Publications
Updated versions: arXiv, Google Scholar, Researchgate, or contact me
Check here for publications listed in chronological order
Updated versions: arXiv, Google Scholar, Researchgate, or contact me
Check here for publications listed in chronological order
Time-optimal neural feedback control of nilpotent systems as a binary classification problem, S. Bicego, S. Gue, D. Kalise and N. Villamizar, [arxiv]
Separable Approximations of Optimal Value Functions and Their Representation by Neural Networks, M. Sperl, L. Saluzzi, D. Kalise and L. Grüne, 2025 [arxiv].
A multiscale Consensus-Based algorithm for multi-level optimization, M. Herty, Y. Huang, D. Kalise and H. Kouhkouh, Mathematical Models and Methods in Applied Sciences 35(10)(2025): 2207-2243 [arxiv, journal].
Control of high-dimensional collective dynamics by deep neural feedback laws and kinetic modelling, G. Albi, S. Bicego and D. Kalise, Journal of Computational Physics 539(2025):114229 [arxiv, journal].
Data/moment-driven approaches for fast predictive control of collective dynamics, G. Albi, S. Bicego, M. Herty, Y. Huang, D. Kalise and C. Segala, Model Predictive Control, Vol. 31 in Dynamic Modeling and Econometrics in Economics and Finance Series, Springer: 29-54, 2025 [arxiv, book].
Multi-level Optimal Control with Neural Surrogate Models, D. Kalise, E. Loayza-Romero, K. A. Morris and Z. Zhong, IFAC-PapersOnLine 58(17)(2024):292-297, [arxiv, journal].
Separable approximations of optimal value functions under a decaying sensitivity assumption, L. Gruene, D. Kalise, L. Saluzzi and M. Sperl, 2023 62nd IEEE Conference on Decision and Control (CDC), [arxiv, journal].
Consensus based optimization via jump-diffusion stochastic differential equations, D. Kalise, A. Sharma and M.V. Tretyakov, Mathematical Models and Methods in Applied Sciences 33(2)(2023): 289--339 [arxiv, journal].
Data-driven initialization of deep learning solvers for Hamilton-Jacobi PDEs, A. Borovykh, D. Kalise, A. Laignelet and P. Parpas, IFAC-PapersOnline 55(30)(2022): 168-173. [arxiv, journal].
Supervised learning for kinetic consensus control, G. Albi, S. Bicego and D. Kalise, IFAC-PapersOnline 55(30)(2022): 103-108 [arxiv, journal].
Gradient-augmented Supervised Learning of Optimal Feedback Laws Using State-dependent Riccati Equations, G. Albi, S. Bicego and D. Kalise. IEEE Control Systems Letters 6(2022): 836 -841 [arxiv, journal].
Supervised learning for optimal feedback laws, in Analysis of Data-driven Optimal Control, Oberwolfach Reports 18(2)(2021):1209--1257, [journal].
Optimal Feedback Law Recovery by Gradient-Augmented Sparse Polynomial Regression, B. Azmi, D. Kalise and K. Kunisch, Journal of Machine Learning Research 22(48)(2021):1--32 [journal (open access)].
Fast and robust consensus-based optimization via optimal feedback control, Y. Huang, M. Herty, D. Kalise and N. Kantas, to appear in SIAM Journal on Scientific Computing [arxiv].
Data-driven Tensor Train Gradient Cross Approximation for Hamilton-Jacobi-Bellman Equations, S. Dolgov, D. Kalise and L. Saluzzi, SIAM Journal on Scientific Computing 45(5)(2023):A2153-A2184 [arxiv, journal].
Optimizing semilinear representations for State-dependent Riccati Equation-based feedback control, S. Dolgov, D. Kalise and L. Saluzzi, IFAC-PapersOnline 55(30)(2022): 510-515 [arxiv, journal]
Tensor Decomposition Methods for High-dimensional Hamilton-Jacobi-Bellman Equations, S. Dolgov, D. Kalise and K. Kunisch. SIAM Journal on Scientific Computing 43(3)(2021): A1625--A1650 [arxiv, journal]
Sparse and switching infinite horizon optimal control with mixed-norm penalizations, D. Kalise, K. Kunisch and Z. Rao, ESAIM: Control, Optimisation and Calculus of Variations 26(61)(2020) [arxiv, journal]
Robust feedback control of nonlinear PDEs by polynomial approximation of Hamilton-Jacobi-Isaacs equations, D. Kalise, K. Kunisch and S. Kundu, SIAM Journal on Applied Dynamical Systems 19(2)(2020):1496–1524, [arxiv, journal]
Polynomial approximation of high-dimensional Hamilton-Jacobi-Bellman equations and applications to feedback control of semilinear parabolic PDEs, D. Kalise and K. Kunisch. SIAM Journal on Scientific Computing 40(2)(2018):A629--A652 [arxiv, journal].
