Dr. Luisa Liboni

Assistant Professor

Phone:
Email: luisa.liboni@uwo.ca

I am an Assistant Professor of Mathematics and Analytics in the School of Management, Economics, and Mathematics at King’s University College at Western University. I teach and conduct research in data science and analytics, applied mathematics, machine learning, and artificial intelligence.

I completed my Ph.D. in Electrical Engineering in 2017 and earned my B.S. in the same field in 2010, both from the University of São Paulo, Brazil. Additionally, I hold a Bachelor’s degree in Education, specializing in Technological Education, from the Federal Institute of Education, Science, and Technology of São Paulo, Brazil (2012).

Before joining King’s, from 2022 to 2023, I was a Postdoctoral Fellow in the Department of Software Engineering at Western University. From 2023 to 2024, I held a Postdoctoral Fellowship from the Western Academy for Advanced Research, collaborating with both the Department of Mathematics and the Brain and Mind Institute at Western University. Prior to this, I was an Associate Professor in the Department of Electrical Engineering at the Federal Institute of Education, Science, and Technology of São Paulo, Brazil.

Teaching

With over ten years of experience in higher education, I aim to inspire students to develop strong foundations in mathematical and analytical thinking.

Courses I regularly teach include:

• Finite Mathematics (Kings)
• Introduction to Analytics (Kings)
• Machine Learning
• Intelligent Systems

Research

My research spans both applied and theoretical areas.

Applied Research:
In my applied work, I focus on a broad range of fields, including power systems and smart grids, industrial networks, and medical and veterinary applications. My vision is to advance efficient and trustworthy decision-making across disciplines through the use of data, scalable and reliable software, and applied mathematics. I use mathematical-statistical tools, machine learning, and AI to solve complex problems and optimize decision-making.

Theoretical Research:
In my theoretical work, I explore where bits and neurons meet. My research in computational neuroscience frames neural networks as complex systems, drawing parallels in terms of emergent behaviour, distributed processing, adaptability, and computation. This work allows us to develop mathematical models and simulations of neural systems. Additionally, the insights gained help create new artificial neural network architectures for machine learning tasks.

Selected Publications

I am always excited to collaborate on interdisciplinary projects and welcome inquiries from students and researchers with similar interests.

For a complete list of publications, visit my Google Scholar profile:
Google Scholar