Shows
Causal Bandits PodcastDo Heterogeneous Treatment Effects Exist? | Stephen Senn X Richard Hahn S2E9 | CausalBanditsPodcastSend us a textDo Heterogeneous Treatment Effects Exist?For the last 50 years, we've designed cars to be safe...For the 50th-percentile male.Well, that's actually not 100% correct.According to Stanford's report, we introduced "female" crash test dummies in the 1960s, but...They were just scaled-down versions of male dummies and...Represented the 5th percentile of females in terms of body size and mass (aka the smallest 5% of women in the general population).These dummies also did not take into account...
2026-01-301h 07
Causal Bandits PodcastCausal Inference & the "Bayesian-Frequentist War" | Richard Hahn S2E8 | CausalBanditsPodcast.comSend us a text*What can we learn about causal inference from the “war” between Bayesians and frequentists?*What can we learn about causal inference from the “war” between Bayesians and frequentists?In the episode, we cover:- What can we learn from the “war” between Bayesians and frequentists?- Why do Bayesian Additive Regression Trees (BART) “just work”?- Do heterogeneous treatment effects exist?- Is RCT generalization a heterogeneity problem?In the episode, we accidentally coined a new term: “feature-level selection bias.”...
2025-12-271h 24
Causal Bandits PodcastThe Causal Gap: Truly Responsible AI Needs to Understand the Consequences | Zhijing Jin S2E7Send us a textThe Causal Gap: Truly Responsible AI Needs to Understand the ConsequencesWhy do LLMs systematically drive themselves to extinction, and what does it have to do with evolution, moral reasoning, and causality?In this brand-new episode of Causal Bandits, we meet Zhijing Jin (Max Planck Institute for Intelligent Systems, University of Toronto) to answer these questions and look into the future of automated causal reasoning.In this episode, we discuss:- Zhijing's new work on the "causal scientist"- What's missing...
2025-10-301h 03
Causal Bandits PodcastCreate Your Causal Inference Roadmap. Causal Inference, TMLE & Sensitivity | Mark van der Laan S2E6 | CausalBanditsPodcast.comSend us a textCreate Your Causal Inference Roadmap. Causal Inference, TMLE & SensitivityIf you're into causal inference and machine learning you probably heard about double machine learning (DML).DML is one of the most popular frameworks leveraging machine learning algorithms for causal inference, while offering good statistical properties.Yet...There's another framework that also leverages machine learning for causal inference that was created years earlier.Welcome to the world of targeted maximum likelihood estimation (TMLE).Our today's guest, Prof. Mark van der...
2025-09-221h 29
Causal Bandits PodcastCausal Inference, Human Behavior, Science Crisis & The Power of Causal Graphs | Julia Rohrer S2E5 | CausalBanditsPodcast.comSend us a text*Causal Inference From Human Behavior, Reproducibility Crisis & The Power of Causal Graphs*Is Jonathan Heidt right that social media causes the mental health crisis in young people?If so, how can we be sure?Can other disciplines learn something from the reproducibility crisis in Psychology, and what is multiverse analysis?Join us for a conversation on causal inference from human behavior, the reproducibility crisis in sciences, and the power of causal graphs!------------------------------------------------------------------------------------------------------Audio version available on YouTube: https://youtu.be...
2025-06-041h 21
Causal Bandits PodcastMSFT Scientist: Agents, Causal AI & Future of DoWhy | Amit Sharma S2E4 | CausalBanditsPodcast.comSend us a text*Agents, Causal AI & The Future of DoWhy*The idea of agentic systems taking over more complex human tasks is compelling.New "production-grade" frameworks to build agentic systems pop up, suggesting that we're close to achieving full automation of these challenging multi-step tasks.But is the underlying agentic technology itself ready for production?And if not, can LLM-based systems help us making better decisions?Recent new developments in the DoWhy/PyWhy ecosystem might bring some answers.Will they—combined with new methods fo...
2025-04-141h 10
Causal Bandits PodcastCausal Secrets of N=1 Experiments | Eric Daza S2E3 | CausalBanditsPodcast.comSend us a text 📽️ FREE Online Course on Causality 📕 Causal Inference & Discovery in PythonCausal Secrets of N=1 ExperimentsJoin me for a one of a kind conversation on the opportunities and challenges of n-of-1 trials, Eric's causal journey, his path into statistics, his love of sci-fi, and how single-subject experiments could reshape personalized medicine.Video version available hereAbout The GuestDr. Eric J. Daza is a biostatistician and health data scientist with over 22 years of exp...
