New arXiv preprint

Laurențiu Leuștean and Horațiu Cheval published the preprint Quadratic rates of asymptotic regularity for the Tikhonov-Mann iteration on arXiv.

New talk in the LOS Seminar

Laurențiu Leuștean will give on Wednesday, June 23, 2021 at 14:00 the talk Proof mining and applications in nonlinear analysis and convex optimization. Part II in the LOS seminar.

New talk in the LOS Seminar

Laurențiu Leuștean will give on Tuesday, June 14, 2021 at 14:00 the talk Proof mining and applications in nonlinear analysis and convex optimization in the LOS seminar.

More news...


The Research Center for Logic, Optimization and Security (LOS) was founded in October 2020 by Laurenţiu Leuştean (head), Paul Irofti and Andrei Pătraşcu.
Our main objective is to stimulate interdisciplinary research in the fields of logic, optimization and security. We are interested both in fundamental research as well as in industrial applications. We focus on proof mining and applications to optimization, ergodic theory and nonlinear analysis, convex optimization for machine learning, signal processing and matrix factorization (dictionary learning), security, anomaly detection and anti-money laundry.

Hall 317, Faculty of Mathematics and Computer Science,
Academiei 14, 010014 Bucharest, Romania



Associated researchers


Horatiu Cheval



DDNET (12PD/2020)

The main goal of this project, called DDNET, is to adapt and propose new dictionary learning methods for solving untractable fault detection and isolation problems found in distribution networks. Given a large dataset of sensor measurements from the distribution network, the dictionary learning algorithms should be able to produce the subset of network nodes where faults exist.

Graphomaly (287PED/2020)

The proposed project, called Graphomaly, aims to create a Python software package for anomaly detection in graphs that model financial transactions, with the purpose of discovering fraudulent behavior like money laundering, illegal networks, tax evasion, scams, etc. Such a toolbox is necessary in banks, where fraud detection departments still use mostly human experts.

StOpAnomaly (143PD/2020)

StOpAnomaly aims to create, analyze and implement numerical optimization algorithms for large-scale optimization focusing on robust anomaly detection models based on decomposition and one-class classification. The research will be directed towards development of a toolbox containing scalable stochastic algorithms that can be used to detect several classes of anomalies in noisy large datasets.


Scientific seminars organized by LOS members


The working seminar of the LOS research center.


The logic seminar features talks on mathematical logic, philosophical logic and logical aspects of computer science.


The Cyber-security seminar brings together academic and industry folk to discuss hot topics in the field ranging from operating systems, static and dynamic analysis of executables to fraud detection and security centric machine learning techniques.