Personal Data

Titus Octavian Pința

titus.pinta@ensta-paris.fr

www.github.com/titus-pinta

www.gitlab.com/titus.pinta

0000-0002-7027-4774

tituspinta.xyz

Date of Birth March 22^nd 1998 | Nationality Romanian

Work Experience

Education

Teaching Experience

Third-Party Funded Projects

1. Gaspard Monge Program for Optimization, Operations Research, and their Interactions with Data Science—Learning efficient neural network architectures using geometric control
2. SMAI-MODE Young Researchers Minisymposium&emdash;New Perspectives in Optimization for Machine Learning and Data Science
3. FMJH thematic postdoc—Inertial Acceleration in Higher Order Methods (ANR-22-EXES-0013)
4. Hi! PARIS—Higher Order Methods for Machine Learning (offer declined)

Publications

1. T. Pința, A Newton-Kantorovich Inverse Function Theorem in Quasi-Metric Spaces. Optimization. (under review).
2. T. Pința, A Newton-type Method for Non-smooth Under-determined Systems of Equations. Numer. Algorithms. (under review).
3. T. Pința, A Stochastic Newton-type Method for Non-smooth Optimization. Math. Program. (under review).
4. E. Cohen, D. R. Luke, T. Pința, S. Sabach, and M. Teboulle, A semi-Bregman proximal alternating method for a class of nonconvex problems: local and global convergence analysis. J. Global Optim. 89 (2024).
5. S. C. László, C. Alecsa, and T. Pința, An Extension of the Second Order Dynamical System that Models Nesterov's Convex Gradient Method. Appl. Math. Optim. 84 (2021).
6. A. Viorel, C. Alecsa, and T. Pința, Asymptotic analysis of a structure-preserving integrator for damped Hamiltonian systems. Discrete Contin. Dyn. Syst. 41 (2021).
7. C. Alecsa, T. Pința, and I. Boroș, New optimization algorithms for neural network training using operator splitting techniques. Neural Networks. 126 (2020).

Organized Conference Sessions

1. Optimization on Non-linear and Metric spaces, PGMO Days, Paris 2025

Invited Talks

1. Newton differentiability and non-smooth Newton-type methods, Séminaire Parisien d'Optimisation, Paris 2025
2. A Newton-type Method for Constrained Optimization, PGMO Days, Paris 2024
3. Operator Splitting Based Newton-type Method for Constrained Optimization, Optimization Techniques in Quantum Chemistry, Aachen 2024

Conference Talks

1. A Newton-Kantorovich-type Theorem in Quasi-Metric Spaces, PGMO Days, Paris, 2025
2. Newton-type methods and Newton differentiability, Young Applied Mathematicians Conference, Padua, 2025
3. A Stochastic Newton-type Method for Non-smooth Optimization, Young Applied Mathematicians Conference, Padua, 2025
4. A Stochastic Newton-type Method for Non-smooth Optimization, International Conference on Stochastic Programming, Paris, 2025
5. A Stochastic Newton-type Method for Non-smooth Optimization, EUROpt Workshop, Southampton, 2025
6. A Newton-type method for non-smooth vector optimization, EURO, Leeds, 2025
7. A Newton-type Method for Multicriteria Optimization, Spring School and Workshop on Variational Analysis and Optimization, Hanoi 2025
8. A Newton-type Method for Constrained Optimization, 4^th International Conference on Variational Analysis and Optimization, Santiago de Chile 2025
9. Newton-type Methods in Abstract Metric Spaces (poster), Congrès des Jeunes Chercheur.e.s en Mathématiques Appliquées, Lyon 2024
10. Random Newton-type Iterations with Application to Electronic Structure Determination, 21^st EUROpt Workshop, Lund 2024
11. Newton-type Methods in Abstract Metric Spaces (poster), Workshop on Nonsmooth Optimization and Applications, Antwerp 2024
12. Operator Splitting Based Newton-type Method for Constrained Optimization, 20^th EUROpt Workshop: Continuous Optimization Working Group is coming home, Budapest 2023
13. Operator Splitting Based Newton-type Method for Constrained Optimization, SIAM Conference on Optimization, Seattle 2023
14. Non-Euclidean Proximal Algorithms for Quadratic Composite Optimization: The Case of Mean Curvature Flow, GAMM Annual Meeting, Aachen 2022
15. Non-Euclidean Proximal Algorithms for Quadratic-Composite Optimization, SIAM Conference on Imaging Science, online 2022
16. Gradient Descent Methods for Machine Learning, Zilele Academice Clujene, Tiberiu Popoviciu Institute of Numerical Analysis, Cluj-Napoca 2019

Workshops

1. 8^th RTG 2088 Workshop: Discovering structure in complex data: Statistics meets Optimization and Inverse Problems, Mariaspring 2023
2. 7^th RTG 2088 Workshop: Discovering structure in complex data: Statistics meets Optimization and Inverse Problems, Goslar 2022
3. 6^th RTG 2088 Workshop: Discovering structure in complex data: Statistics meets Optimization and Inverse Problems, Mariaspring 2021
4. 23^rd Internet Seminar Evolutionary Equations, online 2020
5. 22^nd Internet Seminar Ergodic Theorems, Systems with Quasi-Discrete Spectrum, Wuppertal 2019
6. Numerical Linear Algebra at Tiberiu Popoviciu Institute of Numerical Analysis, Cluj-Napoca 2018
7. Approximation Theory at Tiberiu Popoviciu Institute of Numerical Analysis, Cluj-Napoca 2018

Reviewer for

• IMA Journal of Numerical Analysis
• Optimization
• SIAM Journal of Optimization
• Journal of Optimization Theory and Applications

Languages