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个人简介
Fernando Fernández is a faculty of the Computer Science Department of Universidad Carlos III de Madrid, since october 2005. He received his Ph.D. degree in Computer Science from University Carlos III of Madrid (UC3M) in 2003. He received his B.Sc. in 1999 from UC3M, also in Computer Science. Since 2001, he became assistant and associate professor at UC3M. In the fall of 2000, Fernando was a visiting student at the Center for Engineering Science Advanced Research at Oak Ridge National Laboratory (Tennessee). He was also a postdoctoral fellow at the Computer Science Department of Carnegie Mellon University (visit his old web page at CMU) since october 2004 until december 2005. He is the recipient of a pre-doctoral FPU fellowship award from Spanish Ministry of Education (MEC), a Doctoral Prize from UC3M, and a MEC-Fulbright postdoctoral Fellowship. He has more than 30 jounal and conference papers, mainly in the field of machine learning and planning (see a complete list of publications here). He is interested in intelligent systems that operate in continuous and stochastic domains. In his PhD thesis, he studied different discretization methods of the state space in Reinforcement Learning problems. When he arrived to CMU, he focused his research on the transfer of policies between different Reinforcement Learning tasks. Currently, his research is also focused on connecting classical planning methods with learning mechanism that allow to behave in dynamic and stochastic environments. Applications of his research include robot soccer, adaptive educational systems, tourism support tools and business intelligence.
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论文共 125 篇作者统计合作学者相似作者
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Jose Luis Perez, Javier Corrochano,Javier Garcia,Ruben Majadas, Cristina Ibanez-Llano, Sergio Perez,Fernando Fernandez
JOURNAL OF ARTIFICIAL INTELLIGENCE AND SOFT COMPUTING RESEARCHno. 4 (2023): 273-287
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Machine Learningno. 11 (2022): 4217-4247
Dimitri Voilmy,Karine Lan Hing Ting,Ana Iglesias,Rebeca Marfil,Juan Pedro Bandera,Fernando Fernandez, Quitterie De Roll
Healthcare Systemspp.129-144, (2022)
arxiv(2021)
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International Conference on AI in Finance (ICAIF) (2021): 19:1-19:9
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