Jun 2, 2016 · announcement

Welcome, Friederike!

Alongside our research on emerging machine learning techniques, Fast Forward Labs advises organizations on data science issues like technical architecture, new product development, models and algorithms, and even hiring the right talent. Our client base is growing fast, and we’re excited to support many large financial services, insurance, and media companies, as well as startups building cutting-edge AI products. 

We work closely with our clients to identify opportunities where they can apply our research and take our prototypes the next mile by implementing them on their own data. And we’re delighted to announce a new team member who will be focused on mapping our technology to client business problems. Welcome, Friederike! 

As Research Strategist, Friederike will be the bridge between Fast Forward Labs clients and our internal research and product teams. She’ll help clients use their data creatively and gather feedback to inform our future research. We’re excited to have her on board and to introduce her to the community!

What did you do before joining Fast Forward Labs?

Most recently, I helped academics transition into data science as a Program Director at Insight Data Science. I helped fellows build their own portfolio data product, from ideation through the choice and implementation of machine learning techniques and algorithms.

Prior to Insight, I was a data scientist at Oscar Health. I worked with medical data and learned a lot about how legislation can impact the day-to-day operations of a rapidly growing company. By law, insurance companies have to spend at least 85% of revenue on clinical services, and that creates a lot of work for the data science team! 

Like the rest of the team at Fast Forward Labs, I’m a reformed academic. I got my PhD in Cognitive Neuroscience at University College, London and did a postdoc at New York University. 

Why did you join Fast Forward Labs?

Fast Forward Labs has an eye both on the recent developments in applied machine intelligence research and the companies that use - or will use -machine intelligence to develop products. I am excited about the current and future applications of machine intelligence, how the algorithms impact companies and products, and, by extension, how they will change the way we live and work.

But not all challenges in machine intelligence are technical. I loved how Fast Forward Labs pays as much attention to the human and ethical side of machine intelligence as the technical side. Teams implement data products, and strong teams produce better results. And not all data products are good for the world: machine learning is tricky, and some algorithms perpetuate bias or are hard to interpret. I joined Fast Forward Labs because it has a rare, unique focus on all aspects of machine intelligence: the technical, the human, and the ethical.

What will you be working on at Fast Forward Labs?

At Fast Forward Labs, we research new machine learning techniques, like deep learning for image recognition (as in Pictograph) and automatic document summarization (as in Brief). We also help our clients find new, creative opportunities to use their data, be that to automate internal processes or create new, revenue-generating products. In my role, I’ll work to understand client business problems and translate our research to impact their teams and products.

When you’re not working, what do you like to do?

Books, music, data. I’ve been into the Latin American authors of late, like Jorge Luis Borges, Roberto Bolaño and Cesar Aira. Music, everything from experimental, electronic and classical, to the comforting hum of low-frequency drone. More data? Yes! Last year, I organized a hackathon on healthcare data and I am helping with a hackathon on the TreeCount! data, the most comprehensive data on the trees of New York City. Data is playing a larger role in society at large: today, it seems like basic civic duties like casting a vote require an understanding of how data is generated, processed, and presented. I love helping to foster a tech and data community welcoming and accessible to all.

And a final fun fact: I’ve lived in five different countries!