I’ve most enjoyed the modules that blend real-world software engineering with physical systems.

Please give an overall description about your project. Why did you choose it? What did you learn?

I chose this project because it let me bring together my two main interests: computer science and physics. Since I hope to work in the Internet of Things industry, I was excited to write both low-level code close to the hardware and higher-level Java code that uses Pure Data for signal processing.

The most difficult part was understanding the physics of sound. At first, I struggled with research papers full of technical terms, so I spent time learning basic acoustics before tackling how to model speech (i.e. converting the characteristics of human speech into corresponding tube shapes) and then moving on to digital signal processing. To keep things manageable, I began by checking the hardware and writing simple test programs. Once I understood how the parts worked, I moved on to sending fixed signals through the tube and measuring the results, validating the tube physics. Finally, I developed and tested my DSP algorithms with varying inputs.

Working with the hardware itself also brought surprises. Although the device looked solid, small imperfections caused unpredictable results. With help from iForge, I designed and added custom supports to stabilise the setup, which allowed me to focus on refining my software.

Through this project, I learned a great deal about speech physics and the practical application of DSP. I also gained experience integrating Pure Data with Java, writing my first PD externals in C, and managing concurrency so that the system could run in real time.

While this model cannot yet generate full speech, it provides a clear teaching tool and a strong foundation for future work. In an industrial setting, the same principles could be used to help robots produce more natural, human-like voices in IoT and robotics applications.

Why did you choose BSc Computer Science?

I have always been fascinated by computers. As a child, I spent much of my free time exploring my computer’s capabilities — not just playing games, but learning how it worked under the hood. At fourteen, I wrote my first PHP scripts and gradually built my programming skills. At first, I didn’t think like a programmer, but everything changed in secondary school, where I began to understand core concepts and fell in love with problem-solving.

Although I believe I could have taught myself programming and software engineering, I know I would have struggled with the more mathematics-intensive modules, such as those covering AI or speech processing. This course gives me the structured support and expert guidance I need to tackle those challenges. Choosing it felt obvious: it allows me to deepen my knowledge, work on real-world projects, and prepare for a career doing what I enjoy most — creating software that makes a difference.

What have you enjoyed most about your course so far?

So far, I’ve most enjoyed the modules that blend real-world software engineering with physical systems. In Software Hut, I built applications in Ruby on Rails while working “with a client” to gather requirements, ask the right questions, and refine the design — just like in industry. Speech Processing gave me the thrill of applying acoustic theory and signal-processing algorithms to live audio data, turning math into working code. In Computer Vision, I’m discovering how cameras and algorithms can extract meaning from images. And in Internet of Things, I’ve loved designing end-to-end solutions that connect sensors, hardware, and the cloud — exactly the kind of work I hope to do in my career. Together, these courses have shown me how software and the physical world come together, and they’ve inspired me to pursue projects that make that connection even stronger.

What are the best things about studying your course? 

The best thing about studying this course has been the way it brings together theory and hands-on practice. From building real applications in Software Hut to testing signal-processing algorithms in Speech Processing, each module challenges me to apply what I’ve learned in a tangible way. I’ve gained confidence working with clients, designing hardware-software systems in IoT, and exploring cutting-edge topics like Computer Vision. Above all, I’ve found a supportive community of classmates and professors who guide me as I tackle new mathematical and engineering challenges.

Why did you choose to study at Sheffield?

I first decided in middle school that I wanted to study in the UK because British universities are among the best in the world, and I believed they offered a higher quality education than I could find in Poland. When I received offers from both Surrey and Sheffield, I chose Sheffield because it felt like a safe, calm city where I could focus on my studies. It is also more affordable than many other parts of England. On top of that, Sheffield University has a strong computer science department, friendly staff, and great campus facilities, which made it the perfect place for me to learn and grow.

Are you involved in any extra-curricular activities? What do you enjoy most about these activities?

I’m not formally involved in any university clubs, but I keep myself busy with two main activities outside my studies. First, I’m part of a small team developing an iOS and Android app, which gives me real-world experience in mobile development and teamwork. Second, I go to the gym almost every day. I enjoy how the gym helps me clear my mind after long hours of coding and studying. Both activities balance my academic work: building an app sharpens my technical and collaboration skills, while regular exercise boosts my energy and keeps me focused.

What advice would you give to a younger student considering studying at Sheffield?

If I could give my younger self advice about coming to Sheffield it would be to never hesitate to ask questions in lectures, seminars or labs. That is often the quickest way to clear up confusion and deepen your understanding. Learn to manage your time from day one by balancing lectures, coding projects, gym sessions and downtime with a simple calendar or to-do list. Networking is very important. Building relationships with classmates, tutors and industry visitors can open doors to internships and future job opportunities, so take every chance to introduce yourself and stay in touch.