The recent black hole image, captured by the Event Horizon Telescope (EHT) – a network of eight linked telescopes – was rendered by Dr Bouman’s algorithm. Good article by Katy Steinmetz in Time Magazine online:
Though her work developing algorithms was a crucial to the project, Bouman sees her real contribution as bringing a way of thinking to the table. “What I did was brought the culture of testing ourselves,” she says. The project combined experts from all sorts of scientific backgrounds, ranging from physicists to mathematicians, and she saw the work through the lens of computer science, stressing the importance of running tests on synthetic data and making sure that the methods they used to make the image kept human bias out of the equation.
Bouman says that most of the time she’s not focused on the fact that she’s in a field where women are the minority. “But I do sometimes think about it. How do we get more women involved?” she says. “One key is showing that when you go into fields like computer science and engineering, it’s not just sitting in a lab putting together a circuit or typing on your computer.”
She plans to continue work with the Event Horizon Telescope team, which is adding satellite dishes in space to the network of telescopes here on Earth that were used to produce the image released on Wednesday. With the increased perspective and power, she says, they just might be able to make movies of black holes in addition to still images.
“It’s exciting,” she says. And that’s also her message for the next generation who might consider careers like hers. “As long as you’re excited and you’re motivated to work on it, then you should never feel like you can’t do it.”
Tracey Skivington, Electro-Optics Consultant, Thales UK
Tracey completed a B.Sc. (Hons) in Laser Physics and Optoelectronics followed by a Ph.D. in Physics and Applied Physics at the University of Strathclyde. From here, Tracey joined Thales as a laser engineer before moving into the field of electro-optics engineering.
Currently, Tracey works as an Electro-Optics Consultant within the Optronics and Missile Electronics (OME) domain within Thales.
Her area of expertise is in the modelling of electro-optics sensors across many different platforms, including land, sea and air. The sensor modelling includes, but is not limited to, colour TV cameras, laser rangefinders and designators, SWIR cameras, MWIR and LWIR Thermal Imaging technologies. Tracey also leads and manages the Glasgow OME Specialities team comprising of specialist engineers from disciplines in lasers, optics, electro-optics, algorithms and control systems.
Find out more about opportunities at Thales UK here
Kirstin Hay completed her PhD in Astrophysics at the University of St Andrews in early 2018 – her research focussed on using statistical and machine learning methods for the characterisation of exoplanet transits.
Since then, she has been working as a data scientist at Heineken UK, applying the techniques and methods from scientific research to solve business problems. Having a PhD in itself wasn’t a requirement to work at Heineken but the experience she gained through doing it meant she had lots of evidence of the right skill set.
Ewan shows how a degree in Physics can take you in interesting directions.
Ewan Hemingway, Research Engineer, Canon Medical Research Europe
I first studied physics at Edinburgh University for the Computational Physics MPhys degree. I was interested in acoustics at the time and my Masters project looked at numerical modelling of guitar value amplifiers. However, one of the 5th year elective courses that really grabbed my attention was a series on soft matter physics, and this prompted me to pursue PhD opportunities. Following a recommendation, I joined an EPSRC-funded PhD in the Physics department at Durham University. There I worked on various problems in computational fluid dynamics, specifically in the area of active matter (the study of living fluids).
I was also lucky to gain some industrial experience through a consultation / research project with Schlumberger.
After my PhD, I stayed in Durham for two more years as a post-doc, where I focused on modelling flow instabilities in polymer physics.
Most recently, I joined Canon as a research engineer in the Image Analysis group. I have been there for just under a year, but already I have worked on a range of interesting problems, e.g., using deep learning for image segmentation.