Profile of Viorica Pătrăucean

Viorica is a Research Associate in the Centre for Smart Infrastructure and Construction (CSIC)

This interview was originally published on the CSIC website as part of a series of interviews which showcase the talent and diversity of women working in science and engineering with CSIC.

With thanks to Viorica, Lisa Millard and the CSIC team for allowing us to reproduce the interview here.

How and why did you get into engineering?

It was at high school in Romania that I had my first encounter with computer programming and it was love at first sight. Being able to programme a computer to solve a task fully automatically seemed to me very empowering and restructured my approach towards problem solving. From that moment I knew I wanted to study and work in a field close to computer programming. And I chose computer engineering for college and continued with a Masters and PhD in computer science.

What is your current position and what does it entail?

I am a research associate within CSIC, working mainly on designing and applying state-of-the-art machine learning techniques for geometric and semantic modelling of large-scale outdoor structures. Basically, we train a machine to recognise objects and their shape from images and videos.

What motivates/interests you about what you do?

Besides computer science, I am also fascinated by the inner workings of the human brain – the most complex, beautiful, and mysterious object of study.  In my work I use deep artificial neural networks, which attempt to mimic the way a human brain learns. While solving practical problems, this also helps understanding better how the human brain works.

What has helped shape your career – people, colleagues, family?

I have been extremely lucky to always have by my side people who encouraged me to do what I like and taught me that hard work is the key to every problem. 

What have you gained from working with CSIC?

The main quality that characterises CSIC from my point of view is diversity. I had the chance to work with and learn from experts with very different backgrounds, from academia and industry. It has been very challenging and enriching. I gained knowledge in different fields, the ability to communicate better with different people, and very importantly, I gained new insights into my work as a result of seeing the bigger picture that integrates my work.

How have you overcome challenges/knockbacks in your working life?

Research can be tough; the solutions to the problems we try to solve are almost never obvious. But I understood that this is the beauty of it. The more challenging the problem, the more satisfied I am when finding a solution. I have learned to believe in my ideas and trust my collaborators and to take their criticism as an important source of improvement.  

What is the best thing about what you do?

Learning, in any form or context, is the most interesting and important aspect of life. In research, learning is part of the daily routine and it's the best part of my work. 

Where would you like to see your career going? What’s next?

I will soon be joining a top research lab – Google DeepMind in London – as a research scientist. I will be working in close collaboration with machine learning and neuroscience experts, with the goal of creating artificial agents with human-level intelligence.

Do you have any role models?

Everybody who can teach me something new about a topic that I am interested in becomes, at least temporarily, a role model for me.

What do you think might encourage more women to work in science and engineering?

There might be a general misconception among girls/women that science and engineering are rigid, abstract fields. But this is not the case at all. They are fields with direct impact on society, and solving a problem always requires a combination of knowledge, creativity, determination, and rigour.

Do you have any advice for women who may be considering pursuing a career in this area?

This goes for any field: work hard for what you truly like and fascinates you. Even if it's a male dominated field, be yourself and don't try to behave/look like a man.