How I Changed from Science to Technology

by Azahara Fernández Guizán


How I changed from Science to Technology

I was never a kid that was sure about what professional career I wanted when I grew up. And this has been a good thing for me, because it has let me experience many different fields, and led me to where I am today.

I was born in the north of Spain, in a mining zone of Asturias. My father was a coal miner and my mother a housewife. I attended a local school and a local high school. My grandmother says I was an unusual kid, preferring to be bought a book rather than a box of sweets. I also started learning English when I was 6 years old, and spent my free time reading historical novels and biographies.

I enjoyed visiting museums and monuments, and I used to search for information in my town’s library before going on an excursion. I loved to write stories and tales, and had always obtained high marks in school, which led my teachers to suggest that I study medicine. But I always changed my mind –  from architecture, to journalism or even dentistry, depending on the book I was reading or the museum I’d just visited.

At that age, only one thing was clear: I wanted to be an independent and strong woman like the ones that inspired me. I hadn’t seen many role models during my primary education, but one teacher told us about Marie Curie. At the library, I discovered Rita Levi-Montalcini and the Brontë sisters.



During the last year of high-school I was a mess, and the pressure was high because I had to make a decision. All I had were doubts

In Spain at that time, after finishing your last secondary education course, the students that want to continue to a degree have to take a general exam, the PAU. You could choose the subjects you want to be tested on and, after the exams took place, you were given a mark calculated to take account of your secondary school marks and the results of PAU exams. According to this mark, you could register for certain degrees.

At that point, I decided to take more exams than necessary on the PAU in order to have more options in different types of degree, for example, science, engineering, or languages… But the worst moment of my student life came, and I had to decide.

I had two options on my mind: a Software Engineering degree, and a Biology degree. I must admit it, but at that time I only knew engineering stereotypes and I never liked video games or anything related with hardware, so I decided that a Biology degree would suit me better.


During my degree, I decided that plants and animals were not my passion, but I loved Microbiology, Genetics, Immunology and Neuroscience. I discovered more female role models, researchers who really inspired me, whose lives were incredible to me. I worked hard during my degree and travelled a lot during the summers, thanks to some scholarships that I was awarded (I spent one month in Lowestoft, another in Dublin, and another one in Toronto), and started learning German.


Azahara in the lab

During the second year of my biology degree, I decided that I would become a scientist, and started to look for a professor who would let me gain some experience in their laboratory.

During my penultimate year, I started working in a Neuroscience laboratory, studying the 3D eye degenerating pattern on C3H/He rd/rd mice. After finishing my degree, I decided to enrol in a Masters of Neuroscience and Behavioural Biology in Seville. During this masters, I worked in another Neuroscience laboratory doing electrophysiological studies, trying to understand how information is transformed in the cerebellar hippocampus circuit and how this mechanism could allow us to learn and memorise.

This was a period of my life where I worked a lot of hours, the experiments were very intense, and I had the opportunity to meet important scientist from all the world. I also had a physics peer that analysed all our data, and developed specific programmes in Matlab, which impressed me profoundly.


After this period, I continued working in Science, but I decided to start my PhD on Immunology, back in Asturias.

I worked in a laboratory in which, due to my friends in the lab, every day was special. We worked hard studying different types of tumours and testing different molecules, but also had the time to share confidences and laughs. After three years, I became a PhD in Immunology, and as it was the normal thing to do, I started looking for a post-doc position.

Rather than feeling happy or enthusiastic about the future, I discovered myself being upset and demotivated. I really didn’t want to carry on being a scientist. A huge sensation of failure invaded me, but as J.K. Rowling said “It is impossible to live without failing at something, unless you live so cautiously that you might as well not lived at all. In which case, you’ve failed by default”.

I want to specify that I don’t consider my PhD a waste of time – it has given me, apart from scientific publications, many important aptitudes and abilities, such as team work, analysis, problem solving, leadership, organisation skills, effective work habits, and better written and oral communication.


As you might imagine, this was a hard moment of my life. I was unemployed, and doubtful about my professional career – just as I had been after high school.

