I am an Assistant Professor in the School of Computing, Funded Investigator at the INSIGHT Centre for Data Analytics and the Advanced Manufacturing Research Centre, Dublin City University. My expertise is in Artificial Intelligence (AI) and how to build machines that “learn” and “think”, to help us understand the world and make better, faster decisions. This spans across so many domains, including health, business, education, manufacturing, climate change and social behaviour.
If I weren’t an academic scientist, I would probably be gigging around as I was the lead singer and piano player in a band for over 10 years.
Has your opinion of STEM changed since you were a teenager?
I didn’t know what STEM was back then. In my childhood I loved art and music, playing the piano at the age of 5, spending hours watching my father painting on Sundays and competing with him. Then as I progressed in school I was the perfect student, or so my mum recalls. I was always keen to find answers to my questions. And I had loads of questions. “But why?” was my favourite, I used to drive my teachers and my parents nuts! Sometimes I would get vague answers and so often I went off to the library (the internet later on) to dig deeper and find better answers for myself. This is how my passion for STEM grew bigger since me teenage years, probably as I saw answers being more objective and rewarding for me, or maybe because I was not as competitive in music and arts. Anyway, I decided I wanted to be a scientist, a learner but also a teacher, and this is how I got into my head the idea that one day I would be an academic scientist. Back then I kept thinking: “I want to be happy to go to work every day. So if they pay me to find cool questions about the world and look for new answers, why not?” I did not imagine, back then, it would be so cool and that I would love my job so much.
In your opinion, what is the biggest myth about STEM careers?
As somebody who loved music and art, I think the biggest myth about STEM careers is that they do not involve creativity, that it is just a boring world of numbers and formulas. It is not the case. This is the most creative career you can imagine. Science is about explaining what you can observe, and sometimes predict what is going to happen. Think about the ability to build a self-driving car. You ask yourself what it needs. It needs to see, to calculate distances, to understand road signs, to predict what could happen on the road. Then you ask yourself how you are going to make that happen. You need cameras as its eyes, and infrared sensors to measure distances, and a “brain” to know what sign means what etc.. it is like being Geppetto building Pinocchio and you tell me that’s not creative? Even magic I would say.
Do you believe that there is enough being done to encourage girls and minorities to study STEM and pursue STEM careers?
Stereotypes are the biggest danger. It is not something people do consciously. BBC showed an interesting experiment where they dressed baby boys as girls and vice versa, put them in a room with some toys and a volunteer adult to play with them. The experiment showed how you can actually gender-stereotype children in the toys you choose for them. It all starts really early though. And can be reverted. For example, initiatives like Girls Hack Ireland are very successful in introducing girls to computing, but I think more can be done in primary and secondary school. If you feel like somebody else is telling you what you are good or not good at, and you do not agree, you do not have to follow, as they are probably pushing you in the wrong direction.
What do you love about your current role?
I constantly learn new things. And I do not learn by locking myself in the library the whole day. I learn from my students, from my colleagues, from people I talk to, who are often working in different fields I know very little about. There is always something new to think about, some other question to answer.
What has been the most surprising element of your job?
Probably the fact that when we try to showcase our technology, we find ourselves talking to the most unlikely people and we find out we can do something for them. The application of what we do in domains we never thought of, is fascinating. For example, we have a program, running on a normal laptop, that learned to recognise an image from a fashion catalogue, telling you if it is a jumper, a bag, a pair of trousers and so on. In Mullingar, there are colleagues working on a 3-D printer that builds metal parts (bolts but the same principle applies to hip prosthesis or airplane engine parts), layer after layer, a very expensive process. A layer is built by a laser melting a metal powder which then solidifies. For each layer, their printing machine also creates a coloured picture made of blue, green, yellow and red pixels. The colours represent the intensity of different aspects in the process, such as how hot is the laser, how strong are the emissions from the powder when the laser hits, how long does it take for the powder to cool off, and so on. They have all this information but they do not have a way to automatically process it and use it. For example, they struggle trying to figure out, manually, whether something goes wrong in the printing process: they have to wait till the parts are finished, take each of the hundred parts and test them to see if they resist under pressure or they break (meaning a defect occurred during printing). They would save a lot of money and time if they could know before they finish printing the parts, so they could just pause the process and throw away the bad part. What does it have to do with recognising pictures of fashion items? Well, we found a way to teach our program to recognise, from the images of the layers, when a layer is ok versus when there is a hole or a defect, using the same principle. We are still working on it, but this can have a great impact on safer and more cost effective 3-D printing of metals. The same principle we used to recognise hand-written digits and letters (they are images after all!) so in principle we can teach our machine to read handwriting.
