Isaac Lozano-Osorio

Universidad Rey Juan Carlos
Madrid, Spain

PhD in Artificial Intelligence

Bio

Isaac Lozano-Osorio graduated with a double degree in Computer Science and Computer Engineering from Universidad Rey Juan Carlos, where he was awarded the prize for the Best Final Project. He completed his Master in Artificial Intelligence Research at UIMP with a final average grade of 8.40 and is now a PhD student and university researcher at URJC, member of the Group for Research in Algorithms For Optimization (GRAFO).

His main research interests focus on the applicability of Artificial Intelligence, particularly heuristics and metaheuristics, for solving hard optimization problems related to Social Network Influence Maximization Problems. He has 63 citations according to his ResearchGate profile and is passionate about programming competitions, currently coaching teams at regional/national and European levels.

As a hobby for more than a decade, he plays chess at national level, having been champion on several occasions both individually and by teams in provincial championships in Toledo. This passion led him to develop YottaChess, an online database of all players available at http://yottachess.com/.

Research Focus

Social Network Optimization: His primary research focuses on influence maximization problems in social networks, developing metaheuristic algorithms to solve complex optimization challenges in this domain.

Target Set Selection (TSS) Problem: He proposes the use of metaheuristics for solving the TSS problem, which emerges in the context of influence maximization where the objective is to maximize the number of active users when spreading information throughout a social network.

Budget Influence Maximization Problem (BIMP): His research tackles BIMP, proposing realistic scenarios where the cost of selecting each node is different, modeled by having a budget that can be spent to select network users with associated costs.

Metaheuristic Algorithms: He specializes in developing GRASP (Greedy Randomized Adaptive Search) frameworks and other metaheuristic approaches for hard optimization problems in graph-based scenarios.

Education

PhD in Artificial Intelligence - Universidad Rey Juan Carlos (2020-2024)
MEng in Artificial Intelligence - Universidad Internacional Menéndez Pelayo (2019-2020)
Computer Science & Hardware Engineering - Universidad Rey Juan Carlos (2015-2019)

Recent Recognition

Best Student Paper Award - XV Congreso Español de Metaheurísticas, Algoritmos Evolutivos y Bioinspirados (MAEB 2024)
Research Publications - Work published in various academic venues with material publicly available at https://grafo.etsii.urjc.es/TSS

Awards & Competitions

Research Merits:

Special mention in the E-Madrid congress in the TFG BlueThinking
Winner II Call of the Social Council Awards for Young Researchers

Programming Competitions:

Winner category Postgraduate or professor NO UCM in Las 12 Uvas 2019 and 2020
Third place in T3chFest 2019 Contest
Third place in AdaByron Competition 2019
Participation in SWERC (Southwest Europe Competitive Programming Championship) 2017 and 2018 in Paris representing Universidad Rey Juan Carlos, obtaining in the last year the European diploma

Cybersecurity Competitions:

Winner of the II National CyberLeague GC (as part of ‘Heappies’ team)
Second place in the BitUp 2021 congress contest

Personal Projects

YottaChess - Online database of chess players (http://yottachess.com/)
Competitive Programming Coaching - Training teams for regional/national and European competitions
Chess Championships - National level player with multiple championships in Toledo and Castilla la Mancha