Autumn school co-organized by LOS

Institute for Logic and Data Science, Faculty of Mathematics and Computer Science, University of Bucharest and LOS organize the ILDS-FMI Coq and Lean Autumn School 2023 in the period September 20-23, 2023.

Participation by LOS members at Logic Colloquium 2023

Horațiu Cheval (invited in the Applied Proof Theory Special Session), Laurențiu Leuștean and Andrei Sipoș have all presented their recent research at Logic Colloquium 2023, the annual European meeting of the Association for Symbolic Logic.

New paper in Mathematical Logic Quarterly

Andrei Sipoş published (in collaboration with Liviu Păunescu) the paper A proof-theoretic metatheorem for tracial von Neumann algebras in Mathematical Logic Quarterly.

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

PhD Students

Research Assistants

Undergraduate and Master Students

Cristina Borza


Nicoleta Dumitru


Dafina Trufas


Former Members


NetAlert (SOL4/2021)

NetAlert aims to create a hardware-software sensor solution for detecting anomalies in computer networks based on the monitoring and analysis of data packets. The network-mounted sensor will provide real-time alerts on abnormal traffic behaviors using two complementary approaches:
(i) static analysis based on rules and behavioral patterns;
(ii) machine learning (ML) analysis without prior expert knowledge.

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


The seminar presents recent results on proof mining.

Past seminars