Observatorio de I+D+i UPM
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INVESTIGADORES
ESTRUCTURAS DE I+D+I
ACTIVIDAD INVESTIGADORA
INNOVACIÓN
Investigador
Sandra Maria Gomez Canaval
Categoría Investigador
L.D. PRF.CONTR.DOCT.
Cargos actuales
SUBDIRECTOR DE E.T.S..
Sexo:
M
Escuela UPM
E.T.S DE ING. DE SISTEMAS INFORMÁTICOS
Departamento:
SISTEMAS INFORMÁTICOS (N)
Area Conocimiento
CC. DE COMPUTACION E INTELIGENCIA ARTIFICIAL
Grupo de Investigación:
Grupo de Modelización Matemática y Biocomputación
Email (Directorio UPM)
sm.gomez
upm.es
Datos de Memorias relacionados
Proyectos de I+D+i y generación de recursos
13 Proyectos de I+D+i
1: (2011)
NETWORKS OF BIO-INSPIRED PROCESSORS:HARDWARE IMPLENTATIONS
2: (2011)
SIMBOLO
3: (2012)
BUALAA TV
4: (2012)
NETWORKS OF BIO-INSPIRED PROCESSORS: HARDWARE IMPLEMENTATIONS
5: (2012)
Renovación y nuevas actividades de la red temática en computación biomolecular y biocelular
6: (2013)
Renovación y Nuevas Actividades de la Red Temática en Computación Biomolecular y Biocelular. TIN2011-15874-E (2012)
7: (2014)
FP7 ONTIC( Online Network Traffic Characterization)
8: (2014)
FP7 ONTIC( Online Network Traffic Characterization)
9: (2014)
ONTIC: ONline Network TraffIc Characterization
10: (2015)
CogNet : Building an Intelligent System of Insights and Action for 5G Network Management
11: (2015)
CogNet: Building an Intelligent System of Insights and Action for 5G Network Management
12: (2018)
Deep-Augur: Deep-Augur
13: (2018)
Telecom Diagnostics
Formación de Investigadores y Movilidad
3 Estancias y sabáticos recogidos en programas oficiales
1: (2011)
Estancia de investigación en el Grupo de investigación Modelos de Computación Natural - MCN del Departamento de Informática, Universidad de Verona, Italia
2: (2015)
Estancia de Investigación en el CEA
3: (2016)
Estancia posdoctoral en the 'National Institute of Research and Development for Biological Sciences (NIRDBS)' de Rumania
4 Tesis Doctorales
1: (2014)
"Computational Framework for the Definition of a Bioinspired Model on the Cellular Signalling".
2: (2017)
"General Methodology for Implementing Natural Computers in a Distributed Way" (provisional title). PhD Student: Karina Jiménez. University: Autónoma de Madrid. Doctorate in Computer Science and Telecommunications. Supervisors: Alfonso Ortega dela Puente and Sandra Gómez Canaval. Starting date: January 2015. Provisional end date: December 2017
3: (2017)
"Load Balancers for Virtual Network Functions in Software Defined Networks" (provisional title). PhD Student: Rodrigo López Manrique. University: Politécnica de Madrid. Doctorate in Computational Sciences and Technologies for Smart Cities. Supervisors: Alberto Mozo and Sandra Gómez Canaval. Starting date: September 2015. Provisional end date: December 2017.
4: (2017)
User Stateful Load Balancer for Virtual Network Functions (título provisional)
Difusión de Resultados de Investigación
29 Artículos en revistas
1: (2010)
P-System Communications Architectures Configuration Based on Growing Self-Organizing Maps
2: (2010)
Self-Assembly Process for Integrated Circuits Based on Carbon Nanotubes Using Microfluidic Devices
3: (2011)
Engineering with Biological Systems
4: (2012)
A Web Implementation of A Generalized NEP
5: (2012)
Genetic Network Representation using a Suitable IDE Software Tool to the Bacillus Mycobacterium Tuberculosis
6: (2013)
Simulating Metabolic Processes Using an Architecture Based on Networks of Bio-inspired Processors.
7: (2013)
Simulating Metabolic Processes Using an Architecture Based on Networks of Bio-inspired Processors.
