Meet the HelloScience Team – Pedro
Meet Pedro, Data Scientist, Entrepreneur and Startup Founder
HelloScience is constantly working to increase the ways in which we can support collaborations across ecosystems. To that end, we’re putting a major focus around how we can leverage the power of artificial intelligence and data infrastructure to help support and drive collaborations further. This month, we sit down with data scientist Pedro Parraguez to learn more about his background and vision for building stronger data and A.I. tools into the HelloScience platform in the months ahead.
Could you tell us a bit about your background and interests?
I always live in a duality between being a data researcher and applying research in society.
As a researcher, I seek to answer interesting and open-ended questions that push the boundaries of what we know. That’s what I did for quite a few years in the areas of engineering systems – analyzing things like research and development ecosystems. In these areas, I ask things like – what we can learn from the dynamics of these complex networks? Then, at the other end of the spectrum, I work trying to translate this research into tools that can be applied more directly in society and in businesses. This should also enable us to better understand how researchers work and engineers so that we can support better feedback loops.
Data Natives, Conference. 2018
Now, as an entrepreneur and start-up founder, I’m now focusing on what I call capability mapping and matchmaking. This essentially means trying to better understand what we are able to do as groups of people. In this case this means to map what scientists and engineers are working on and how we can use the building blocks they create in the past to build new things together.
For example, with HelloScience, we are building out the infrastructure that the platform is built on to add in more features that seek to use capability mapping and matchmaking elements to enhance collaboration. This is currently “work in progress” and we hope to have some great results later in the year.
How are you applying this work and research with HelloScience?
The problem that we always face is that as science and technology gets more and more complex, we increasingly end up – often building without first realizing– information or knowledge “silos” in order to manage that complexity. But we also need mechanisms to be able to see across those silos, and to do so in a smart way that helps makes the right connections between them.
The great and unique nature of HelloScience is that it naturally brings together companies and researchers with an impact first mentality. To have such an interface between the private sector, academia and NGOs is not so common, and the more you can be that interface, the more things can happen that are hard to replicate elsewhere.
“The question for us, working on behalf of the HelloScience Community, is how can we take advantage of all of the knowledge, insights and add value using data that is otherwise is dormant or that is not necessarily connected to other parts of the platform or larger R&D ecosystem.“
Working with Alfred and the HelloScience Team, we have been thinking about ways of making HelloScience smarter through what we call the ‘engine room’ or the backend infrastructure of the platform. The question for us, working on behalf of the HelloScience Community, is how can we take advantage of all of the knowledge, insights and value using data that is otherwise is dormant or is not necessarily connected to other parts of the platform or larger R&D ecosystem?
This is why we are focusing our work on capability mapping and matchmaking – so that we can build on top of the HelloScience ecosystem and make better connections both inside and outside of the platform.
What are you hoping to achieve through these collaborations?
Well, I certainly hope that we can show with the HelloScience platform that you can transform the way a company or an organization works, and how a community works, when they collaborate on very big and crucial sustainability challenges.
We believe that by getting the right combination of the current qualitative work behind the platform – the people on the ground that know how to facilitate collaborations – with a process for building more effective analytics and use data for good – we can get far more impact faster, and with the same or maybe less resources.
How will these developments change the way people engage on the HelloScience platform?
In the beginning, the work we’re doing with data and analytics will show up as relatively subtle nudges and cues like recommendations on projects you might be interested in, that will become smarter over time. All of these things are part of a gradual process, but as we go further this year and next year, we should be able to see that the recommendations become increasingly more effective in fostering meaningful insights, relationships and collaborations.
And from there, we should also start bringing in more people, projects, and knowledge from outside the core of the existing HelloScience community – for example: research outputs or mentorship connections that are highly relevant for what a user within the platform is looking at, just at the right the moment to give new perspectives and insights.
That is definitely something I’m very much looking forward to seeing play a role on the platform – because it’s not about quantity, really, it’s about quality. And that focus on the quality of the interactions and concrete real-world impact is at the heart of HelloScience.