Current student, International student
- Subject area
- Mechanical, Electrical and Manufacturing Engineering
After completing my master’s in Big Data Science and Technology, I wanted to continue my studies and I decided to undertake a PhD and Loughborough was the perfect place for me.
Coming to study at Loughborough University was quite a crucial decision for me. As a parent, I was aware that Loughborough will be home to my family for the duration of my PhD. I looked at what the town was like for living, schooling and raising young kids. The University’s position on the various university rankings in the UK was a great bonus. I was also very pleased to find the level of support I received from the Doctoral College and my primary supervisor in the initial stages of my application. Their understanding of my status as a parent and efforts to tailor around my circumstances was quite a compelling reason. Additionally, I was offered a full-fee waiver studentship, which is a helpful financial support and one of the strongest reasons for choosing to come to study at Loughborough.
My research is quite a diverse topic and still shaping up. It falls under the wide spectrum of explainable artificial intelligence (XAI) which is artificial intelligence (AI) in which the results of the solution can be understood by humans. The study focuses on the manufacturing industry and aims on finding best practises that offer a level of transparency and accountability to see whether the predictions and outputs generated are fair. Additionally, it further explores the legislative, ethical and user-centred practices that are most suited in manufacturing.
I quite enjoy the independence in driving my research with constant support and advice from my supervisors. The idea that I can map the scope and the direction of the research brings vigour and creativity in my approach. I also find the several training activities, seminars and other supportive content offered by the Doctoral College, Wolfson School and several other initiatives quite conducive to my research.
Another factor that I value most is the advice and support I get from my school, supervisors and several other teams on how to juggle my activities around being a parent. I am a member of the PGR Parent and Carers Network, which I find very helpful in terms of advice and networking with people with similar circumstances.
My PhD journey is quite like any parent doctoral researcher. I am a mother of two beautiful boys who put a smile on my face on the worst of days but bring a certain level of challenge to my PhD journey. I schedule my engagements in view of their wellbeing and the time they require of me as their mother. My day begins at 5:00am, with an hour and a half of some start up reading followed by the breakfast routine, getting the kids ready for school and dropping them off. This is usually followed by a peaceful breakfast at 9:00am to get myself ready for a busy day ahead.
The first year of PhD is quite a blessing; it is a time when you can research as far and wide as you can to find a novelty factor, a gap in research, or something that is simply intriguing. Reading good content is crucial to every research. My day is usually divided into a reserved time for reading, training, attending conferences, as well as any other ad hoc activities that I might need to do. In my weekly supervisory meetings, my supervisors and I agree on some targets that I need to meet for the next week; I divide these over the whole working week.
I like keeping lists and religiously following them, but I tend to be not too ambitious when writing up my daily activity list. My active day has to end at 3:00pm, which is when the children come home, and my evenings are usually reserved for family time. Once the children are in bed, I devote at least an hour to completing any unfinished tasks and planning an agenda for the next day.
I think for me, my research topic found me as opposed to the other way round. My interest was piqued by visualisation of machine learning model outcomes to enhance understanding by the end users. The idea that we need to actively research the concept of explainability of the machine learning models became a topic of interest during my first meeting with my supervisors. My initial understanding or point of view of this topic was that we do not really need explanation and that we should trust AI for what it does for us. I value this research a lot because it has changed my way of thinking. I learnt quite early into my PhD that every point of view should be open to discussion and that nothing can be conclusive unless it is factual. AI is widely implemented in many industries, and while it makes life easy, at times it generates outputs or predictions that may have a negative effect. Hence, it is important that a certain level of explainability is offered by these complex models so that we can make informed decisions.
I am quite a stringent advocate of transparency in AI and after my research, I would like to work more in this field. I think there is much need to bridge the knowledge gap between AI and different industries and I would like to be a part of the initiative. Also, I dream of seeing more women in STEM in Pakistan and I would really like to work towards making that happen. This is something that I would like to pursue once I have completed my PhD.
One thing that I have learnt from my own PhD experience is being kind to myself. I would pass on this advice quite gladly to any future PhD students. There are times when I don’t seem to be meeting any real targets and seem somewhat lost, but I always manage to find my way back on track. I strongly advise making full use of the expertise and knowledge of your supervisors; they are there to help and offer advice on best practice. They have been through the journey and they are aware of the challenges. I also recommend being realistic and disciplined in setting targets and meeting them in time. Most importantly however, enjoy the journey. I would like to look back at it as the time that I learnt most, made most acquaintances and friends for life.