Hamilton-Jacobi-Bellman Equations: Numerical Methods and Applications in Optimal Control, D. Kalise, K. Kunisch and Z. Rao (eds.), Vol. 21 De Gruyter - Radon Series on Computational and Applied Mathematics, 2018.
Infinite horizon sparse optimal control, D. Kalise, K. Kunisch, and Z. Rao Journal of Optimization Theory and Applications 172(2)(2017):481-517 [arxiv, journal]
Novel Directions in Optimization, Control and Games with Applications, M.S. Aronna, D. Kalise, and D. Tonon (eds.), Lecture Notes in Mathematics, Springer, 2017.
Local minimization algorithms for dynamic programming equations, D. Kalise, A. Kroener, and K. Kunisch. SIAM Journal on Scientific Computing 38(3)(2016):A1587--A1615 [arxiv, journal]
Smoothened quasi-time-optimal control for the torsional torque in a two-mass system, E. Fuentes, D. Kalise, and R. Kennel, IEEE Transactions on Industrial Electronics 63(6)(2016):3954--3963 [arxiv, journal]
Value iteration convergence of ε-monotone schemes for stationary Hamilton-Jacobi equation, O. Bokanowski, M. Falcone, R. Ferretti, L. Gruene, D. Kalise and H. Zidani, Discrete and Continuous Dynamical Systems - Series A 35(9)(2015), 4041 - 4070, [pdf]
An efficient policy iteration algorithm for the solution of dynamic programming equations, A. Alla, M. Falcone and D. Kalise, SIAM Journal on Scientific Computing 37(1)(2015), 181-200, [pdf]
An accelerated value/policy iteration scheme for optimal control problems and games, A. Alla, M. Falcone and D. Kalise, Numerical Mathematics and Advanced Applications - ENUMATH 2013, LNCSE 103(2015), 489-497, [pdf]
Cascade-free predictive speed control for electrical drives, E. Fuentes, D. Kalise, R.M. Kennel and J. Rodríguez, IEEE Transactions on Industrial Electronics 61(5)(2014), 2176 - 2184, [journal]
A high-order semi-Lagrangian/finite volume scheme for Hamilton-Jacobi-Bellman-Isaacs equations, M. Falcone and D. Kalise, System Modeling and Optimization, Springer, 105-117 (2014), [pdf,]
A semi-Lagrangian scheme for Lp-penalized minimum time problems, M. Falcone, D. Kalise and A. Kroener, Proceedings of the 21st International Symposium on Mathematical Theory of Networks and Systems, 1798-1803 (2014), [pdf]
Reduced-order minimum time control of advection-reaction-diffusion systems via dynamic programming, D. Kalise and A. Kroener, Proceedings of the 21st International Symposium on Mathematical Theory of Networks and Systems, 1196-1202 (2014), [pdf]
An accelerated policy iteration algorithm for the solution of dynamic programming equations, A. Alla, M. Falcone and D. Kalise, PAMM 13(1)(2013), 467-468, [journal]
Hierarchical clustering and dimensional reduction for optimal control of large-scale agent-based models, A. Monti, F. Diele and D. Kalise, 2025 [arxiv].
Linearised feedback stabilization of the McKean-Vlasov PDE, D. Kalise, L.M. Moschen and G.A. Pavliotis, 2025 [arxiv].
Parallel-in-time preconditioning for time-dependent variational mean field games, H. Wolles-Ljósheim, D. Kalise, J.W. Pearson and F.J. Silva, 2025 [arxiv].
A Spectral Approach to Optimal Control of the Fokker-Planck Equation, D. Kalise, L. Moschen, G.A. Pavliotis and U. Vaes, IEEE Control Systems Letters, vol. 9, pp. 504-509, 2025 [arxiv, journal].
Collisionless and Decentralized Formation Control for Strings, Y.-P. Choi, D. Kalise and A. Peters, Networks & Heterogeneous Media 20(3)(2025):844-867 [arxiv, journal].
A multiscale Consensus-Based algorithm for multi-level optimization, M. Herty, Y. Huang, D. Kalise and H. Kouhkouh, Mathematical Models and Methods in Applied Sciences 35(10)(2025): 2207-2243 [arxiv, journal].
