Romeo Sanchez Nigenda
School of Mechanical and Electrical Engineering · Universidad Autónoma de Nuevo León
Biography
Dr. Sánchez Nigenda is the Leader of the Computational Intelligence Research Group at UANL. He is a member of the National System of Researchers (Level I) and the Graduate Program in Artificial Intelligence and Optimization (PIAO). He also collaborates with the Doctoral program in Information Technologies (DTI) and the Master’s in Logistics at FIME. He has supervised numerous Doctoral and Master’s theses and has participated in various graduate and undergraduate committees. Representing UANL, he has been distinguished as an Associate Researcher of the National Transportation Laboratory and a project evaluator for CONACyT. He has also served as an evaluator on several committees, notably the Tecnos NL 4.0 Award, the National Science Expo, and the Fulbright-García Robles Program of the US-Mexico Commission for Educational and Cultural Exchange. His research interests include: AI planning algorithms and Machine Learning. Heuristic optimization. Multi-agent systems engineering.
Education
Romeo Sánchez is a Research Professor associated with the School of Mechanical and Electrical Engineering (FIME) at the Autonomous University of Nuevo León (UANL). He holds a Ph.D. in Computer Science from Arizona State University. He served as an intern at NASA’s Ames Research Center and as a Researcher at the Information Sciences Institute of the University of Southern California, where he received two Meritorious Service Awards for his work on autonomous agents. The technology developed during this time received the Best Demo Award at the International Conference on Autonomous Agents an...
Recent Scopus Publications
- Systematic review of teen pregnancy prevention programs using websites and chatbots
- Scheduling personalized study plans considering the stress factor
- Holding times to maintain quasi-regular headways and reduce real-time bus bunching
- Weighted U-NET++ and 2D-HMM Ensemble for Gastrointestinal Image Segmentation
- Parallel best-first search algorithms for planning problems on multi-core processors
Links
- ORCID https://orcid.org/0000-0001-7272-3759
- Google Scholar https://scholar.google.com/citations?user=bFPpEAwAAAAJ
- Scopus https://www.scopus.com/authid/detail.uri?authorId=14066552900
- Personal Weblink https://www.uanl.mx/investigadores/romeo-sanchez-nigenda/