Eunice López Camacho

Ph. D. Information Technology and Communications

I am a researcher in Computer Science. My work lies at the interface of Computing Science and Operational Research with emphasis on optimisation, hyper-heuristics, and evolutionary computation. I have explored the bin packing problem domain, mainly for 2D irregular shapes. I am interested in analyzing problem features to discover how these features relate to heuristics performance. I have implemented some Statistical tools in my last investigations.
My teaching carreer is around Math, Statistics and Computer Science. In the past I have participated in research projects related to Education and Social Sciences, analyzing data from surveys and academic evaluations.

Research interests

Evolutionary Computation - Optimization - Heuristics - Hyper-heuristics - Bin packing - Statistical analysis - Data mining - Forecasting

Research projects

ITESM Strategic Project: Intelligent Learning for Pattern Recognition and Logistics Problems (Research Member) 2012-2015.
CONACyT Project: Working Towards the Generality of Hyper-heuristics for Optimization Problems (Research Member) 2009-2013.
CONACyT Project: Diagnóstico del Programa Oportunidades en el desempeño académico y su impacto en el abatimiento de desigualdades educativas en comunidades rurales y semi-urbanas (Research Member) 2005-2007.


List of publications
Google scholar, Scopus
Irregular test instances artificially created for the 2D bin packing problem: Terashima 1, Terashima 2.
Java source code for solving 2D irregular instances with several heuristics. Convex and non-convex shapes can be handled.


Sistemas Aleatorios
Fundamentos de Computación (Análisis de Algoritmos)
Estadística I
Estadística II
Probabilidad y Estadística
Estadística Administrativa I
Estadística Administrativa II
Introducción a las Matemáticas
Matemáticas I

Email: eunice.lopez (at)
Room: A4-122B.
Tel: (52) 81-83582000, x 4528.
Tecnológico de Monterrey, Campus Monterrey
Av. Eugenio Garza Sada #2501 Sur
Monterrey, N.L. 64849
Office hours