Computation and Control of Unstable Steady States for Mean Field Multiagent Systems, S. Bicego, D. Kalise and G.A. Pavliotis, Proceedings of the Royal Society A 481: 20240476 (2025) [arxiv, journal].
A Total Variation Flow Scheme for Ergodic Mean Field Games, D. Kalise, A. Oliveiro and D. Ruiz-Balet, 2024 [arxiv].
Computation and Control of Unstable Steady States for Mean Field Multiagent Systems, in High-Dimensional Control Problems and Mean-Field Equations with Applications in Machine Learning, Oberwolfach Report 56/2024.
Convex Optimisation Methods for Variational Mean Field Games, in Control Methods in Hyperbolic PDEs, Oberwolfach Report 52/2023.
Moment-driven predictive control for mean-field collective dynamics, G. Albi, M. Herty, D. Kalise and C. Segala, SIAM Journal on Optimization and Control 60(2)(2022): 814-841 [arxiv, journal].
Controlling swarms towards flocks and mills, J.A. Carrillo, D. Kalise, F. Rossi and E. Trélat., SIAM Journal on Optimization and Control 60(3)(2022):1863--1891 [arxiv, journal].
Featured Book Review, Crowds in equations: an introduction to the microscopic modeling of crowds, SIAM Rev. 62 (2020), no. 3, 729–731, [journal] .
A collisionless singular Cucker-Smale model with decentralized forcing and applications to formation control for UAVs, Y.~P. Choi, D. Kalise, A. Peters and J. Peszek. SIAM Journal on Applied Dynamical Systems 18(4)(2019):1954-1981 [arxiv, journal].
On the implementation of a primal-dual algorithm for second order time-dependent mean field games with local couplings, L. Brice\~no-Arias, D. Kalise, Z. Kobeisi, M. Lauriere, A. Mateos-González and F.J. Silva, , ESAIM: Proceedings and Surveys 65(2019):330-348 [arxiv, journal].
Optimal consensus control of the Cucker-Smale model, J.A. Carrillo, M. Bongini, D. Kalise and R. Bailo.IFAC-PapersOnLine 51(3)(2018):1-6 [arxiv, journal].
Suboptimal stabilization of agent-based dynamics through nonlinear feedback control synthesis, M. Herty and D. Kalise, 2018 IEEE 14th International Conference on Control and Automation (ICCA), 556--561, 2018 [preprint, journal].
Proximal methods for stationary Mean Field Games with local couplings, L. Briceño--Arias, D. Kalise, and F.J. Silva. SIAM Journal on Control and Optimization 56(2)(2018):801-836 [arxiv, journal].
(Sub)Optimal feedback control of mean-field multi-population dynamics: a Boltzmann-Bellman approach, G. Albi and D. Kalise IFAC-PapersOnLine 51(3)(2018):86-91, [arxiv, journal].
Multiscale optimal control of collective behavior phenomena, in Challenges in Optimal Control of Nonlinear PDE Systems, Oberwolfach Reports 15(2)(2018):941-1020 [journal].
Mean field control hierarchy, G. Albi, Y.P. Choi, M. Fornasier and D. Kalise, Applied Mathematics & Optimization 76(1)(2017):93-135 [arxiv, journal].
A Boltzmann approach to mean-field sparse feedback control, G. Albi, M. Fornasier and D. Kalise, IFAC-PapersOnLine 50(1)(2017):2898-2903 [arxiv, journal].
Invisible control of self-organizing agents leaving unknown environments, G. Albi, M. Bongini, E. Cristiani, and D. Kalise, SIAM Journal on Applied Mathematics, 76(4)(2016):1683-1710 [arxiv, journal].
(Un)conditional consensus emergence under perturbed and decentralized feedback controls, M. Bongini, M. Fornasier and D. Kalise, Discrete and Continuous Dynamical Systems - Series A 35(9)(2015), 4071 - 4094, [pdf].
Current Sheet Thickness in the Plasma Focus Snowplow Model, J. Fernández, E. Hernández, D. Kalise, V. Muñoz, D. Pasten and M. Zambra, Journal of Plasma and Fusion Research Series 8(2009), 879-882, [pdf].
Optimal Control for Thin Film Flow On Flexible Topography, S. Alrashidy, A. Kalogirou, D.Kalise and K. van der Zee, 2025 [arxiv].