2025-03-311h 01
Causal Bandits PodcastFrom Quantum Physics to Causal AI at Spotify | Ciarán Gilligan-Lee S2E2 | CausalBanditsPodcast.comSend us a textFrom Quantum Causal Models to Causal AI at SpotifyCiarán loved Lego.Fascinated by the endless possibilities offered by the blocks, he once asked his parents what he could do as an adult to keep building with them.The answer: engineering.As he delved deeper into engineering, Ciarán noticed that its rules relied on a deeper structure. This realization inspired him to pursue quantum physics, which eventually brought him face-to-face with fundamental questions about causality.Today, Ciarán blends his deep und...
2025-01-2952 min
Causal Bandits Podcast49% Less Loss with Causal ML | Stefan Feuerriegel S2E1 | CausalBanditsPodcast.comSend us a textStefan Feuerriegel is the Head of the Institute of AI in Management at LMU.His team consistently publishes work on causal machine learning at top AI conferences, including NeurIPS, ICML, and more.At the same time, they help businesses implement causal methods in practice.They worked on projects with companies like ABB Hitachi, and Booking.com.Stefan believes his team thrives because of its diversity and aims to bring more causal machine learning to medicine.I had a great conversation with him, and...
2025-01-1728 min
Causal Bandits PodcastCausal AI at cAI 2024 London | CausalBanditsPodcast.comSend us a textCausal Bandits at cAI 2024 (The Royal Society, London)The cAI Conference in London slammed the door on baseless claims that causality cannot be used in industrial practice.In the episode of Causal Bandits Extra we interview participants and speakers at Causal AI Conference London, who share their main insights from the event, and the challenges they face in applying causal methods in their everyday work.Time codes:00:29 - Eyal Kazin (Zimmer Biomet)01:44 - Athanasios Vlontzos (Spotify)04:02 - Mimie Liotsiou (Dunnhumby)06:13 - Fernanda Hinze...
2024-12-0920 min
Causal Bandits PodcastCausal Bandits @ CLeaR 2024 | Part 2 | CausalBanditsPodcast.comSend us a textWhich models work best for causal discovery and double machine learning?In this extra episode, we present 4 more conversations with the researchers presenting their work at the CLeaR 2024 conference in Los Angeles, California.What you'll learn:- Which causal discovery models perform best with their default hyperparameters?- How to tune your double machine learning model?- Does putting your paper on ArXiv early increase its chances of being accepted at a conference?- How to deal with causal representation learning with multiple latent interventions?
2024-10-2822 min
Causal Bandits PodcastCausal Bandits @ CLeaR 2024 | Part 1 | CausalBanditsPodcast.comSend us a textRoot cause analysis, model explanations, causal discovery.Are we facing a missing benchmark problem?Or not anymore?In this special episode, we travel to Los Angeles to talk with researchers at the forefront of causal research, exploring their projects, key insights, and the challenges they face in their work.Time codes:0:15 - 02:40 Kevin Debeire2:41 - 06:37 Yuchen Zhu06:37 - 10:09 Konstantin Göbler10:09 - 17:05 Urja Pawar17:05 - 23:16 William OrchardEnjoy!Support the showCausal Bandits Podcast
2024-10-0722 min
Causal Bandits PodcastCausal Bandits @ AAAI 2024 | Part 2 | CausalBanditsPodcast.comSend us a text *Causal Bandits at AAAI 2024 || Part 2*In this special episode we interview researchers who presented their work at AAAI 2024 in Vancouver, Canada.Time codes: 00:12 - 04:18 Kevin Xia (Columbia University) - Transportability4:19 - 9:53 Patrick Altmeyer (Delft) - Explainability & black-box models9:54 - 12:24 Lokesh Nagalapatti (IIT Bombay) - Continuous treatment effects12:24 - 16:06 Golnoosh Farnadi (McGill University) - Causality & responsible AI16:06 - 17:37 Markus Bläser (Saarland University) - Fast identification of causal parameters17:37 - 22:37 Devendra Singh Dhami (TU/e) - The future of causal AI Support the...
