi.org/10.1016/j.automatica.2008.07.007 Controllability of complex networks: https://doi.org/10.1038/nature10011 Controlling complex networks with complex nodes: https://doi.org/10.1038/s42254-023-00566-3 Analysis, design and implementation of a novel scheme for in-vivo control of synthetic gene regulatory networks: https://doi.org/10.1016/j.automatica.2011.01.073 In-vivo Real-time Control of Protein Expression from Endogenous and Synthetic Gene Networks: https://doi.org/10.1371/journal.pcbi.1003625 A network model of Italy shows that intermittent regional strategies can alleviate the COVID-19 epidemic: https://doi.org/10.1038/s41467-020-18827-5 A Continuification-Based Control Solution for Large-Scale Shepherding:  https://arxiv.org/abs/2411.04791 Shepherding control and herdability in complex multiagent systems: https://doi.org/10.1103/PhysRevResearch.6.L032012 Nonreciprocal field theory for decision-making in multi-agent control systems: https://doi.org/10.1038/s41467-025-63071-4 Support the show Podcast info Podcast website: https://www.incontrolpodcast.com/ Apple Podcasts: https://tinyurl.com/5n84j85j Spotify: https://tinyurl.com/4rwztj3c RSS: https://tinyurl.com/yc2fcv4y Youtube: https://tinyurl.com/bdbvhsj6 Facebook: https://tinyurl.com/3z24yr43 Twitter: https://twitter.com/IncontrolP Instagram: https://tinyurl.com/35cu4kr4 Acknowledgments and sponsors This episode was supported by the National Centre of Competence in Research on «Dependable, ubiquitous automation» and the IFAC Activity fund. The podcast benefits from the help of an incredibly talented and passionate team. Special thanks to L. Seward, E. Cahard, F. Banis, F. Dörfler, J. Lygeros, ETH studio and mirrorlake . Music was composed by A New Element.

  4. 15 Apr

    ep43 - Steve Brunton: DMD, Koopman, SINDy, Eigensteve Channel, HydroGym, Optimization, and much more

    Outline 00:00 - Intro 01:15 - Origin story: early path and the road to science  04:20 - On graphical visualization and aphantasia  08:08 - The interest in fluid dynamics  12:00 - Caltech, Jerry Marsden, and the move to the Pacific time zone  19:43 - Dynamic Mode Decomposition (DMD) and the Koopman operator  27:15 - On teaching and the Eigensteve channel  39:22 - SINDy: Sparse Identification of Nonlinear Dynamics  45:45 - Automatic knowledge creation and Explainable AI  54:31 - HydroGym: RL benchmarks for fluid flow control  1:01:37 - Optimization boot camp  1:05:31 - Collimator  1:13:18 - Outro Links Steve's website: https://www.eigensteve.com/ Eigensteve channel: https://www.youtube.com/c/eigensteve Jerrold E. Marsden: https://en.wikipedia.org/wiki/Jerrold_E._Marsden Aphantasia: https://en.wikipedia.org/wiki/Aphantasia J. Nathan Kutz: https://amath.washington.edu/people/j-nathan-kutz Clarence W. Rowley: https://cwrowley.princeton.edu/ DMD: https://en.wikipedia.org/wiki/Dynamic_mode_decomposition Koopman operator: https://en.wikipedia.org/wiki/Koopman_operator Dynamic Mode Decomposition book: https://epubs.siam.org/doi/book/10.1137/1.9781611974508 On Dynamic Mode Decomposition paper: https://doi.org/10.3934/jcd.2014.1.391 DMD with control: https://arxiv.org/abs/1409.6358 Compressed sensing and DMD: https://doi.org/10.3934/jcd.2015002 Modern Koopman Theory for Dynamical Systems: https://arxiv.org/abs/2102.12086 Deep learning for universal linear embeddings of nonlinear dynamics: https://doi.org/10.1038/s41467-018-07210-0 Data-driven discovery of Koopman eigenfunctions for control: https://doi.org/10.1088/2632-2153/abf0f5 PyDMD: https://github.com/PyDMD Discovering governing equations from data by sparse identification of nonlinear dynamical systems: https://doi.org/10.1073/pnas.1517384113 Data-driven discovery of partial differential equations: https://doi.org/10.1126/sciadv.1602614 SINDy for model predictive control in the low-data limit: https://doi.org/10.1098/rspa.2018.0335 PySINDy: https://github.com/dynamicslab/pysindy SINDy with control: https://arxiv.org/abs/2108.13404 SINDy review: https://doi.org/10.1146/annurev-control-030123-015238 Data-Driven Science and Engineering: Machine Learning, Dynamical Systems, and Control: http://www.databookuw.com Explainable AI: Learning from the Learners: https://arxiv.org/abs/2601.05525 HydroGym: https://github.com/dynamicslab/hydrogym Support the show Podcast info Podcast website: https://www.incontrolpodcast.com/ Apple Podcasts: https://tinyurl.com/5n84j85j Spotify: https://tinyurl.com/4rwztj3c RSS: https://tinyurl.com/yc2fcv4y Youtube: https://tinyurl.com/bdbvhsj6 Facebook: https://tinyurl.com/3z24yr43 Twitter: https://twitter.com/IncontrolP Instagram: https://tinyurl.com/35cu4kr4 Acknowledgments and sponsors This episode was supported by the National Centre of Competence in Research on «Dependable, ubiquitous automation» and the IFAC Activity fund. The podcast benefits from the help of an incredibly talented and passionate team. Special thanks to L. Seward, E. Cahard, F. Banis, F. Dörfler, J. Lygeros, ETH studio and mirrorlake . Music was composed by A New Element.

