DANIELE MORTARI
Professor

Biography
During past few years, my research has focused on: 1) orientation and position estimation of spacecraft, 2) attitude sensor data processing, 3) satellite constellations, and 4) various topics in linear algebra and numerical algorithms (function inversion, interpolation, differential equations, rotation in ndimensional real and complex spaces, etc.).
Editorship
 MDPI Mathematics. Special Issue “Computational Mathematics, Algorithms, and Data Processing“. Deadline for manuscript submissions: 31 December 2019.
 MDPI Sensors. Special Issue “Attitude Sensors“. Deadline for manuscript submissions: 31 March 2020.
Research Interest
 Attitude and position determination systems
 Satellite constellations design
 Sensor data processing
 Algorithms and linear algebra
Ph.D. Research Team
Carl Leake  (2019 NSTRF) 
Hunter Johnston  (2019 NSTRF) 
Stoian  Borissov 
Peter  Jones 
2019 Journal Publications
 Mai, T. and Mortari, D. “Theory of Functional Connections Applied to Nonlinear Programming under Equality Constraints,” Journal of Computational and Applied Mathematics, Submitted.
 Fialho, M.A.A. and Mortari, D. “Theoretical Limits of Star Sensors Accuracy,” [arXiv], MDPI Sensors, Submitted.
 Arnas, D., Leake, C., and Mortari, D. “The nDimensional kvector and its Application to Orthogonal Range Searching,” Applied Mathematics and Computation, Submitted.
 de Almeida, M.M., Mortari, D., Zanetti, R., and Akella, M. “QuateRA: the Quaternion Regression Algorithm,” AIAA Journal of Guidance, Control, and Dynamics, Submitted.
 BaniYounes, A. and Mortari, D. “Derivation of Exact Attitude Error Kinematics Equations, MDPI Sensors, In print
 Leake, C., Johnston, H., Smith, L., and Mortari, D. “Analytically Embedding Differential Equation Constraints into LeastSquares Support Vector Machines using the Theory of Functional Connections,” MDPI Machine Learning and Knowledge Extraction. (2019), 1(4), 10581083. Also in arXiv.1812.05571.
 Johnston, H., Leake, C., Efendiev, Y., and Mortari, D. “Selected Applications of the Theory of Connections: A Technique for Analytical Constraint Embedding,” MDPI Mathematics, 2019, 7(6), 537.
 Furfaro, R. and Mortari, D. “Leastsquares Solution of a Class of Optimal Guidance Problems via Theory of Connections,” ACTA Astronautica, In print.
 Mortari, D. and Leake, C. “The Multivariate Theory of Connections,” MDPI Mathematics, 2019, 7(3), 296.
 Mortari, D., Johnston, H., and Smith, L. “High Accurate LeastSquares Solutions of Nonlinear Differential Equations, Journal of Computational and Applied Mathematics, Vol. 352, 15 May 2019, pp. 293307.