A big part of research is data, but for the Mendeley Data Sciences team, data is all they research. The team makes a big deal of big data, acting as wizards in our Mendeley world, magically bringing bits together. The Data Science team links data and projects, and connects research and business to build better products, such as the paper recommender and social networks. Collaboration is key to making the most of big data, and our Data Science team is constantly involved with conferences, meetings and internal talks to help connect Mendeley to the world of research.

Kris Jack

Chief Data Scientist

@_krisjack

Kris joined Mendeley in 2010. He has a wide range of experience in Data Science both in industry and academia.

He obtained BSc Hons in Computer Science at the University of Dundee in 2002, followed by a PhD in 2006. Following that, Kris was employed as an Expert R&D Engineer in France Telecom until 2008 then at the Commissariat à l’Énergie Atomique until 2009. Before joining Mendeley, he worked as a Research Associate at the University of Manchester in their Text Mining team.

How do you describe your role on the Data Science Team?

I’m responsible for leading the Data Science team, making way for them to do great work and hopefully pitching in myself along the way.

What is your favourite part about working for Mendeley?

Knowing that we’re making a difference to how research gets done. As a researcher myself, I know how hard research is and how much easier we could make it with the right tools to support us.

What do you enjoy doing in your free time?

Relaxing with my family.

 

Phil Gooch

Senior Data Scientist

Phil joined Mendeley in June 2014. He’s been conjuring structured knowledge from unstructured text within STM publishing and in academia for several years.

Prior to Mendeley, Phil worked for Oxford University Press as a Language Technologist. He completed a PhD in Health Informatics in 2012. Following this, he worked as a Research Associate for the University of Sheffield in their Natural Language Processing group, and as Research Developer in Digital Humanities at Kings College, London. In previous career-lives, Phil worked as a rehab therapist in the NHS, a computer games programmer, and musician.

@Phil_Gooch

How do you describe your role on the Data Science Team?

I contribute expertise in natural language processing and information extraction, so that as a Data Science team, and in collaboration with our Platform team, we can create useful – and hopefully exciting! – tools for researchers.

What is your favourite part about working for Mendeley?

I love working with text, and developing workflows and tools to uncover the knowledge and connections that are buried in the vast amount of research literature. Also, working with the really smart people here who can work the magic to turn prototype code into something production-worthy!

What do you enjoy doing in your free time?

Long walks in the countryside with family and friends, being by the sea, cycling, writing music, enjoying the arts.

 

Maya Hristakeva

Senior Data Scientist

Machine learning is Maya’s passion and she has focused her entire career thus far in this space by developing algorithms and building software within start-up organisations. Before moving to the UK in 2010, Maya was a Machine Learning PhD student at University of California- Santa Cruz. She also worked as a Researcher at Silicon Valley based startup C8 Medisensors, where she developed algorithms to non-invasively measure blood sugar in people (using ramen spectroscopy – no needles).

After moving to the UK, Maya worked at Mendeley before the Elsevier acquisition as a Data Mining Engineer. Then, I joined Cognitive Match, another startup, as a Sr. Research Scientist focusing on using machine learning techniques for behavioral targeting and recommendations.

Within 2 years my path crossed with Mendeley again after the Elsevier acquisition. She is happy to be back working as a member of the Data Science team where we are focused on the next generation of solutions to help our users connect to their research and to other collaborators in innovative, valuable ways.

How do you describe your role on the Data Science Team?

I work on building recommender systems to help researchers contextualise their work within the global body of research, and connect them with relevant researchers, groups and articles.

What is your favourite part about working for Mendeley?

I enjoy the creative working environment, lots of smart and diverse people, as well as having the latest technologies at my fingertips. I also love that Mendeley reaches millions of people with our products and makes a difference in researchers’ lives.

What do you enjoy doing in your free time?

Wine, Food, Kickboxing, Argentine Tango, and Traveling (but not necessarily in that order)