I am leading several Innosuisse and SNF-funded projects and collaborations, for process optimization and control in machining using both data-driven methods and global optimization approaches. My interests are in industrial process optimization, as demonstrated for turning and grinding process, as well as plasma spray coating; condition monitoring, and standardization of systems and components, taking advantage of sensor data; and on intelligent control. A recent big topic of interest is robot-based manufacturing - reaching high precision for typical CNC-controlled process, using industrial robots coupled with advanced tracking, state estimation merging data from different sources, and learning control. The projects are focused on developing methods for improving the accuracy of path following for motion drives with applications in precision machining, using optimisation-based control in combination with learning and Bayesian methods, and on developing new, data-driven control methods for advanced manufacturing. Other topics of interest and ongoing projects are related to fault diagnostics, data-efficient probabilistic approaches applied to improve various manufacturing aspects, and application and adaptation of fast numerical methods for industrial processes. Another big topic of interest is data-driven process control.

I am collaborating with PhD students and postdocs in the group of Prof. John Lygeros at IfA. We have always available projects for ETH master students in the intersection between control, machine learning, and optimization. For ETH students: we currently have several possibilities (master and semester projects) for students interested in robot-based manufacturing, especially in system integration - building the robot system, integrating all the sensing equipment, and the corresponding algorithms for trajectory planning, state estimation, and control. The projects can be targeted to your interests. Drop me an e-mail if interested!