The Engineer's Impact - Katarina Grolinger

Your inside look at faculty’s research and its effect on society

In this Q&A series, we’ll feature Western Engineering faculty members to gain a succinct overview of their research, understand its impact on society, and discover intriguing little-known facts.

Meet Electrical and Computer Engineering Assistant Professor Katarina Grolinger.

Can you describe your research?

My research group aims to make better use of IoT data, extract value from data, and support new data-driven solutions by devising machine learning solutions for IoT systems. The number of connected devices (e.g., smartphones, smartwatches, and industrial sensors) is growing at an unprecedented rate, creating an explosion of data that are moving among devices, storage, and processing locations. These data present tremendous opportunities, but the data potential is only unlocked through analysis. We leverage machine learning at scale, distributed, and edge computing to develop solutions for a variety of domains.

How does your research impact society in everyday life?

IoT spending is estimated to exceed $1 trillion in 2023, up from $742 billion in 2020. Although the deployment of connected devices is rapidly increasing, even data currently captured by those devices remain underutilized. As machine learning and AI extract value from data, their impact crosses fields and includes healthcare, industry 4.0, smart cities, smart grid, and many others. Recent aggressive investment in machine learning and artificial intelligence reflects their importance in driving economic growth and improving lives. 

What’s an interesting, little-known fact related to your research?

Although there has been a hype around deep learning in recent years, these techniques are not new. Deep learning is based on neural networks which were first proposed in 1944 and have been attracting different levels of attention through decades. What enabled recent developments and the success of deep learning is the availability of data and hardware (e.g., GPUs, supercomputers).