Thanks to my husband, who supported me while converting my career, I decided to give software development a try.  As I didn’t have the necessary money or time to start a new degree, I signed up for a professional course in applications software development. The first days were difficult since all the other students were young and I didn’t feel at ease.

But as I learned software languages as HTML, CSS, JavaScript and Java, I also participated with good results in some software competitions which allowed me to gain confidence.


In 2015 I started working as software developer in .Net MVC, a language that I hadn’t studied during my course, but I had the necessary basics to learn it quickly and become part of a team. For me, one of the most marvellous things about software development is that it consists of team-work.

I also discovered that there are a lot of people working in this field that love to exchange knowledge, and I regularly go to events and meetups. I have also started recently giving talks, and workshops, some of them technological, with the aim of promoting the presence of women in technology.


Women and girls need to be encouraged to discover what software development really is. The software industry needs them. Software can be better, but only if it is developed by diverse teams with different opinions, backgrounds, and knowledge.


Women are literally boring….

By: Laurie Winkless

Tunnels, that is. All over the world, Tunnel Boring Machines (or TBMs) are chewing their way through the packed subterranean network of your nearest city. But something you might not know is that they’re all given women’s names. Naming a machine after a human isn’t that weird, right? Many of us have named our cars after all, but it goes a bit deeper for TBMs. According to tunnelling tradition, a TBM cannot start work until it is officially named. But exactly where we got the tradition of naming them after women remains a bit of a mystery.

Some sources suggest that it comes from the 16th century, when miners, armourers, and artillerymen prayed to Saint Barbara. Legend has it that Barbara’s father had locked her in a windowless tower when he found out about her conversion to Christianity. Later, a flash of lightning struck him dead, and since then, all trades associated with darkness and the use of explosives have recognised Barbara as their patron saint. Today’s tunnel engineers see themselves as fitting that description, and so give TBMs women’s names in Barbara’s honour. Others suggest that the tradition comes from the link between miners and ship-builders – their physical strength and similar skills often saw men switch between trades as the need arose. Boats have long been given the pronoun ‘she’ (again for reasons unknown), so perhaps using women’s names for tunnelling machines started there?

Regardless of its beginnings, this tradition is carried out throughout the world today, as a sign of good luck for the project ahead. And, perhaps surprisingly in our increasingly secular world, most tunnelling projects still erect a shrine to Saint Barbara at the tunnel entrance.

I am a massive fan of TBMs. Here I am looking very excited in a TBM- tunnel under the streets of London. If I lived my life again, I think I’d be a tunnelling engineer. (Credit: Laurie Winkless)

Anyway, before we meet some of the First Ladies of the Underground, let have a quick look at how they work. First off, TBMs are huge. Bertha, the largest TBM in the world, is currently working her way under Seattle. She has a diameter of 17.5m, is 99 m long, and weighs over 6,000 tonnes. If we measure her in units of ‘double decker buses’ – she’s as tall as four parked on top of one another, as long as eight parked nose-to-tail, and weighs as much as 467 of them. So it’s no surprise that she’s usually referred to as ‘Big Bertha’.

So what do TBM’s like Bertha do with all that…girth? In their simplest form, TBMs are cylinder-shaped machines that can munch their way through almost any rock type. As I mentioned in my book, Science and the City, TBMs are generally referred to as ‘moles’, but I prefer to think of them as earthworms. Worms eat, push forward and expel whatever is left over, and while there are lots of different types of TBM, they pretty much all do those same three things.

Image credit: Crossrail

At the front, TBMs have a circular face covered in incredibly hard teeth made from a material called tungsten carbide. As the cutter-head rotates, it breaks up the rock in front of it. This excavated material is swallowed through an opening in the face (some would call it a mouth) and it is carried inside the body of the TBM using a rotating conveyor belt. There, it is mixed with various additives (rather like saliva or stomach acid in some animals) that turn the rock into something with the consistency, if not the minty-freshness, of toothpaste. After digestion, this goo is expelled out of the back of the TBM, and it travels along a conveyor belt, until it reaches a processing facility above ground. There, the goo is filtered and treated, with much of it reused in other building projects.