  5. 16 Mar

    ep42 - inControl guide to ... the Nyquist criterion

    Outline 00:00 – Intro 04:43 – Life and background 08:45 – Bell Labs 13:42 – Inventing the negative feedback amplifier 18:15 – Nyquist's landmark contributions 20:43 – Regeneration theory 27:10 – Frequency response 32:03 – Cauchy’s argument principle 36:05 – The Nyquist criterion 41:37 – Why is it so hard? 45:27 – Robustness, margins, and practical aspects 56:41 – Beyond the Nyquist criterion 1:04:25 – Pitfalls and common misunderstandings 1:07:00 – Outro Links Brian Douglas's video: http://y2u.be/sof3meN96MA The Idea Factory: https://en.wikipedia.org/wiki/The_Idea_Factory Inventing the Negative Feedback Amplifier: https://doi.org/10.1109/MSPEC.1977.6501721 Johnson–Nyquist noise:  https://doi.org/10.1103/PhysRev.32.110 Nyquist sampling theorem: https://en.wikipedia.org/wiki/Nyquist%E2%80%93Shannon_sampling_theorem Regeneration theory: https://doi.org/10.1002/j.1538-7305.1932.tb02344.x Gain and phase margins: https://en.wikipedia.org/wiki/Bode_plot#Gain_margin_and_phase_margin Routh–Hurwitz criterion: https://en.wikipedia.org/wiki/Routh%E2%80%93Hurwitz_stability_criterion Åström’s lecture: https://archive.control.lth.se/media/Staff/KarlJohanAstrom/Lectures/ASMENyquistLecture2005.pdf Scale-Relative Graphs: https://doi.org/10.1109/TAC.2023.3234016 Support the show Podcast info Podcast website: https://www.incontrolpodcast.com/ Apple Podcasts: https://tinyurl.com/5n84j85j Spotify: https://tinyurl.com/4rwztj3c RSS: https://tinyurl.com/yc2fcv4y Youtube: https://tinyurl.com/bdbvhsj6 Facebook: https://tinyurl.com/3z24yr43 Twitter: https://twitter.com/IncontrolP Instagram: https://tinyurl.com/35cu4kr4 Acknowledgments and sponsors This episode was supported by the National Centre of Competence in Research on «Dependable, ubiquitous automation» and the IFAC Activity fund. The podcast benefits from the help of an incredibly talented and passionate team. Special thanks to L. Seward, E. Cahard, F. Banis, F. Dörfler, J. Lygeros, ETH studio and mirrorlake . Music was composed by A New Element.