2024-09-2322 min
Causal Bandits PodcastCausal Bandits @ AAAI 2024 | Part 1 | CausalBanditsPodcast.comSend us a text Causal Bandits at AAAI 2024 || Part 1In this special episode we interview researchers who presented their work at AAAI 2024 in Vancouver, Canada and participants of our workshop on causality and large language models (LLMs)Time codes:00:00 Intro00:20 Osman Ali Mian (CISPA) - Adaptive causal discovery for time series04:35 Emily McMilin (Independent/Meta) - LLMs, causality & selection bias07:36 Scott Mueller (UCLA) - Causality for EV incentives12:41 Andrew Lampinen (Google DeepMind) - Causality from passive data15:16 Ali Edalati (Huawei) - About Causal Parrots workshop
2024-09-1019 min
Causal Bandits PodcastFree Will, LLMs & Intelligence | Judea Pearl Ep 21 | CausalBanditsPodcast.comSend us a textMeet The Godfather of Modern Causal InferenceHis work has pretty literally changed the course of my life and I am honored and incredibly grateful we could meet for this great conversation in his home in Los AngelesTo anybody who knows something about modern causal inference, he needs no introduction.He loves history, philosophy and music, and I believe it's fair to say that he's the godfather of modern causality.Ladies & gentlemen, please welcome, professor Judea Pearl.Subscribe to never...
2024-08-1254 min
Causal Bandits PodcastCausal AI & Individual Treatment Effects | Scott Mueller Ep. 20 | CausalBanditsPodcast.comSend us a textCan we say something about YOUR personal treatment effect?The estimation of individual treatment effects is the Holy Grail of personalized medicine.It's also extremely difficult.Yet, Scott is not discouraged from studying this topic.In fact, he quit a pretty successful business to study it.In a series of papers, Scott describes how combining experimental and observational data can help us understand individual causal effects.Although this sounds enigmatic to many, the intuition behind this mechanism is simpler...
2024-07-2252 min
Causal Bandits PodcastCausal AI in Personalization | Dima Goldenberg Ep 19 | CausalBanditsPodcast.comSend us a textVideo version of this episode is available here Causal personalization?Dima did not love computers enough to forget about his passion for understanding people.His work at Booking.com focuses on recommender systems and personalization, and their intersection with AB testing, constrained optimization and causal inference.Dima's passion for building things started early in his childhood and continues up to this day, but recent events in his life also bring new opportunities to learn.In the episode, we discuss:What can...
2024-07-011h 06
Causal Bandits PodcastCausal Inference for Drug Repurposing & CausalLib | Ehud Karavani Ep 18 | CausalBanditsPodcast.comSend us a textWas Deep Learning Revolution Bad For Causal Inference?Did deep learning revolution slowed down the progress in causal research?Can causality help in finding drug repurposing candidates?What are the main challenges in using causal inference at scale?Ehud Karavani, the author of the CausalLib Python library and Researcher at IBM Research shares his experiences and thoughts on these challenging questions.Ehud believes in the power of good code, but for him code is not only about software development....
2024-06-1753 min
Causal Bandits PodcastFrom Physics to Causal AI & Back | Bernhard Schölkopf Ep 17 | CausalBanditsPodcast.comSend us a text Causal AI: The Melting Pot. Can Physics, Math & Biology Help Us?What is the relationship between physics and causal models?What can science of non-human animal behavior teach causal AI researchers?Bernhard Schölkopf's rich background and experience allow him to combine perspectives from computation, physics, mathematics, biology, theory of evolution, psychology and ethology to build a deep understanding of underlying principles that govern complex systems and intelligent behavior.His pioneering work in causal machine learning has revolutionized the field, providing new insights th...
2024-06-0334 min
Causal Bandits PodcastOpen Source Causal AI & The Generative Revolution | Emre Kıcıman Ep 16 | CausalBanditsPodcast.comSend us a text What makes two tech giants collaborate on an open source causal AI package?Emre's adventure with causal inference and causal AI has started before it was trendy. He's one of the original core developers of DoWhy - one of the most popular and powerful Python libraries for causal inference - and a researcher focused on the intersection of causal inference, causal discovery, generative modeling and social impact.His unique perspective, inspired by his experience with low-level programming combined with his vivid interest in how humans i...
2024-05-2042 min
Causal Bandits PodcastWhy Hinton Was Wrong, Causal AI & Science | Thanos Vlontzos Ep 15 | CausalBanditsPodcast.comSend us a textRecorded on Jan 17, 2024 in London, UK. Video version available hereWhat makes so many predictions about the future of AI wrong?And what's possible with the current paradigm?From medical imaging to song recommendations, the association-based paradigm of learning can be helpful, but is not sufficient to answer our most interesting questions.Meet Athanasios (Thanos) Vlontzos who looks for inspirations everywhere around him to build causal machine learning and causal inference systems at Spotify's Advanced Causal Inference Lab.In...
