Mikael Yamanee-NolinDoctoral Student
Research focused on model-based optimization of complex chemical production systems with respect to efficient usage of raw material by utilizing state-of-the-art dynamic process flowsheeting software coupled to the programming language Python. Working with both flowsheeting models as well as deep learning models. Also working with preparative chromatography for the purification of biopharmaceuticals, and blue-green systems for urban flooding mitigation. Quite the mix, and very rewarding, with lots of opportunities for participating in teamwork and driving projects forwards.
Teaching and developing the course Transport Phenomena given to year 2 students at Chemical and Biotech Engineering.
Recent research outputs
Research output: Chapter in Book/Report/Conference proceeding › Book chapter
Research output: Contribution to journal › Article