Because of their shape, TBMs produce smooth tunnel walls, which can then be lined using curved segments of concrete. TBMs manage this part of the process too – many metres behind the cutter-head, large robotic suction arms called erectors (stop giggling) pick up and place the concrete panels, to form a complete ring. As the TBM moves forward, more and more of these rings are put into place, until the tunnel is fully clad. In this way, cities across the globe can produce fully-lined tunnels at the rather impressive rate of 100 m per week.

Enough background. Time to meet some of the TBMs boldly going where no machine-named-after-a-woman has gone before.

London – Ada, Phyllis, Victoria, Elizabeth, Mary, Sophia, Jessica and Ellie

Crossrail is Europe’s biggest engineering project. Since 2009, they’ve constructed two brand-new, 21 km-long tunnels across London, running east-west. To do this, they used eight TBMs, and as tradition dictates, each was given a woman’s name, selected by members of the public. The first six machines were named after historical London figures, whilst the final two machines were named after ‘modern day heroes’. Because two TBM’s excavate parallel tunnels at the same time, they’re also named in pairs.

Image credit: Crossrail

– Mary and Sophia: These two excavated Crossrail’s new Thames Tunnel, between Plumstead and North Woolwich. They were named after the wives of Isambard and Marc Brunel, the famous engineers who constructed London’s first Thames Tunnel over 150 years ago. The women were a lot faster than their hubbies though – the original tunnel took 16 years to construct. This one was completed in just eight months.

Victoria and Elizabeth: Can you guess which women from history these TBMs were named after?! Yep, Queenie #1 and #2. In the citation, the reason given was that “Victoria was monarch in the first age of great railway engineering projects and Elizabeth is the monarch at the advent of this great age.” Victoria and Elizabeth excavated the tunnels that run between Canning Town and Farringdon, finishing the job in May 2015. As an aside, the Crossrail route itself will appear on tube maps as ‘The Elizabeth Line’, which is disappointingly predictable. I was rooting for ‘The Brunel Line’ myself, but hey.

Ada and Phyllis: These may be my favourites – named after the world’s first computer scientist, Ada Lovelace, and Phyllis Pearsall, who single-handedly created the London A-Z. Lovelace was a woman before her time – without her work, Charles Babbage and his ‘analytical engine’ would have been nothing more than a rich-man and his hobby. Pearsall, on the other hand, got lost on the way to a party in 1935, and decided the maps were inadequate. She walked a total of 3,000 miles to compile the first comprehensive street map of the city. Their Crossrail reincarnations drove west from Farringdon station, laying the groundwork for the second stage of the project.

Jessica and Ellie: These names were selected by primary school children from East London, and they come from heptathlete Jessica Ennis-Hill and swimmer Ellie Simmonds, who won gold medals at the 2012 Olympics and Paralympics held in the city. Like their human counterparts, these TBMs were hard-working, each excavating two sections of Crossrail’s route.

London has two brand-new TBMs too, which will be working on the extension to the tube’s Northern Line – the line I spent almost all of my 13 years in London living on. Like Crossrail’s Jessica and Ellie, the names of the newbies – each weighing in at 650 tonnes (or 50 double-decker buses) – were selected by schoolchildren. They drew inspiration from pioneering women in aviation. One is named Amy, after Amy Johnson, the first female pilot to fly solo from Britain to Australia. And the second is Helen, named after the first British astronaut, Helen Sharman.

Seattle – Big Bertha

What more can I say about Bertha? Well, she was named after one of Seattle’s early mayors. In fact, Bertha K. Landes was the city’s first and only female mayor…. And she’s still widely regarded as one of the best they ever had. She fought against police corruption and dangerous drivers, and advocated for municipal ownership of the Seattle City Light and street railways. In 2013, Bertha-the-TBM started her long journey across the city, excavating a multilevel road tunnel to replace the Alaskan Way Viaduct. But just six months into the project, Bertha ground to a halt. Investigations showed that some of Bertha’s cutting teeth had been severely damaged by a large steel pipe embedded in the ground that hadn’t shown up on surveys. Over the next two years (yes, really), construction engineers dug a recovery pit, so that they could access the machine’s cutter-head, and partially replace it. Bertha resumed tunnel boring in late December, 2015. As I type, she’s also on a pause because of some misalignment, but this stoppage is expected to be temporary. Poor Bertha.

