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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 we learn about human psychology from building causal recommender systems?
- What it's like to work in a culture of radical experimentation?
- Why you should not skip your operations research classes?
Ready to dive in?
About The Guest
Dima Goldenberg is a Senior Machine Learning Manager at Booking.com, Tel Aviv, where he leads machine learning efforts in recommendations and personalization utilizing uplift modeling. Dima obtained his MSc in Tel Aviv University and currently pursuing PhD on causal personalization at Ben Gurion University of the Negev. He led multiple conference workshops and tutorials on causality and personalization and his research was published in top journals and conferences including WWW, CIKM, WSDM, SIGIR, KDD and RecSys.
Connect with Dima:
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
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Causal AI || Causal Machine Learning || Causal Inference & Discovery
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