2024-05-061h 05
Causal Bandits PodcastCausal Inference & Financial Modeling with Alexander Denev Ep 14 | CausalBanditsPodcast.comSend us a textVideo version available here Are markets efficient, and if not, can causal models help us leverage the inefficiencies?Do we really need to understand what we're modeling?What's the role of symmetry in modeling financial markets?What are the main challenges in applying causal models in finance?Ready to dive in? About The GuestAlexander Denev is the CEO of Turnleaf Analytics. He's an author of multiple books on financial modeling and a former Head...
2024-04-151h 04
Causal Bandits PodcastCausal Inference & Reinforcement Learning with Andrew Lampinen Ep 13 | CausalBanditsPodcast.comSend us a textLove Causal Bandits Podcast?Help us bring more quality content: Support the showVideo version of this episode is available hereCausal Inference with LLMs and Reinforcement Learning Agents?Do LLMs have a world model?Can they reason causally?What's the connection between LLMs, reinforcement learning, and causality?Andrew Lampinen, PhD (Google DeepMind) shares the insights from his research on LLMs, reinforcement learning, causal inference and generalizable agents.We also discuss the nature of intelligence...
2024-04-0155 min
Causal Bandits PodcastCausal Inference, Clinical Trials & Randomization || Stephen Senn || Causal Bandits Ep. 012 (2024)Send us a textSupport the showVideo version available on YouTubeDo We Need Probability?Causal inference lies at the very heart of the scientific method. Randomized controlled trials (RCTs; also known as randomized experiemnts or A/B tests) are often called "the golden standard for causal inference".It's a less known fact that randomized trials have their limitations in answering causal questions.What are the most common myths about randomization?What causal questions can and cannot be answered with...
2024-03-181h 18
Causal Bandits PodcastCausal Models, Biology, Generative AI & RL || Robert Ness || Causal Bandits Ep. 011 (2024)Send us a textSupport the showVideo version available on YouTube Recorded on Nov 12, 2023 in Undisclosed location, Undisclosed locationFrom Systems Biology to CausalityRobert always loved statistics.He went to study systems biology, driven by his desire to model natural systems.His perspective on causal inference encompasses graphical models, Bayesian inference, reinforcement learning, generative AI and cognitive science.It allows him to think broadly about the problems we encounter in modern AI research. Is the reward enough...
2024-03-041h 13
Causal Bandits PodcastCausal AI & Supply Chain || Ishansh Gupta || Causal Bandits Ep. 010 (2024)Send us a textSupport the showVideo version available on YouTubeRecorded on Sep 27, 2023 in München, GermanyFrom supply chain to large language models and backIshansh realized the potential of data when he was just 10 years old, during his time as a junior cricket player. His journey led him to ask questions about the mechanisms behind the observed events. Can large language models (LLMs) help in building an industrial causal graph? What inspires stakeholders to share their knowledge an...
2024-02-1958 min
Causal Bandits PodcastOn Causal Inference in Fintech & Being an Author || Matheus Facure || Causal Bandits Ep. 009 (2024)Send us a textSupport the showVideo version of this episode is available on YouTubeRecorded on Oct 15, 2023 in São Paulo, BrazilCausal Inference in Fintech? For Brave and True OnlyFrom rural Brazil to one of the country’s largest banks, Matheus’ journey could inspire many. Similarly to our previous guest, Iyar Lin, Matheus was interested in politics, but switched to economics, where he fell in love with math. Observing the state of the industry, he quickly realized that without causa...
2024-02-051h 07
Causal Bandits PodcastCausal ML, Transparency & Time-Varying Treatments || Iyar Lin || Causal Bandits Ep. 008 (2024)Send us a textSupport the showVideo version available on YouTube Recorded on Sep 13, 2023 in Beit El'Azari, Israel The eternal dance between the data and the modelEarly in his career, Iyar realized that purely associative models cannot provide him with the answers to the questions he found most interesting. This realization laid the groundwork for his search for methods that go beyond statistical summaries of the data. What started as a lonely journey, led him to become a data science lead...
2024-01-2256 min
Causal Bandits Podcast[Extra]: Mosquitos, Pascal & Hedge Funds || A Walk with Darko Matovski, PhD (causaLens) in London (2024)Send us a textSupport the showVideo version available on YouTubeRecorded on Sep 4, 2023 in London, UKA causal betDarko's story begins in Eastern Europe, where his early attempts in building a business and the influence of early-stage role models shaped his attitudes and helped him move through challenging and lonely moments in his career. See how mosquitos, Pascal programming language, and problems with generalization in vision models inspired Darko to build a company that helps some of the world's...