Statistical Proper Orthogonal Decomposition for model reduction in feedback control, S. Dolgov, D. Kalise and L. Saluzzi, 2023 [arxiv].
State-dependent Riccati equation feedback stabilization for nonlinear PDEs, A. Alla, D. Kalise and V. Simoncini, Advances in Computational Mathematics 49(2023): 9 [arxiv, journal (open access)].
Optimization and Control for Partial Differential Equations: Uncertainty quantification, open and closed-loop control, and shape optimization, M. Heinkenschloss, R. Herzog, D. Kalise, G. Stadler and E. Trélat (eds.) Vol. 29 De Gruyter - Radon Series on Computational and Applied Mathematics, 2022.
Optimal Actuator Design for the Euler-Bernoulli Vibration Model Based on LQR Performance and Shape Calculus, M. S. Edalatzadeh, D. Kalise, K. A. Morris and K. Sturm. IEEE Control Systems Letters 6(2022):1334--1339 [arxiv, journal].
Optimal actuator design based on shape calculus, D. Kalise, K. Kunisch and K. Sturm. Mathematical Models and Methods in Applied Sciences 28(13)(2018): 2667-2717 [arxiv, journal].
HJB-POD feedback synthesis approach for the wave equation, A. Alla, D. Kalise and M. Falcone, Bulletin of the Brazilian Mathematical Society 47(1)(2016), 51 - 64, [pdf]
Reduced-order LQG control of a Timoshenko beam model, P. Braun, E. Hernández and D. Kalise ,Bulletin of the Brazilian Mathematical Society 47(1)(2016), 143 - 155, [pdf]
A locking-free scheme for the LQR control of a Timoshenko beam, E. Hernández, D. Kalise and E. Otárola, Journal of Computational and Applied Mathematics 235(5)(2011), 1383-1393, [pdf]
Numerical approximation of the LQR problem in a strongly damped wave equation, E. Hernández, D. Kalise and E. Otárola, Computational Optimization and Applications 47(1)(2010), 161-178, [pdf]
Modelamiento y control activo de vibraciones en estructuras delgadas (in Spanish), Civil Mathematical Engineering Thesis, UTFSM (Chile), 89 pp. (2008), [pdf]
Minimising emissions from flights through realistic wind fields with varying aircraft weights, D. Kalise, N.K. Nichols, D.I.A. Poll, C.A. Wells and P.D. Williams, Transportation Research Part D 117(2023): 103660 [journal (open access)]
Biologically inspired herding of animal groups by robots, A. J. King, S. J. Portugal, D. Strömbom, R. P. Mann, J. Carrillo, D. Kalise, G. de Croon, H. Barnett, P. Scerri, R. Gross, D. Chadwick, M. Papadopolou, Methods in Ecology and Evolution, 00, 1– 9 (2023) [journal (open access)]
The role of airspeed variability in fixed-time, fuel-optimal trajectory planning, D. Kalise, N.K. Nichols, D.I.A. Poll, C.A. Wells and P.D. Williams, Optimization and Engineering (2023), [journal (open access)].
Using mobility data in the design of optimal lockdown strategies for the COVID-19 pandemic, R. Dutta, S.N. Gomes, D. Kalise and L. Pacchiardi. PLoS Computational Biology 17(8): e1009236, 2021 [journal (open access)]
Reducing transatlantic flight emissions by fuel-optimised routing, D. Kalise, N. Nichols, I. Poll, C.A. Wells and P.D. Williams, Environmental Research Letters 16:025002, 2021 [journal (open access)]
A WENO-TVD finite volume scheme for the approximation of atmospheric phenomena, D. Kalise, Hyperbolic Problems: Theory, Numerics, Applications, AIMS Series on Applied Mathematics 8(2014), 717-724, [pdf]
Modeling and numerical approximation of a 2.5D set of equations for mesoscale atmospheric processes, D. Kalise and I. Lie, Journal of Computational Physics 231(2012), 7274-7298, [pdf]
General requirement for harvesting antennae at Ca2+ and H+ sinks, F. Barros, D. Kalise and C. Martínez, Frontiers in Neuroenergetics (2010), 2-27, [pdf]
High-resolution schemes for the approximation of atmospheric phenomena, Ph.D. Thesis, University of Bergen, 163 pp. (2012), [pdf]
A numerical study of a WENO-TVD finite volume scheme for the numerical simulation of atmospheric advective and convective phenomena, preprint[pdf]
D. Kalise, I. Lie, and E.F. Toro. High-order finite volume schemes for layered atmospheric models, preprint [pdf]