  6. 16 Feb

    ep41 - A minimal history of optimal control

    Outline 00:00 - Intro 02:55 - Brachistochrone problem 20:52 - Beginning of the calculus of variations 32:00 - Principle of least action 42:37 - Maximum principle 1:02:35 - Dynamic programming 1:11:12 - Linear quadratic control 1:16:37 - Beyond optimal control: games, nonsmooth analysis, MPC, RL 1:28:40 - Outro Links 300 years of optimal control: https://tinyurl.com/2s3t8se4 Brachistochrone: https://tinyurl.com/mwmv38ew Acta Eruditorum, 1696: https://tinyurl.com/55yf5v49 Acta Eruditorum, 1697: https://tinyurl.com/2a7msaaj Bernoulli family: https://tinyurl.com/y2vx2xdn Leibniz–Newton calculus controversy: https://tinyurl.com/3974fdhd Calculus of variations: https://tinyurl.com/3vvz8tuf Beginning of the Calculus of Variations: https://tinyurl.com/mv6btxfn Lagrangian mechanics: https://tinyurl.com/ycx5fv46 Euler–Lagrange equation: https://tinyurl.com/53yybvyx Hamiltonian mechanics: https://tinyurl.com/yfrd8zhz Hamilton–Jacobi equation: https://tinyurl.com/46m9cuvs Pontryagin: https://tinyurl.com/35ehxnex Pontryagin’s autobiography:  https://ega-math.narod.ru/LSP/book.htm Discovery of the Maximum Principle: https://tinyurl.com/3s43nv4t Maximum Principle: https://tinyurl.com/4f7352t4 Goddard problem: https://tinyurl.com/5n8swp2m Hamilton–Jacobi–Bellman equation: https://tinyurl.com/4uemn5y4 Kalman filter: https://tinyurl.com/39zx5yry Clarke: https://tinyurl.com/yj2tzcjb MPC: https://tinyurl.com/4sf5pzvy RL: https://tinyurl.com/ee5ne7sz AlphaGo: https://tinyurl.com/ydrf8jsc Support the show Podcast info Podcast website: https://www.incontrolpodcast.com/ Apple Podcasts: https://tinyurl.com/5n84j85j Spotify: https://tinyurl.com/4rwztj3c RSS: https://tinyurl.com/yc2fcv4y Youtube: https://tinyurl.com/bdbvhsj6 Facebook: https://tinyurl.com/3z24yr43 Twitter: https://twitter.com/IncontrolP Instagram: https://tinyurl.com/35cu4kr4 Acknowledgments and sponsors This episode was supported by the National Centre of Competence in Research on «Dependable, ubiquitous automation» and the IFAC Activity fund. The podcast benefits from the help of an incredibly talented and passionate team. Special thanks to L. Seward, E. Cahard, F. Banis, F. Dörfler, J. Lygeros, ETH studio and mirrorlake . Music was composed by A New Element.

  7. 15 Jan

    ep40 - Jeff Shamma: gain scheduling, nonlinear control, learning & dissipativity in games, jiu-jitsu

