Professor’s portrait: AI to tackle real-world challenges
For over two decades, Carlos N. Silla Jr., newly appointed Professor at Halmstad University, has been researching Artificial Intelligence (AI) and its potential to solve real-world problems. Through his research and dedication to education, he is helping to shape the future of AI while mentoring the next generation of researchers.

“AI is a tool with incredible potential, and my goal is to ensure that we’re using it in ways that truly make a difference.”
Carlos N. Silla Jr., Professor
What fascinates Carlos N. Silla Jr. most about AI and machine learning (ML) is their potential to solve practical, real-world problems.
“AI isn’t just theoretical. It can actually help solve pressing issues across different fields”, he says.
Carlos N. Silla Jr's research includes various domains, from health informatics to education and audio technologies.
“Collaborating across fields helps us combine strengths and tackle problems that wouldn’t be solvable with one discipline alone”, he says.

Carlos N. Silla Jr., Professor of Machine Learning.
AI in education and music
Carlos N. Silla Jr. has used AI to improve teaching and learning methods in education. One example is a project in predictive learning analytics, where his former PhD student developed a tool that automatically groups students based on their coding skills.
“The tool groups students based on their coding abilities, saving teachers a lot of time, especially in large programming classes where manual grouping would be nearly impossible”, says Carlos N. Silla Jr.
Carlos N. Silla Jr’s work with AI extends to the arts, applying AI to music genre classification and bird species identification through audio signals.
“The key to success in these areas lies in combining deep learning techniques with hand-crafted features designed by experts,” he says, explaining how this approach has significantly improved accuracy in AI-driven audio analysis.

Carlos N. Silla Jr. has used AI in many different areas and sees how beneficially the different parts connect to each other.
Mentoring the next generation
Throughout his career, Carlos N. Silla Jr. has remained committed to mentoring students and fostering young talent.
“It’s vital that we give students the tools, confidence, and support they need to be innovative and make a difference in the world”, he says.
At Halmstad University, this commitment is reflected in initiatives like the Center for Applied Intelligent Systems Research (CAISR) and the research programme Learning in a Digitalised Society (LeaDS), both of which Carlos N. Silla Jr. is a part of. These initiatives connect academic research with societal needs.
“Our close connection to society is what makes our work so meaningful. It’s truly exciting to be part of an environment where AI is actively used to solve real-world problems”, he says.
Creativity as a key factor
One area where Carlos N. Silla Jr. has made a valuable contribution is in STEAM (science, technology, engineering, arts, and mathematics) education. He has led several outreach projects to encourage more women to pursue and remain in computer science. By integrating music and programming he has created creative approaches to engage more students.
“Robotics might not appeal to everyone, but bringing in music and arts opens up new ways to engage students. The impact of educational projects goes beyond academic results. They shape how students see themselves and their future”, he says.
Carlos N. Silla Jr’s passion for creativity in education led him to complete a second undergraduate degree in Music Education and Pedagogy in 2022. This reflects his belief that the arts play a crucial role in fostering critical thinking and innovation.
Tackling future challenges
One of the major challenges in AI research is handling imbalanced datasets, which can affect the precision of AI models. During the COVID-19 pandemic, Carlos N. Silla Jr. and his research team became aware of this issue when trying to predict pneumonia from X-ray images. They found that while AI could become good at identifying healthy lungs, it struggled to detect diseases and conditions like pneumonia.
Similar problems arise in cybersecurity, where it’s difficult for AI to reliably detect malicious activity due to an overwhelming amount of normal network traffic.
“In real-world data, we often have a lot more examples of normal behaviour than the things we’re actually trying to predict. It’s not just about building accurate models, but also about finding new methods to handle these imbalances in data effectively”, Carlos N. Silla Jr. says.
Looking ahead, Carlos N. Silla Jr. remains committed to advancing the field of AI and applying its potential to benefit society.
“AI is a tool with incredible potential, and my goal is to ensure that we’re using it in ways that truly make a difference”, he says.
Text: Anna-Frida Agardson
Photo: AI generated by Halmstad University (top picture), Dan Bergmark,
Illustration: Carlos N. Silla Jr.
About Carlos N. Silla Jr.
Carlos N. Silla Jr. earned his Bachelor of Science in Computer Science from Pontifícia Universidade Católica do Paraná (PUCPR), Brazil, in 2004. During this time, he also received the Marcelino Champagnat Award for the highest academic performance among his peers. He continued his studies at PUCPR, completing a Master of Science in Computer Science in 2007. That same year, he moved to the United Kingdom to pursue a PhD in Computer Science at the University of Kent. His research led to his thesis “Novel Approaches for Hierarchical Classification with Case Studies in Protein Function Prediction”, which he completed in 2011. Expanding his academic interests, Carlos N. Silla Jr. obtained a Bachelor’s degree in Music Education from PUCPR in 2022.
In terms of professional experience, Carlos N. Silla Jr. started his career as a Part-time Assistant Lecturer at PUCPR in 2007, a role he held until he began his PhD studies. While working on his doctorate, he took on a similar role at the University of Kent. In 2012, he became an Adjunct Professor in the Computer Engineering Department at the Federal University of Technology of Paraná (UTFPR) in Brazil on the Cornélio Procópio campus. There, he was also the Head of the Graduate Programme in Informatics from December 2012 to December 2015. In 2016, Carlos N. Silla Jr. returned to PUCPR as an Adjunct Professor in the Graduate Programme in Computer Science.
In 2024, Carlos N. Silla Jr.. was appointed Professor of Machine Learning at Halmstad University. He will be inaugurated at the Academic Ceremony on 15 November.