Causal Bandits Podcast

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*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) - Transportability
4:19 - 9:53 Patrick Altmeyer (Delft) - Explainability & black-box models
9:54 - 12:24 Lokesh Nagalapatti (IIT Bombay) - Continuous treatment effects
12:24 - 16:06 Golnoosh Farnadi (McGill University) - Causality & responsible AI
16:06 - 17:37 Markus Bläser (Saarland University) - Fast identification of causal parameters
17:37 - 22:37 Devendra Singh Dhami (TU/e) - The future of causal AI

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Causal Bandits Podcast
Causal AI || Causal Machine Learning || Causal Inference & Discovery
Web: https://causalbanditspodcast.com
Connect on LinkedIn: https://www.linkedin.com/in/aleksandermolak/
Join Causal Python Weekly: https://causalpython.io
The Causal Book: https://amzn.to/3QhsRz4

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*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?
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Video version available on Youtube:

https://youtu.be/8yWKQqNFrmY

Recorded on Mar 12, 2025 in Bengaluru, India.
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*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*

Listen on: Apple Podcasts Spotify

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Causal Bandits Podcast
Causal AI || Causal Machine Learning || Causal Inference & Discovery
Web: https://causalbanditspodcast.com
Connect on LinkedIn: https://www.linkedin.com/in/aleksandermolak/
Join Causal Python Weekly: https://causalpython.io
The Causal Book: https://amzn.to/3QhsRz4

Send us a text

Support the showVideo version available on YouTube
Recorded on Sep 4, 2023 in London, UK
A causal bet
Darko'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 top companies streamline and deploy causal inference workflows today.
Learn how his hedge fund experience shaped his thinking about business.
Causal Bandits Extra is a series of conversations with non-technically-focused people involved in or interested in causality from business, social and other perspectives.
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About The Guest
Darko Matovski, PhD is the co-founder and CEO of causaLens, a $50M venture-backed scaleup. He holds a PhD in Computer Science and an MBA from the University of Southampton.
Connect with Darko:
- Darko Matovski on LinkedIn: https://www.linkedin.com/in/matovski/
- causaLens web page
About The Host
Aleksander (Alex) Molak is an independent machine learning researcher, educator, entrepreneur and a best-selling author in the area of causal machine learning.
Connect with Alex:
- Alex on the Internet
Causal Bandits Team
Project Coordinator: Taiba Malik (https://www.instagram.com/taibasplay/) Video and Audio Editing: Navneet Sharma, Aleksander Molak *Action* Connect on LinkedIn: https://www.linkedin.com/in/aleksandermolak/ Join Causal Python Weekly: https://causalpython.io Causal Bandits: https://causalbanditspodcast.com The Causal Book: https://amzn.to/3QhsRz4 *Sponsorship Disclaimer* This episode has been made possible with the support of causaLens. We appreciate their contribution to making

Support the show

Causal Bandits Podcast
Causal AI || Causal Machine Learning || Causal Inference & Discovery
Web: https://causalbanditspodcast.com
Connect on LinkedIn: https://www.linkedin.com/in/aleksandermolak/
Join Causal Python Weekly: https://causalpython.io
The Causal Book: https://amzn.to/3QhsRz4

Send us a text

Support the show
Video version available on YouTube
Recorded on Sep 27, 2023 in München, Germany
From supply chain to large language models and back
Ishansh 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 and which causal discovery algorithms have been most effective for Ishansh's supply chain use case?
Hear the insights from one of the BMW Group's fastest-rising young data science talents.
Ready?
About The Guest
Ishansh Gupta is a Lead Data Scientist at BMW Group. Previously, he worked for several companies, including a legendary German sports club SV Werder Bremen. He studied Computer Science, and co-founded an educational startup during his study years. He has supervised or supported students in various universities, including the Munich-based TUM and MIT.
Connect with Ishansh:
- Ishansh on Twitter/X
- Ishansh on LinkedIn
About The Host
Aleksander (Alex) Molak is an independent machine learning researcher, educator, entrepreneur and a best-selling author in the area of causality
Connect with Alex:
- Alex on the Internet
Links
Papers
Full list of papers here
Books
- Molak (2023) -

Listen on: Apple Podcasts Spotify

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Causal Bandits Podcast
Causal AI || Causal Machine Learning || Causal Inference & Discovery
Web: https://causalbanditspodcast.com
Connect on LinkedIn: https://www.linkedin.com/in/aleksandermolak/
Join Causal Python Weekly: https://causalpython.io
The Causal Book: https://amzn.to/3QhsRz4

Send us a text

Support the show
Video version available on YouTube
Recorded on Nov 29, 2023 in Cambridge, UK
Should 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 the context of general machine learning. Her papers on heterogeneous treatment effect estimators and model evaluation bring unique perspectives to the community.
Her recent NeurIPS paper on double descent aims at bridging the gap between statistical learning theory and a counter-intuitive phenomenon of double descent observed in complex machine learning architectures.
Ready to dive in? ------------------------------------------------------------------------------------------------------ About The Guest
Alicia Curth is a Machine Learning Researcher and a final year PhD student at The van der Schaar Lab at Cambridge University. Her research is focused on causality, understanding machine learning methods from ground up and personalized medicine. Her works are frequently accepted at best machine learning conferences (she's a true serial NeurIPS author).
Connect with Alicia:
- Alicia on Twitter/X
- Alicia on LinkedIn
- Alicia 's web page
About The Host
Aleksander (Alex) Molak is an independen

Listen on: Apple Podcasts Spotify

Support the show

Causal Bandits Podcast
Causal AI || Causal Machine Learning || Causal Inference & Discovery
Web: https://causalbanditspodcast.com
Connect on LinkedIn: https://www.linkedin.com/in/aleksandermolak/
Join Causal Python Weekly: https://causalpython.io
The Causal Book: https://amzn.to/3QhsRz4