What has been your most exciting career moment to date?
It is difficult for me to pick one day only. Any intervention in the media is actually exciting as you get to talk to the general public about what you do. I remember one recently, being interviewed by Dublin City FM on the outcome of a project funded by the European Commission on Smart Cities, which also featured in the top ranked scientific journal in the field, that was an exciting achievement.
Do you get to work with any new technologies?
All the time. The exciting part of my job is using the latest technology for something new for which this technology has not been used before. We need to collect data for our machine to learn things, and to collect data we often need sensors. We used all sorts of sensors not only for capturing images, audio and video, but also for measuring things in the environment (things like temperature, light, pollution, traffic) on objects (things like distance, acceleration) and on people (things like heart rate, body sweat, body movements). The problem is then what to do with all this, how to make sense of it all without having to go through all the numbers. For example in a project with city administrators we had an app (like google maps) suggesting a cyclist in real time the healthiest path to take based on traffic, pollution, bike speed, heart rate and other data, so that he could be on time wherever he needed to be, but also maximise both health and road safety.
Do you ever get to travel abroad for work?
More than I would like. Now I probably want to spend more time with my family and kids but when I was on my own, I travelled a lot. There are so many reasons to travel: to conferences, to project meetings, to field-trip. I also went to Saudi Arabia as a visiting professor to a women-only university. I went all over Europe, and some places in America and Africa too. I met many interesting people and great long lasting collaborations and connections came out of those trips, as well as friendships.
What kind of other experts do you work with on a day to day basis?
On a day-to-day basis I currently talk to people in Computing, Engineering, Health and Manufacturing. However, what we do in my team can be applied to so many fields that we find ourselves talking to many different people within specific projects. To mention some: earth scientists, city administrators, lawyers, criminal police, medical doctors.
Is your current job, and the work of the wider team, making a difference in the world?
I think we are and certainly will continue to. We are pushing the boundaries of technology and Artificial Intelligence, helping machines to make sense of the world so they can help us live longer and better.
Do you feel that you fit the stereotypical description of a person in your role?
I think there is no stereotypical description of a person in my role, really. That is the good of it, you can be what you are and reinvent yourself.
If a young person told you that they would like to get into your role, what advice would you give them?
Make a plan. A short, medium and long term plan. Be flexible and ready to change the plan if needed. Never lose track of your goal, of where you want to get. Find a good mentor, somebody you trust and respect that can advise you, and get as much feedback as you possibly can.
Did you complete any sort of placement or internship during your studies? If so, did it prepare you for what you do now?
No I did not as it was not part of the programme when and where I studied. Talking to different people about what I liked helped me find what I wanted to be… In a way I felt the call for being a scientist and working in academia but I could not listen to that straight away. My father wanted me to be an accountant. We did not have career advisers. My family pushed me to get a job and so I did, with the agreement that after one year I would have had a chance to rethink about it. They thought I would give up on the idea of pursuing further education once I got my first salary and felt settled in my working routine. I didn’t, and eventually I ended up back onto my path.
Do you feel secure in the fact that you can earn a living from a career in Stem?
I didn’t know it back then, and the way it started in my country it was really challenging. That is why I left and came over to Ireland. It was not long till my hard work and my achievements started to pay off.
What television series are you currently watching?
Stranger Things brings me back to the 80s, the time I grew up. And it reminds me of ET.
The Crown, as I am really bad at history and it is an easy way of understanding part of it.
Grey’s Anatomy: unfortunately Dr. House is no longer airing but I like all those weird medical cases.
How to Get Away with Murder, gets me thinking and trying to make sense of it all.