In the Author Spotlight series, TDS Editors talk to members of our community about their work in data science and AI, their writing, and their sources of inspiration. Today, we are excited to share our interview with Sara A. Metwalli.
Sara is a quantum computer researcher in the Quantum Software Lab, exploring how machine learning and quantum systems intersect and how to write software for quantum computers. He writes on quantum topics with a focus on clarity, realism, and separating the hype from what actually works. Sara also likes to exercise, read, write, and explore the world. He has lived in Egypt, Japan, the US, and is now in Scotland.
The last time we spoke to you was five years ago – in our first Author Spotlight! – you were in the early stages of your PhD program in Japan. What have you been doing?
It feels like forever since we did the last writer! I started writing for TDS in 2019. I was preparing to start my PhD, I did so in 2020, and finished it in 2024. I have to admit that writing for TDS helped me get through the isolation of being a PhD student during COVID.
I moved to the US in mid-2024, right after defending my thesis, and worked for six months as a social and learning coordinator before returning to school for a one-year postdoc. I finally moved to Scotland in October last year.
In the five years since that Q&A, we've seen the arrival of LLMs and agents, among other innovations. How has the rise of AI tools every day affected your work – and life in general?
The rise in popularity of LLMs changed the world and not just my life. As a person especially in higher education institutions, I am constantly reading papers and talking to researchers working in this technology. I worked with them and discussed their ideas. I always find it interesting how research grows outside of research labs – how researchers don't know how the technology will be used once everyone has access to it.
The sudden, explosive popularity of generative AI has made me more aware of the importance of sharing research as it develops, not just as it matures.
I believe that LLMs can be used to make many people's lives easier, but they can be misused to harm. Finding a balance at the personal level, the professional level, and the community level is a challenge any emerging technology faces at its inception.
Your interest in quantum technology started long before the field started creating a lot of buzz a few years ago. What drew you to this area in the first place?
My interest in quantum tech started somewhere around 2018! I was doing my master's and working as a teaching assistant in a quantum physics class. I really enjoyed the class, and the professor did a great job explaining things that I had never understood before.
When I was thinking about pursuing a PhD, the field of quantum computing was just beginning to blossom: IBM had shared its intention to make its machines public and released Qiskit. It was exciting, complex, and mentally challenging (three things that attract me in any field). It had math, power, and code. I asked the Professor I was working with if he knew anyone willing to take on a PhD student who does not have a quantum background to do a PhD, and I was surprised that he did. The person who informed me turned out to be my PhD supervisor.
I love software and math, and quantum combines the two with the power of great apps. Today, I am a researcher at the Quantum Software Lab at the University of Edinburgh, Scotland. I work on the bridge between data science and quantum computing, as well as quantum machine learning and quantum computing applications.
Your public writing on TDS has changed over the last year or two to focus almost exclusively on quantum. Why is it important for data and ML professionals to learn about this technology?
Since the word “quantum” is a buzzword, misinformation about it has exploded. As someone in the field, I hate to see people being misled by false information. I can see the quantum energy, and I can see how fast it is growing. I think the only reason it has improved so quickly is the involvement of people outside of academia. I believe that data scientists are essential to the development of quantum computing, and quantum computing has the potential to change the way we think about data science and machine learning.
I personally believe that data scientists should care about quantum computing because many of the important tasks they are already working on (such as optimization, sampling, and large linear algebra) are exactly the kinds of problems that quantum algorithms aim to speed up or handle differently. Quantum methods, such as the Quantum Approximate Optimization Algorithm and Quantum Machine Learning, have the potential to improve performance in areas such as model training, complex simulations, and decision making under uncertainty.
In fact, today's hardware is still limited, but the long-term impact may reshape how hard data problems are solved. So it's an opportunity not only to be ready for the next big step in technology, but also to be a part of shaping that technology.
What was your experience as a publicist in the years of ChatGPT, Gemini, and more? What motivates you to write these days?
That's a great question! I love AI for production; it shows how far we as humans have been able to take technology. But, after all, it's a machine; it is an algorithm that finds patterns: it has no soul, it has no experience.
I continue to write and read the writings of my favorite authors because teaching or imparting knowledge is something for people. ChatGPT can give you the basics of the topic, but someone who has been through the learning process can tell you more, as they will consider the obstacles they faced and the challenges they overcame. They can relate to students more than AI – and that, to me, is very important.
To learn more about Sara's work and stay up to date with her latest articles, you can follow her on TDS.
