Dafna Shahaf has so many cool research projects. In this episode we talked about a few of them - using metro maps to visualize information about events and storylines; an algorithm that judges jokes; a search engine that finds creative solutions using analogies; finding surprising facts in wikipedia. She tells us how she comes up with these ideas, how she choses which ones to focus on and about her way of "failing fast".

David Golan was on the track to becoming a university professor. Then something happened that made him changed route. He co-founded viz.ai - a company that helps doctors detect strokes quickly. We talked about How to use Deep Learning when you don't have a lot of data; about the challenges in building an AI-oriented company in the field of medicine; and about how the time he spent as a researcher helps him as an entrepreneur.

Yair Mazor is the head of Data Science at windward. In this episode we talked about how to efficiently getting into new domain as a data scientist, about data science for maritime analytics and about different aspects in managing data science teams: the pros and cons of working as teams of data scientists vs. being a part of product and development teams; balancing between short and long term research goals; working with product managers and finally - can data scientists work in agile?

Ofra Amir did her PhD in computer science in Harvard, where she studied the interactions between humans and intelligent machines. In this episode we talk with Ofra about designing algorithms whose goal is to improve human performance in a given task, how to design metrics when some of your goals are not easily measurable, and how to explain the decisions of intelligent agents to humans.

Yo data scientists, Nimrod Priell has a very important message for you - Data Science is much more than just Machine Learning. It may sound trivial when you think about it, but yet it's very easy to forget these days. Nimrod, a Data Science team lead at facebook, told us about 7 different products of a data scientist (only one of which is a machine learning model!), about the two metrics he uses to evaluate a product, and how it helps him to manage data science projects and build a versatile and diverse team. We found this talk very interesting, and hope you do too.

In this episode we talked with Sefi Cohen, head of Data Science squad in the IDF. He tells us about the different projects they're doing and how he started a Data Science team with very little knowledge of Machine Learning and Data Science techniques, how he chose the right people for this team and how they all learned the craft together.

Uri Shalit did his Ph.d at the Hebrew University and a post doc in NYU. We talked about his research in machine learning for Health Care and what are the unique challenges in this field, about Causal Inference and how it is relevant to many machine learning problems, and about a cool study he did during his Ph.d about Motif identification in music.

What's it like to be the only data scientist at a company? What mistakes companies do when building their data science team and how to avoid them? And what did it feel like when Intel acquired Mobileye? Galit Bary Weisberg is here to answer all of these questions.

On the first episode we talked with Yoav Goldberg from Bar Ilan university about NLP, deep learning research, life in academia and that medium blog post that started a fire. Click on the episode name to get a list of resources related to what we talked about.

In this short episode we tell you a bit about this podcast and about ourselves.