8: (2013)
An Architecture forRepresenting Biological Processes based on Networks of Bio-inspired Processors
9: (2014)
Networks of Polarized Evolutionary Processors Are Computationally Complete
10: (2014)
Transducers based on Networks of Evolutionary Processors
11: (2015)
Distributed Simulation of NEPs Based On-Demand Cloud Elastic Computation
12: (2015)
How Nets of Evolutionary Processors (NEPs) Could be Simulated in a Distributed Way
13: (2015)
How to Search Optimal Solutions in Big Spaces with Networks of Bio-Inspired Processors
14: (2015)
Massively Parallel Unsupervised Feature Selection on Spark
15: (2015)
NPEPE: Massive Natural Computing Engine for Optimally Solving NP-complete Problems in Big Data Scenarios
16: (2016)
A Fast Iterative Algorithm for Improved Unsupervised Feature Selection
17: (2016)
Networks of splicing processors with evaluation sets as optimization problems solvers
18: (2016)
On the Computational Power of Networks of Polarized Evolutionary Processors. (JCR Journal Q2)
19: (2016)
Solving Optimization Problems by using Networks of Evolutionary Processors with Quantitative Filtering
20: (2016)
Solving optimization problems by using networks of evolutionary processors with quantitative filtering
21: (2016)
Towards Quantitative Networks of Polarized Evolutionary Processors: A Bio-Inspired Computational Model with Numerical Evaluations
22: (2016)
Transducers Based on Networks of Polarized Evolutionary Processors
23: (2017)
Iterative column subset selection
24: (2017)
On the computational power of networks of polarized evolutionary processors
25: (2017)
Probabilistic Leverage Scores for Parallelized Unsupervised Feature Selection
26: (2017)
Transducers based on networks of polarized evolutionary processors
27: (2018)
Forecasting short-term data center network traffic load with convolutional neural networks
28: (2018)
Iterative column subset selection
29: (2018)
Towards Probabilistic Networks of Polarized Evolutionary Processors
6 Capítulos de libros
1: (2010)
Bacterial Technology to Build Computers: a Survey
2: (2011)
Suitability of Artificial Neural Networks for Designing LoC Circuits
3: (2014)
Networks of Polarized Evolutionary Processors Are Computationally Complete
4: (2015)
Massively Parallel Unsupervised Feature Selection on Spark
5: (2015)
Massively Parallel Unsupervised Feature Selection on Spark
6: (2015)
NPEPE: Massive Natural Computing Engine for Optimally Solving NP-complete Problems in Big Data Scenarios
1 Conferencias invitadas en congresos
1: (2014)
Towards Quantitative Perspective in Networks of Evolutionary Processors. International Conference in Natural Information Technologies, Madrid, October 2014.
3 Cursos, seminarios y tutoriales
1: (2014)
Networks of Bio-inspired Processors: towards simulation of cellular processes
2: (2016)
Networks of Bioinspired Processors for Optimization Problems
3: (2017)
Networks of Evolutionary Processors: Words and Pictures
3 Libros
1: (2011)
Diccionario Informático en Lengua de Signos Española
2: (2014)
Proceedings of First International Workshop in Big Data and Applications
3: (2014)
Proceedings of First International Workshop in Big Data and Applications. (Funded by FP7 ONTIC project, no. 619633).
18 Ponencia en Congresos
1: (2010)
P-System Communications Architectures Configuration based on Growing Self-Organizing Maps
2: (2011)
Suitability of artificial neural network for designing LoC circuits
3: (2011)
Suitability of Artificial Neural Networks for Designing LoC Circuits
4: (2013)
Simulating Metabolic Processes Using an Architecture Based on Networks of Bio-inspired Processors.Unconventional Computation and Natural Computation
5: (2014)
Networks of Polarized Evolutionary Processors Are Computationally Complete
6: (2015)
Distributed Simulation of NEPs Based On-Demand Cloud Elastic Computation
7: (2015)
How Nets of Evolutionary Processors (NEPs) Could be Simulated in a Distributed Way
8: (2015)
How to Search Optimal Solutions in Big Spaces with Networks of Bio-Inspired Processors
9: (2015)
Massively Parallel Unsupervised Feature Selection on Spark.
10: (2015)
NPEPE: Massive Natural Computing Engine for Optimally Solving NP-complete Problems in Big Data Scenarios.
11: (2016)
A Fast Iterative Algorithm for Improved Unsupervised Feature Selection
12: (2016)
Feature Ranking and Selection for Big Data Sets
13: (2016)
Parallelized Unsupervised Feature Selection for Large-Scale Network Traffic Analysis
14: (2016)
Towards Quantititive Networks of Evolutionary Polarized Processors: a bio-inspired computational framework with numerical evaluations
15: (2017)
Deep convolutional neural networks for detecting noisy neighbours in cloud infrastructure.
16: (2017)
Deep convolutional neural networks for detecting noisy neighbours in cloud infrastructure
17: (2017)
Probabilistic Leverage Scores for Parallelized Unsupervised Feature Selection.
18: (2017)
PROBABILISTIC LEVERAGE SCORES FOR PARALLELIZED UNSUPERVISED FEATURE SELECTION (ALPHA CORE B)
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