Causal Bandits Podcast
Causal Bandits Podcast, hosted by Alex Molak, explores causality, causal AI, and causal machine learning through conversations with leading experts. The show bridges academia and industry, philosophy and practice, and different schools of thought within causality. Alex Molak, a machine learning engineer and author, travels to record interviews with influential minds in the field. Listeners learn about causal inference, causal discovery, and related topics. Stay causal!
Episodes
AI's Fluency Is Not Understanding | Elias Bareinboim S3E02 | CausalBanditsPodcast.com
Send us Fan MailThis episode was created in collaboration with the UBC Causal AI Cluster: https://aicausal.ubc.ca/Ask an image model what happens when you flip the switch on a desk lamp, and many will show it lit, even when the cable is lying on the desk, unplugged.The lamp is only the easiest instance. The same thing happens wherever the question is about an action or a change the data never show
Spaceflight Epidemiologist's Grand DAG | Robert Reynolds, PhD S3E01 | CausalBanditsPodcast.com
Send us Fan MailJoin the UBC Causal AI Cluster launch eventIn-person & online on October 8, 2026More on the event here How do you build a causal model when only a few hundred people in history have ever been your population?Robert J. Reynolds was brought into NASA to answer questions difficult to settle with a simple experiment: what threatens astronauts health and how to make sure that counte
Can You Trust It? (One Day, 140K Downloads) | Isaac Gerber S2E12 | CausalBanditsPodcast.com
Send us Fan MailHow do you trust causal inference code that no human has read?On New Year's Day this year, Isaac Gerber was a little bored. A week later he had shipped diff-diff, a difference-in-differences library that has since crossed 140,000 downloads, built almost entirely by AI agents. In this conversation we get into how he makes causal inference software he can actually stand behind,
Strait of Hormuz: Causal Models for Rare Events | Alexander Denev S2E11 | CausalBanditsPodcast.com
Send us Fan Mail*How do you forecast an event that has never happened before?*How do you forecast an event that has never happened before?The recent closure and reopening of the Strait of Hormuz are unique events. For events like these, traditional risk models lose their statistical basis: repetition. Alexander Denev returns to the podcast to show how causal models (Bayesian networks) let us reaso
Causality, Experimentation, and Marketplaces | Lawrence De Geest S2E10
Send us Fan MailCausality, Experimentation, and MarketplacesMeet Lawrence de Geest (Zoox, ex-Lyft, ex-NBA), a former soccer player and an ex-NBA data scientist, who fell in love with marketplaces, despite the fact he hated math.In the episode we ponder how to deal with causality when our interventions change the dynamics of the environment we intervene upon, what to do with SUTVA violations, and h
Do Heterogeneous Treatment Effects Exist? | Stephen Senn X Richard Hahn S2E9 | CausalBanditsPodcast
Send us Fan MailDo 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
Causal Inference & the "Bayesian-Frequentist War" | Richard Hahn S2E8 | CausalBanditsPodcast.com
Send us Fan Mail*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
The Causal Gap: Truly Responsible AI Needs to Understand the Consequences | Zhijing Jin S2E7
Send us Fan MailThe 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 th
Create Your Causal Inference Roadmap. Causal Inference, TMLE & Sensitivity | Mark van der Laan S2E6 | CausalBanditsPodcast.com
Send us Fan MailCreate 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
Causal Inference, Human Behavior, Science Crisis & The Power of Causal Graphs | Julia Rohrer S2E5 | CausalBanditsPodcast.com
Send us Fan Mail*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 huma
MSFT Scientist: Agents, Causal AI & Future of DoWhy | Amit Sharma S2E4 | CausalBanditsPodcast.com
Send us Fan Mail*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, ca
Causal Secrets of N=1 Experiments | Eric Daza S2E3 | CausalBanditsPodcast.com
Send us Fan Mail 📽️ 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 hereAbo
From Quantum Physics to Causal AI at Spotify | Ciarán Gilligan-Lee S2E2 | CausalBanditsPodcast.com
Send us Fan MailFrom 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 p
49% Less Loss with Causal ML | Stefan Feuerriegel S2E1 | CausalBanditsPodcast.com
Send us Fan MailStefan 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 becaus
Causal AI at cAI 2024 London | CausalBanditsPodcast.com
Send us Fan MailCausal 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