    Outline 00:00 - Intro 03:18 - Early days: why control, M. Athans, and IDSS 12:21 - What is gain scheduling? 33:37 - Paradigm shifts & the ‘90s: Minnesota → Texas → LA 42:19 - Robustness & fundamental limitations of nonlinear systems 57:35 - Set-valued control & estimation 01:04:52 - Game theory & multi-agent control 01:28:18 - Learning & dissipativity in games & multi agent AI 01:45:03 - KAUST: building something new 01:53:33 - On human-algorithmic interaction 01:59:07 - Advice to future students: control, jiu-jitsu, and chatbots in education 2:10:02 - Outro Links Jeff’s website: https://tinyurl.com/52btmmz7 CSM interview: https://tinyurl.com/49wh98x7 Domain: feedbackcontrol.com M. Athans: https://tinyurl.com/nhbw66wa PhD thesis: https://tinyurl.com/5eyxkfm6 IDSS: https://tinyurl.com/bdenwy6d Research on gain scheduling: https://tinyurl.com/55se8zcr Overview of LPV systems: https://tinyurl.com/3ksff58b Åström’s lecture: https://tinyurl.com/33mxkkfe Necessity of the small gain theorem: https://tinyurl.com/mjn9eeb4 Sensitivity reduction for nonlinear plants: https://tinyurl.com/23tej5yp Respect the unstable: https://tinyurl.com/3yww5eds Differential inclusion: https://tinyurl.com/4yvc8vcc Lectures on game theory: https://tinyurl.com/4z8hh3rn Dynamic fictitious play: https://tinyurl.com/yc6wsxjj Cooperative control and potential games: https://tinyurl.com/4hbmrt72 Dissipativity theory in game theory: https://tinyurl.com/3theyc7x Population games, stable games, and passivity: https://tinyurl.com/zxwtzv6w Game theory and control: https://tinyurl.com/yencrwm3 Higher-order uncoupled learning: https://tinyurl.com/376r5r9x Support the show Podcast info Podcast website: https://www.incontrolpodcast.com/ Apple Podcasts: https://tinyurl.com/5n84j85j Spotify: https://tinyurl.com/4rwztj3c RSS: https://tinyurl.com/yc2fcv4y Youtube: https://tinyurl.com/bdbvhsj6 Facebook: https://tinyurl.com/3z24yr43 Twitter: https://twitter.com/IncontrolP Instagram: https://tinyurl.com/35cu4kr4 Acknowledgments and sponsors This episode was supported by the National Centre of Competence in Research on «Dependable, ubiquitous automation» and the IFAC Activity fund. The podcast benefits from the help of an incredibly talented and passionate team. Special thanks to L. Seward, E. Cahard, F. Banis, F. Dörfler, J. Lygeros, ETH studio and mirrorlake . Music was composed by A New Element.

  8. 16/12/2025

    ep39 - Female influencers in control

    Outline 00:00 - Intro 05:01 - Female Influencers in Control — The Backstory 08:08 - Sofya Kovalevskaya 15:21 - Irmgard Lotz 26:16 - A new wave of control influencers 34:26 - Some data 43:38 - What can one do?  1:00:10 - Exhibition + survey 1:05:21 - Outro Links Female influencers in control project: https://tinyurl.com/mv879ahf Charlotta Johnsson: https://tinyurl.com/343esbeu Eva Westin: https://tinyurl.com/3p6fd5n8 Margret Bauer: https://tinyurl.com/47d35xzb Sofya Kovalevskaya: https://tinyurl.com/4mmzruwc Remembering Sofya Kovalevskaya: https://tinyurl.com/4cpw7vff Irmgard Lotz: https://tinyurl.com/y2exmndm Flow Computation Pioneer Irmgard Flügge-Lotz (1903–1974): https://tinyurl.com/4cy3xsp3 Discontinuous Automatic Control: https://tinyurl.com/yeys5dxx Historical Female Influencers in Automatic Control: https://tinyurl.com/yxw4bjxe Activity report: https://tinyurl.com/jwzn4z3c Support the show Podcast info Podcast website: https://www.incontrolpodcast.com/ Apple Podcasts: https://tinyurl.com/5n84j85j Spotify: https://tinyurl.com/4rwztj3c RSS: https://tinyurl.com/yc2fcv4y Youtube: https://tinyurl.com/bdbvhsj6 Facebook: https://tinyurl.com/3z24yr43 Twitter: https://twitter.com/IncontrolP Instagram: https://tinyurl.com/35cu4kr4 Acknowledgments and sponsors This episode was supported by the National Centre of Competence in Research on «Dependable, ubiquitous automation» and the IFAC Activity fund. The podcast benefits from the help of an incredibly talented and passionate team. Special thanks to L. Seward, E. Cahard, F. Banis, F. Dörfler, J. Lygeros, ETH studio and mirrorlake . Music was composed by A New Element.

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About

The first podcast on control theory. inControl shop: https://incontrolpodcast.myshopify.com/

Information

  • Creator
    Alberto Padoan
  • Years Active
    2022 - 2026
  • Episodes
    46
  • Rating
    Explicit
  • Copyright
    © 2026 inControl
  • Show Website
    inControl

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