MSFT Scientist: Agents, Causal AI & Future of DoWhy | Amit Sharma S2E4 | CausalBanditsPodcast.com
Send 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 for validating causal models now available in DoWhy—impact the way we build and interact with causal models in industry?------------------------------------------------------------------------------------------------------Video version available on Youtube: https://youtu.be/8yWKQqNFrmYRecorded on Mar 12, 2025 in Bengaluru, India.------------------------------------------------------------------------------------------------------*About The Guest*Amit Sharma is a Principal Researcher at Microsoft Research and one of the original creators of the open-source Python library DoWhy, considered the "scikit-learn of causal inference." He holds a PhD in Computer Science from Cornell University. His research focuses on causality and its intersection with LLM-based and agentic systems. Amit deeply cares about the social impact of machine learning systems and sees causality as one of the main drivers of more useful and robust systems.Connect with Amit:- Amit on LinkedIn: https://www.linkedin.com/in/amitshar/- Amit on BlueSky:- Amit 's web page: http://amitsharma.in/*About The Host*Aleksander (Alex) Molak is an independent machine learning researcher, educator, entrepreneur and a best-selling author in the area of causality (https://amzn.to/3QhsRz4 ).Connect with Alex:- Alex on the Internet: https://bit.ly/aleksander-molakSupport the showCausal Bandits PodcastCausal AI || Causal Machine Learning || Causal Inference & DiscoveryWeb: https://causalbanditspodcast.comConnect on LinkedIn: https://www.linkedin.com/in/aleksandermolak/Join Causal Python Weekly: https://causalpython.io The Causal Book: https://amzn.to/3QhsRz4
--------
1:10:10
Causal Secrets of N=1 Experiments | Eric Daza S2E3 | CausalBanditsPodcast.com
Send 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 experience (Cornell, UNC Chapel Hill, Stanford). He works at Boehringer Ingelheim. Eric is a creator of Stats-of-1, a health innovation newsletter & podcast on n-of-1 trials, single-case designs, switchback experiments, and personal AI for digital health/medicine.All views and opinions expressed by Dr. Eric J. Daza represent no one but himself. These views and opinions do not represent the views and opinions of his employer.Connect with Eric:Eric on LinkedInEric on BlueSkyEric's web pageAbout The HostConnect with Alex:Alex on the Internet 👉🏼 Consulting and Causal AI Training For Your Team: hello <at> causalpython.ioEpisode LinksPapersDaza (2018) - "Causal Analysis of Self-tracked Time Series Data Using a Counterfactual Framework for N-of-1 Trials"Matias, Daza et al (2022) - "What possibly affects nighttime heart rate? Conclusions from N-of-1 observational data"BooksAsimov, I (1991) - "Foundation"AppsStudyUWebpagesStats-of-1Support the showCausal Bandits PodcastCausal AI || Causal Machine Learning || Causal Inference & DiscoveryWeb: https://causalbanditspodcast.comConnect on LinkedIn: https://www.linkedin.com/in/aleksandermolak/Join Causal Python Weekly: https://causalpython.io The Causal Book: https://amzn.to/3QhsRz4
--------
1:01:14
From Quantum Physics to Causal AI at Spotify | Ciarán Gilligan-Lee S2E2 | CausalBanditsPodcast.com
Send 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 understanding of physics and quantum causal models with applied work at Spotify, solving complex problems in innovative ways.Recently, while collaborating with one of his students, he stumbled upon a new interesting question: could we learn something about the early history of the universe by applying causal inference methods in astrophysics?Could we? Hear it from Ciarán himself.Join us for this one-of-a-kind conversation!------------------------------------------------------------------------------------------------------Video version and episode links available on YouTubeRecorded on Nov 6, 2024 in Dublin, Ireland.------------------------------------------------------------------------------------------------------About The GuestCiarán Gilligan-Lee is Head of the Causal Inference Research Lab at Spotify and Honorary Associate Professor at University College London. He got interested in causality during his studies in quantum physics. This interest led him to study quantum causal models. He published in Nature Machine Intelligence, Nature Quantum Information, Physical Review Letters, New Journal of Physics and more. In his free time, he writes for New Scientist and helps his students apply causal methods in new fields (e.g., astrophysics).Connect with Ciarán:- Ciarán on LinkedIn: https://www.linkedin.com/in/ciaran-gilligan-lee/- Ciarán's web page: https://www.ciarangilliganlee.com/About The HostAleksander (Alex) Molak is an independent machine learning researcher, educator, entrepreneur Support the showCausal Bandits PodcastCausal AI || Causal Machine Learning || Causal Inference & DiscoveryWeb: https://causalbanditspodcast.comConnect on LinkedIn: https://www.linkedin.com/in/aleksandermolak/Join Causal Python Weekly: https://causalpython.io The Causal Book: https://amzn.to/3QhsRz4
--------
52:10
49% Less Loss with Causal ML | Stefan Feuerriegel S2E1 | CausalBanditsPodcast.com
Send 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 I hope you'll enjoy it too!>> Guest info:Stefan Feuerriegel is a professor and the Head of the Institute of AI in Management at LMU. Previously, he worked as a consultant at McKinsey & Co. and ran his own AI startup.>> Episode Links:Papers- Feuerriegel, S. et al. (2024) - Causal machine learning for predicting treatment outcomes (https://www.nature.com/articles/s41591-024-02902-1)- Kuzmanivic, M. et al. (2024) - Causal Machine Learning for Cost-Effective Allocation of Development Aid (https://arxiv.org/abs/2401.16986)- Schröder, M. et al. (2024) - Conformal Prediction for Causal Effects of Continuous Treatments (https://arxiv.org/abs/2407.03094)>> WWW: https://www.som.lmu.de/ai/>> LinkedIn: https://www.linkedin.com/in/stefan-feuerriegel/Support the showCausal Bandits PodcastCausal AI || Causal Machine Learning || Causal Inference & DiscoveryWeb: https://causalbanditspodcast.comConnect on LinkedIn: https://www.linkedin.com/in/aleksandermolak/Join Causal Python Weekly: https://causalpython.io The Causal Book: https://amzn.to/3QhsRz4
--------
28:35
Causal AI at cAI 2024 London | CausalBanditsPodcast.com
Causal Bandits Podcast with Alex Molak is here to help you learn about causality, causal AI and causal machine learning through the genius of others. The podcast focuses on causality from a number of different perspectives, finding common grounds between academia and industry, philosophy, theory and practice, and between different schools of thought, and traditions. Your host, Alex Molak is an a machine learning engineer, best-selling author, and an educator who decided to travel the world to record conversations with the most interesting minds in causality to share them with you.Enjoy and stay causal!Keywords: Causal AI, Causal Machine Learning, Causality, Causal Inference, Causal Discovery, Machine Learning, AI, Artificial Intelligence
México