Causal Bandits @ CLeaR 2024 | Part 2 | CausalBanditsPodcast.com
Send us Fan MailWhich 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
Causal Bandits @ CLeaR 2024 | Part 1 | CausalBanditsPodcast.com
Send us Fan MailRoot 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 -
Causal Bandits @ AAAI 2024 | Part 2 | CausalBanditsPodcast.com
Send us Fan Mail *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 - 1
Causal Bandits @ AAAI 2024 | Part 1 | CausalBanditsPodcast.com
Send us Fan Mail 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 & sel
Free Will, LLMs & Intelligence | Judea Pearl Ep 21 | CausalBanditsPodcast.com
Send us Fan MailMeet 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
Causal AI & Individual Treatment Effects | Scott Mueller Ep. 20 | CausalBanditsPodcast.com
Send us Fan MailCan 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
Causal AI in Personalization | Dima Goldenberg Ep 19 | CausalBanditsPodcast.com
Send us Fan MailVideo 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 ch
Causal Inference for Drug Repurposing & CausalLib | Ehud Karavani Ep 18 | CausalBanditsPodcast.com
Send us Fan MailWas 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 c
From Physics to Causal AI & Back | Bernhard Schölkopf Ep 17 | CausalBanditsPodcast.com
Send us Fan Mail 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 etholo
Open Source Causal AI & The Generative Revolution | Emre Kıcıman Ep 16 | CausalBanditsPodcast.com
Send us Fan Mail 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
Why Hinton Was Wrong, Causal AI & Science | Thanos Vlontzos Ep 15 | CausalBanditsPodcast.com
Send us Fan MailRecorded 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
Causal Inference & Financial Modeling with Alexander Denev Ep 14 | CausalBanditsPodcast.com
Send us Fan MailVideo 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 Analytic
Causal Inference & Reinforcement Learning with Andrew Lampinen Ep 13 | CausalBanditsPodcast.com
Send us Fan MailLove 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 h
Causal Inference, Clinical Trials & Randomization || Stephen Senn || Causal Bandits Ep. 012 (2024)
Send us Fan MailSupport 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 c
Causal Models, Biology, Generative AI & RL || Robert Ness || Causal Bandits Ep. 011 (2024)
Send us Fan MailSupport 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, generativ
Causal AI & Supply Chain || Ishansh Gupta || Causal Bandits Ep. 010 (2024)
Send us Fan MailSupport 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 i
On Causal Inference in Fintech & Being an Author || Matheus Facure || Causal Bandits Ep. 009 (2024)
Send us Fan MailSupport 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 l
Causal ML, Transparency & Time-Varying Treatments || Iyar Lin || Causal Bandits Ep. 008 (2024)
Send us Fan MailSupport 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 stati
![[Extra]: Mosquitos, Pascal & Hedge Funds || A Walk with Darko Matovski, PhD (causaLens) in London (2024)](https://storage.buzzsprout.com/w1dk33de06vqbo2gkjrtda4pcsnn?.jpg)
[Extra]: Mosquitos, Pascal & Hedge Funds || A Walk with Darko Matovski, PhD (causaLens) in London (2024)
Send us Fan MailSupport 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
Causal AI, Justin Bieber & Optimal Experiments || Jakob Zeitler || Causal Bandits Ep. 007 (2024)
Send us Fan MailSupport 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 hi
Causal AI, Effect Heterogeneity & Understanding ML || Alicia Curth || Causal Bandits Ep. 006 (2023)
Send us Fan MailSupport 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
Causal AI & Dynamical Systems || Naftali Weinberger || Causal Bandits Ep. 005 (2023)
Send us Fan MailSupport 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 di
Autonomous Driving, Causality & Long Tails || Daniel Ebenhöch || Causal Bandits Ep. 004 (2023)
Send us Fan MailSupport 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 work
Causality, Marketing & Simulations || Juan Orduz || Causal Bandits Ep. 003 (2023)
Send us Fan MailSupport 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
Causal AI, Modularity & Learning || Andrew Lawrence || Causal Bandits Ep. 002 (2023)
Send us Fan MailSupport 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
Causality, Bayesian Modeling and PyMC || Thomas Wiecki || Causal Bandits Ep. 001 (2023)
Send us Fan MailSupport 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
Causality, LLMs & Abstractions || Matej Zečević || Causal Bandits Ep. 000 (2023)
Send us Fan MailSupport 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 struc
