Dante Kalise

Dr. Dante Kalise is a Reader in Computational Optimisation and Control in the Department of Mathematics at Imperial College London, where he also serves as the MSc Course Director for Applied Mathematics. Previously, he held roles including Assistant Professor at the University of Nottingham (2019–2021), Imperial College Research Fellow (2017–2019), Research Scientist at RICAM Linz (2013–2017), and Postdoctoral Researcher at Sapienza University of Rome (2011–2013). He earned his B.Sc. and M.Sc. in Mathematical and Electronic Engineering from the Federico Santa María Technical University in Chile, followed by a Ph.D. in Mathematics from the University of Bergen (Norway, 2012).

His research focuses on computational methods for optimisation and control, including nonlinear PDEs, high-dimensional approximation, and agent-based models. Key areas include scientific machine learning, epidemiological modeling, and fluid dynamics control. He leads initiatives such as the EPSRC Centre for Doctoral Training in Collaborative Computational Modelling and a new MSc stream in Scientific Computing & Machine Learning.

He actively organises workshops and conferences, including sessions on Conservation Science and Control Theory applications. Editorial duties include roles as Associate Editor for Mathematics of Control, Signals, and Systems and Advances in Continuous and Discrete Models. Recent recognitions include contributions to optimised lockdown strategies and flight emissions reduction, featured in PLOS and Science Magazine.

His academic supervision has produced impactful work, such as Cathie Wells' award-winning PhD project on flight emissions optimisation. He is committed to interdisciplinary research, often collaborating with engineering and environmental science teams to address complex systems challenges.