Why Data Scientists Should Care About Quantum Computing | Towards data science

In the Writing Spotlight series, TDS Editors chat with members of our community about their work in data science and AI, their writing, and their sources of inspiration. Today, we are pleased to share our interview with Sara A. Metwalli.

Sara is a quantum computing researcher at the Quantum Software Lab, exploring how machine learning and quantum computing intersect with how to write software for quantum computers. He writes on quantum topics with a focus on clarity, authenticity, and separating the hype from what actually works. Sara also likes to work, read, write and explore the world. He has lived in Egypt, Japan, the US, and now in Scotland.

When we last talked to you five years ago – in our first Writer Spotlight! – you were in the early stages of your PhD program in Japan. What have you been up to?

It feels like forever since we featured the last author! I started writing for TDS in 2019. I was preparing to start my PhD, I did so in 2020, and I finished it in 2024. I have to admit that writing for TDS helped me to be able to isolate myself as a PhD student in the time of COVID.

I moved to the US in mid-2024, right after defending my thesis, and worked for six months as an information and education coordinator before returning to school for a one-year postdoc. I finally moved to Scotland last October.

In the five years since Q&A, we have seen the arrival of LLMs and attorneys, among other innovations. How has the rise of everyday AI tools affected your work – and life in general?

The rise in popularity of the LLM has changed the world and not just my life. As someone primarily in academia, I have been reading papers and talking to researchers who were working on 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 gets it.

The sudden, explosive explosion of AI innovation made me more aware of the importance of sharing research as it progresses, not just as it develops.

I believe LLMs can be used to make life easier for many people, but they can be misused to cause harm. Finding balance on a personal level, on a professional level, and on a social level is a challenge that any emerging technology faces at its inception.

Your interest in quantum technology began long before the field began to develop serious ideas in the last few years. What attracted you to this place?

My interest in quantum tech started somewhere around 2018! I was doing my master’s and working as a teaching assistant in the quantum physics department. I really enjoyed the class, and the professor did a great job of explaining things I didn’t understand before.

While I was thinking about pursuing a PhD, the field of quantum computing was starting to blossom: IBM had shared its plan to make its tools public and released Qiskit. It was exciting, complex, and intellectually challenging (three things that attract me in any field). It had math, skills, and coding. I asked a professor I was working with if he knew anyone willing to take a PhD student with no PhD skills, and to my surprise he did. The person he introduced me to became my PhD supervisor.

I love software and math, and quantum combines the two with the potential for large-scale applications. 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 studying quantum mechanics and quantum computing applications.

Your public article on TDS has changed over the last year or two to focus solely on quantum. Why is it important for data and ML professionals to learn about this technology?

Since “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 see quantum potential, and I see how it’s growing rapidly. I think the only reason it’s improving so quickly is the involvement of people outside of academia. I believe that data scientists are important 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 basic tasks they are already working on (such as optimization, sampling, and large linear algebra) are types 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.

Of course, today’s hardware is still limited, but the long-term impact can change the way hard data problems are solved. So it’s an opportunity not only to prepare for the next big step in technology, but also to be a part of creating that technology.

How has your experience been as a social writer in the era of ChatGPT, Gemini, and more? What motivates you to write these days?

That is a very good question! I like the AI ​​that generates; it shows how much we as humans have been able to achieve with technology. But really, it’s a machine; it’s an algorithm that finds patterns: it doesn’t have a soul, it doesn’t have experience.

I continue to write and read the posts of the authors I like because teaching or imparting knowledge is a personal thing. ChatGPT can give you the basics of the topic, but someone who has gone through the learning process can tell you more, as they will think about the obstacles they have faced and the challenges they have overcome. They can relate to readers more than AI can – 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.