[camera] Day 4 morning – JSALT 2025 – Sekanina: Evolutionary ML in engineering design
Lukáš Sekanina from Brno University of Technology will present: Evolutionary machine learning in engineering design.
The use of evolutionary algorithms for the automated design of programs, electronic circuits, neural networks, antennas, and other objects has become a fruitful approach in computer science and engineering in the last decade. The reason is that evolutionary approaches can handle the design process in a holistic, multi-objective way and create solutions with unique properties. With the massive development of AI based on machine learning, evolutionary machine learning has been introduced to enrich machine learning methods with evolutionary computing techniques and vice versa. This tutorial surveys the key ingredients of evolutionary design methods, focusing on genetic programming. Examples of evolved solutions (such as approximate arithmetic circuits, neural network architectures, and image filters) that show unique properties compared to conventional designs will be presented and discussed.
Bio: Lukáš Sekanina (Senior Member of IEEE) received all his degrees from the Brno University of Technology, Czech Republic (Ing. in 1999, Ph.D. in 2002), where he is currently a full professor and Head of the Department of Computer Systems. He was awarded the Fulbright scholarship and worked on the evolutionary circuit design with NASA Jet Propulsion Laboratory at Caltech in 2004. He was a visiting lecturer with Pennsylvania State University (2001), Universidad Politécnica de Madrid (2012), and a visiting researcher with the University of Oslo in 2001. He has worked as an associate editor of IEEE Transactions on Evolutionary Computation and an editorial board member of the Genetic Programming and Evolvable Machines Journal. As a PC co-chair, he contributed to organizing conferences such as ICES, EuroGP, DDECS, DTIS, and DATE. He was a principal investigator of eight projects supported by the Czech Science Foundation. Prof. Sekanina co-authored one patent and over 250 research papers, mostly in genetic programming, approximate computing, evolvable hardware, and automated design methods.
Lukáš Sekanina from Brno University of Technology will present: Evolutionary machine learning in engineering design.
The use of evolutionary algorithms for the automated design of programs, electronic circuits, neural networks, antennas, and other objects has become a fruitful approach in computer science and engineering in the last decade. The reason is that evolutionary approaches can handle the design process in a holistic, multi-objective way and create solutions with unique properties. With the massive development of AI based on machine learning, evolutionary machine learning has been introduced to enrich machine learning methods with evolutionary computing techniques and vice versa. This tutorial surveys the key ingredients of evolutionary design methods, focusing on genetic programming. Examples of evolved solutions (such as approximate arithmetic circuits, neural network architectures, and image filters) that show unique properties compared to conventional designs will be presented and discussed.
Bio: Lukáš Sekanina (Senior Member of IEEE) received all his degrees from the Brno University of Technology, Czech Republic (Ing. in 1999, Ph.D. in 2002), where he is currently a full professor and Head of the Department of Computer Systems. He was awarded the Fulbright scholarship and worked on the evolutionary circuit design with NASA Jet Propulsion Laboratory at Caltech in 2004. He was a visiting lecturer with Pennsylvania State University (2001), Universidad Politécnica de Madrid (2012), and a visiting researcher with the University of Oslo in 2001. He has worked as an associate editor of IEEE Transactions on Evolutionary Computation and an editorial board member of the Genetic Programming and Evolvable Machines Journal. As a PC co-chair, he contributed to organizing conferences such as ICES, EuroGP, DDECS, DTIS, and DATE. He was a principal investigator of eight projects supported by the Czech Science Foundation. Prof. Sekanina co-authored one patent and over 250 research papers, mostly in genetic programming, approximate computing, evolvable hardware, and automated design methods.