Image credit: Washington State Department of Transportation

Auckland – Alice

Since moving to New Zealand in December, I’ve had a bit of rail-infrastructure-shaped gap in my life. Thankfully, Kiwis are also fans of TBMs, but they tend to use them for road tunnels. The latest one to finish her work is Alice – a 3200 tonne (246 buses) TBM that spent the last two years carving a path between Auckland’s major transport routes. Alice’s tunnel connects State Highway 16 and State Highway 20, and once it opens in April/May 2017, it will complete the city’s ring road. Having recently spent more than an hour in Auckland traffic heading to the airport, I can attest to how much the road is needed! Since finishing her tour of duty, Alice has since gone to a farm when she can roam free amongst all of the other TBMs…. Oh if only this were true. In reality, the largest sections of the machine are being shipped back to her German manufacturer. There, her components will be used to build another TBM. So it’s not been a bad life, I guess.

San Francisco – Mom Chung

Mom Chung is another TBM that has already done her job and is now ‘in retirement’. She is named after Dr. Margaret Chung, the first American-born female Chinese physician, who practiced medicine in the heart of San Francisco’s Chinatown. During World War II, she took lots of American servicemen under her wing, earning her the nickname ‘Mom’. Legend has it that when one of her ‘sons’ became a congressman, he filed the legislation to create a female branch of the Navy, in response to pressure from Mom, who was a firm supporter of women in the military. Mom Chung-the-TBM built the southbound central subway tunnel in San Francisco, and even had a Twitter account for a while.

Of course, actual, real-life women work alongside (and inside) these machines. As more women are attracted into engineering, tunnelling is no longer solely a male pursuit. Women still make up a small percentage (around 11% of the UK construction sector, for example), but those numbers are slowly growing. So no matter which way you look at it, women are literally boring. Tunnelling is awesome.

*** You can follow Laurie on Twitter @laurie_winkless. She also wants to say thank you to Dr Jess Wade for inspiring this article. If you love science and very cool doodles, you can also follow Jess on Twitter – she’s @jesswade


Detecting Parkinson’s Disease with your mobile phone


by Reham Badaway, in collaboration with Dr. Max Little.

So, what if I told you that in your pocket right now, you have a device that may be able to detect for the symptoms of a brain disease called Parkinson’s, much earlier than doctors themselves can detect for the disease? I’ll give you a minute to empty out the contents of your pockets. Have you guessed what it is? It’s your smartphone! Not only can your trusty smartphone keep you in touch with family and friends, or help you look busy at a party that you know no-one at, it can also detect for the very early symptoms of a debilitating disease. One more reason to love your smartphone!

What is Parkinson’s disease?

So, what is Parkinson’s disease (PD)? PD is a brain disease which significantly restricts movement. Some of the symptoms of PD include slowness of movement, trembling of the hands and legs, the resistance of the muscles to movement, and loss of balance. All of these movement problems (symptoms) are extremely debilitating and affect the quality of life for those diagnosed with the disease. Unfortunately, it is only in the late stages of the disease, i.e. when the symptoms of the disease are extremely apparent, that doctors can confidently detect PD. There is currently no cure for the disease. Detecting the disease early on can help us find a cure, or find medicines that aim to slow down disease progression. Thus, methods that can detect PD before doctors themselves can detect for the disease, i.e. in the early stages of the disease, are pivotal.

Smartphone sensing

So, how can we go about detecting the disease early on in a non-invasive, cheap and easily accessible manner? Well, we believe that smartphones are the solution. Smartphones come equipped with a large variety of sensors to enhance your experience with your smartphone (Fig 1). Over the last few years, abnormal characteristics in the walking pattern of individuals with PD have been successfully detected using a smartphone sensor known as an accelerometer. Accelerometers can detect movement with high precision at very low cost, making them perfect for wide-scale application.


