Abstract: As AI matures, the focus shifts from developing smarter models to questions about how to use them in real-world cases. The shift from handcraft to a more systematic and efficient industrial way of developing, testing, monitoring, and maintaining ML systems raises novel challenges. In this talk, I will cover some of our work in the area of MLOps, such as cost-efficient inference, automation of ML practices, monitoring the accuracy of ML, and detection of anomalies.

Speaker: Dr Jukka K. Nurminen is a professor of computer science at the University of Helsinki. He has worked extensively on software research in the telecom industry at Nokia Research Center, in academia at Aalto University, and in applied research at VTT. His key research contributions are on energy-efficient software, mobile peer-to-peer networking, and cloud solutions but his experience ranges widely from applied optimization to AI, from network planning tools to mobile apps, and from software project management to tens of patented inventions. He received his MSc degree in 1986 and PhD degree in 2003 from Helsinki University of Technology (now Aalto University) in applied mathematics. Currently, his main interests are in the engineering of machine learning systems, fair and reliable operation of AI, and software development for quantum computers.

Affiliation: University of Helsinki

Place of Seminar:  Kumpula exactum D122 (in person) & zoom ( Meeting ID: 640 5738 7231 ; Passcode: 825217)