Mikael Johansson

Mikael Johansson is a Professor at Kungliga Tekniska Högskolan (KTH), specializing in Control Technology. He teaches and coordinates courses such as Distributed Optimization (FEL3311) and various advanced-level degree projects in computer science, electrical engineering, and systems engineering. His research spans Control Systems, Machine Learning, and Optimization, with a focus on asynchronous algorithms, federated learning, and applications in energy systems and construction.

His work includes 15 recent publications on topics like neural networks, distributed optimization, and battery technology. Notable areas of contribution are in asynchronous learning, federated learning with privacy constraints, and quasi-Newton methods for optimization. His research bridges theoretical advancements with practical applications in urban design, healthcare, and autonomous systems.