Fig 1: Sensors, satellites and radio frequency in Smartphones

Detecting Parkinson’s disease before symptoms arise

Interestingly, subtle movement problems have been reported in individuals with a high risk of developing PD using sensors similar to those found in smartphones, specifically when given a difficult activity to do such as walking while counting backwards. Individuals at risk of developing the disease are individuals who are expected to develop the disease in the later stages of their life due to say a genetic mutation, but have not yet developed the key symptoms required for PD diagnosis. The presence of subtle movement problems in individuals with a high risk of developing PD indicates that the symptoms of PD exist in the early stages of the disease progression, just subtly. Unfortunately, these subtle movement problems are so subtle that individuals at risk of developing PD, as well as doctors, cannot detect them – so we must go looking for them. It is crucial that we can screen individuals for these subtle movement problems if we are to detect the disease in the early stages. The ability of smartphone sensors to detect the subtle movement problems in the early stages of PD has not yet been investigated. Using smartphones as a screening tool for detecting PD early on will mean a more widely accessible and cost-effective screening method.

Our solution to the problem

We aim to distinguish individuals at risk of developing PD from risk-free individuals by analysing their walking pattern measured using a smartphone accelerometer.

How does it work?

So, how would it work? Users download a smartphone app, in which they are instructed to place their smartphone in their pocket and walk in a straight line for 30 seconds. During these 30 seconds, a smartphone accelerometer records the user’s walking pattern (Fig 2).


Fig 2: Smartphone records user walking

The data collected from the accelerometer is then downloaded on to a computer so we can examine the presence of subtle movement problems in an individual’s walking pattern. However, to ensure that the subtle movement problems that we observe in an individual’s walking pattern is due to PD, we aim to simulate the user’s walking pattern via modelling the underlying mechanisms that occur in the brain during PD. If the simulated walking pattern matches the walking pattern collected from the user’s smartphone (Fig 3), we can look back at our model of the basal ganglia (BG)- an area in the brain often associated with PD – to see if it is predictive of PD.




If it is predictive of PD, and we observe subtle movement problems in the user’s walking pattern, we can classify an individual as being at risk of developing PD. Thus, an individual’s health status will be based on a plausible link between their physical and biological characteristics. In cases in which the biological and physical evidence do not stack up, for example when we observe subtle movement problems in an individual’s walking pattern but the information drawn from the BG is not indicating PD, we can dismiss the results in order to prevent a misdiagnosis. A misdiagnosis can have a significant impact on an individual’s health and psychology. Thus, it is pivotal that the methods that we build allow us to identify scenarios in which the model is not capable of accurately predicting an individual’s health status, a problem which a lot of current techniques in the field lack.

To simulate the user’s walking pattern, we aim to mathematically model the BG and use it as input into another mathematical model of the mechanics of human walking. The BG model consists of many variables to make it work. To find the values for the different variables of the BG model such that it simulates the user’s walking pattern, we will use a statistical technique known as Approximate Bayesian Computation (ABC). ABC works by running many simulations of the BG model until it simulates a walking pattern that is a close match to the user’s walking pattern.

Ultimately our approach aims to provide insight into an individual’s brain deterioration through their walking pattern, measured using smartphone accelerometers, in order to know how their health is changing.


As well as identifying those at risk of developing PD from healthy individuals, our approach provides the following benefits:

  • Providing insight into how the disease affects movement both before and after diagnosis.
  • Identifying disease severity in order to decide on the right dosage of medication for patients.
  • Tracking the effect of drugs on symptom severity for PD patients and those at risk.


Apple recently launched ResearchKit, which is a collection of smartphone applications that aims to monitor an individual’s health. Companies such as Apple are realising the potential of smartphones to screen for diseases. The ability to monitor patients long-term, in a non-invasive manner, through smartphones is promising, and can provide a more accurate picture of an individual’s health.

Advances in smartphone sensing are likely to have a substantial impact in many areas of our lives. However, how far can we go with monitoring people without jeopardizing their privacy? How do we prevent the leakage of sensitive information collected from millions of people? The growing evolution of sensor-enabled smartphones presents innovative opportunities for mobile sensing research, but it comes with many challenges that need to be addressed.