Authors

Maya Hristakeva (m<last name>@gmail.com) is a Lead Data Scientist at Mendeley and RELX group working on building tools to help researchers connect to their research and to collaborators. Her research interests are in the areas of scalable machine learning, recommender systems and optimization algorithms. She is also interested in the end-to-end process of building data products: from algorithms to good user experience.

https://twitter.com/mayahhf

Kris Jack (mr<first name><last name>@gmail.com) is the Chief Data Scientist at Mendeley and Head of Data Science in the RELX group.  He’s passionate about making software that helps people to understand and communicate complex information as well as make new discoveries.  His main research interests lie in the fields of Recommendation Systems, Information Retrieval, Information Extraction, Machine Learning, and Artificial Intelligence.  He’s also passionate about transforming technology into useful products for real users and the team dynamics involved in getting stuff done.

https://twitter.com/_krisjack

Together, Maya and Kris have brought a number of recommender systems into the world.  Their most recent product is called Mendeley Suggest, a recommender system for researchers.

Guest Authors

Michael Ekstrand (<lastname>@acm.org) is an Assistant Professor in the Department of Computer Science at Texas State University. His primary research interests are on human dimensions of intelligent information systems, with a particular focus on recommenders, working to make these tools truly beneficial to the people that they impact. He also leads the LensKit project to support reproducible research on recommender systems through open-source research tooling.

https://md.ekstrandom.net

https://twitter.com/mdekstrand

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