2024-01-1622 min
Causal Bandits PodcastCausal AI, Justin Bieber & Optimal Experiments || Jakob Zeitler || Causal Bandits Ep. 007 (2024)Send us a textSupport the showVideo version of this episode is available hereRecorded on Sep 5, 2023 in Oxford, UKHave you ever wondered if we can answer seemingly unanswerable questions? Jakob's journey into causality started when he was 12 years old. Deeply dissatisfied with what adults had to offer when asked about the sources of causal knowledge, he started to look for the answers on his own. He studied philosophy, politics and economics to find his place at UCL's Centre...
2024-01-081h 08
Causal Bandits PodcastCausal AI, Effect Heterogeneity & Understanding ML || Alicia Curth || Causal Bandits Ep. 006 (2023)Send us a textSupport the showVideo version available on YouTube Recorded on Nov 29, 2023 in Cambridge, UKShould we continue to ask why? Alicia's machine learning journey began with... causal machine learning. Starting with econometrics, she discovered semi-parametric methods and the Pearlian framework at later stages of her career and incorporated both in her everyday toolkit. She loves to understand why things work, which inspires her to ask "why" not only in the context of treatment effects, but also in...
2023-12-2754 min
Causal Bandits PodcastCausal AI & Dynamical Systems || Naftali Weinberger || Causal Bandits Ep. 005 (2023)Send us a textSupport the showVideo version available on YouTubeRecorded on Aug 29, 2023 in München, GermanyCan we meaningfully talk about causality in dynamical systems?Some people are puzzled when it comes to dynamical systems and the idea of causation.Dynamical systems well-known in physics, social sciences, and biology are often thought of as a special family of systems, where it might be difficult to meaningfully talk about causal direction. Naftali Weinberger devoted his career to examining the relationships between s...
2023-12-111h 18
Causal Bandits PodcastAutonomous Driving, Causality & Long Tails || Daniel Ebenhöch || Causal Bandits Ep. 004 (2023)Send us a textSupport the showVideo version available on YouTubeRecorded on Aug 27, 2023 in München, GermanyIs Causality Necessary For Autonomous Driving?From a child experimenter to a lead engineer working on a general causal inference engine, Daniel's choices have been marked by intense curiosity and the courage to take risks.Daniel shares how working with mathematicians differs from working with physicists and how having both on the team makes the team stronger. We discuss the journey Daniel and his t...
2023-11-2752 min
Causal Bandits PodcastCausality, Marketing & Simulations || Juan Orduz || Causal Bandits Ep. 003 (2023)Send us a textSupport the show Video version available on YouTubeRecorded on Aug 25, 2023 in Berlin, Germany Is Marketing Intrinsically Causal? After spending 5 years talking to mathematicians, Juan decided to look for new opportunities that would offer him more immediate impact on the world. Little did he know that this journey will lead him to become a Senior Data Scientist at Wolt - one of the global food delivery leaders with operations in 25 countries. In this episode we discuss Juan's journey towards...
2023-11-1653 min
Causal Bandits PodcastCausal AI, Modularity & Learning || Andrew Lawrence || Causal Bandits Ep. 002 (2023)Send us a textSupport the show`from causality import solution`Recorded on Sep 04, 2023 in London, United KingdomA Python package that would allow us to address an arbitrary causal problem with a one-liner does not yet exist.Fortunately, there are other ways to implement and deploy causal solutions at scale. In this episode, Andrew shares his journey into causality and gives us a glimpse into the behind-the-scenes of his everyday work at causaLens. We discuss new ideas that Andrew and his team...
2023-11-071h 24
Causal Bandits PodcastCausality, Bayesian Modeling and PyMC || Thomas Wiecki || Causal Bandits Ep. 001 (2023)Send us a textSupport the showVideo version of this episode is available on YouTubeRecorded on Aug 24, 2023 in Berlin, GermanyDoes Causality Align with Bayesian Modeling? Structural causal models share a conceptual similarity with the models used in probabilistic programming. However, there are important theoretical differences between the two. Can we bridge them in practice? In this episode, we explore Thomas' journey into causality and discuss how his experience in Bayesian modeling accelerated his understanding of basic causal concepts. ...
2023-11-0758 min
Causal Bandits PodcastCausality, LLMs & Abstractions || Matej Zečević || Causal Bandits Ep. 000 (2023)Send us a textSupport the showVideo version of this episode available on YouTubeRecorded on Aug 14, 2023 in Frankfurt, GermanyAre Large Language Models (LLMs) causal? Some researchers have shown that advanced models like GPT-4 can perform very well on certain causal benchmarks. At the same time, from the theoretical point of view it's highly unlikely that these models can learn causal structures. Is it possible that large language models are not causal, but talk causality? In our conversation we explore this...
2023-11-061h 10