Wouter Caarls

  • Endereço para acessar este CV: http://lattes.cnpq.br/1164394299894445
  • Última atualização do currículo em 11/10/2018


Wouter Caarls obtained a Master's degree in Artificial Intelligence from the University of Amsterdam in 2002, and continued to do a PhD at the Delft University of Technology, on the subject of intelligent cameras, completed in 2008. After postdoctoral fellowship positions working on microscope automation and robotics, he is now an assistant professor working on reinforcement learning for robotics at the Pontifical Pontifical Catholic University of Rio de Janeiro. (Texto informado pelo autor)


Identificação


Nome
Wouter Caarls
Nome em citações bibliográficas
CAARLS, W.;CAARLS, WOUTER;Wouter Caarls;Caarls, Wouter;W. Caarls;Caarls, W.;WOUTER CAARLS

Endereço


Endereço Profissional
Pontifícia Universidade Católica do Rio de Janeiro, Reitoria, Departamento de Engenharia Elétrica.
Pontifícia Universidade Católica - PUC
Gávea
22451900 - Rio de Janeiro, RJ - Brasil
Telefone: (21) 35271231


Formação acadêmica/titulação


2002 - 2008
Doutorado em Applied Sciences.
Delft University of Technology, TU DELFT, Holanda.
Título: Automated Design of Application-Specific Smart Camera Architectures, Ano de obtenção: 2008.
Orientador: Pieter Jonker.
1997 - 2002
Mestrado em Artificial Intelligence.
Universiteit van Amsterdam, UvA, Holanda.
Título: Genetic Algorithm Visualisation,Ano de Obtenção: 2002.
Orientador: Peter Sloot.
Coorientador: Jaap Kaandorp.




Formação Complementar


2005 - 2005
Extensão universitária em One-month internship (Shorin Kyo). (Carga horária: 160h).
NEC Corporation, NEC, Japão.
2002 - 2002
Extensão universitária em One-month internship (Richard Kleihorst). (Carga horária: 160h).
Philips Research Eindhoven, PRE, Holanda.


Atuação Profissional



Universidade Federal do Rio de Janeiro, UFRJ, Brasil.
Vínculo institucional

2014 - 2016
Vínculo: Scholarship, Enquadramento Funcional: Bolsista Jovem Talento Ciência sem Fronteiras, Carga horária: 40


Delft University of Technology, TU DELFT, Holanda.
Vínculo institucional

2009 - 2014
Vínculo: , Enquadramento Funcional: Postdoctoral research fellow, Carga horária: 38, Regime: Dedicação exclusiva.


Max Planck Institute for Biophysical Chemistry, MPIBPC, Alemanha.
Vínculo institucional

2007 - 2009
Vínculo: Formal labor contract, Enquadramento Funcional: Postdoctoral research fellow, Carga horária: 40, Regime: Dedicação exclusiva.


Pontifícia Universidade Católica do Rio de Janeiro, PUC-Rio, Brasil.
Vínculo institucional

2016 - Atual
Vínculo: Formal labor contract, Enquadramento Funcional: Professor Assistente I, Carga horária: 40, Regime: Dedicação exclusiva.



Projetos de pesquisa


2014 - 2016
KOROIBOT
Descrição: The goal of the KoroiBot project is to enhance the ability of humanoid robots to walk in a dynamic and versatile fashion in the way humans do. Research and innovation work in KoroiBot will mainly target novel motion control methods for existing hardware, but it will also derive optimized design principles for next generation robots. By doing so, KoroiBot addresses the ambitious goals set for the humanoid robots of the 21st century which are supposed to work and replace humans e.g. in households, disaster sites or space missions but which still lack the very fundamental ability to walk in a human-like fashion. Compared to all the intelligence that humanoids have to acquire to perform these tasks, the demand for an improved walking performance seems simple, but it is in fact very challenging, and the motion abilities of contemporary humanoids are still far behind their human role models. Human gaits are at the same time efficient, robust and versatile but gaits of humanoids or bipedal robots are at best good in one of these areas. This problem is not only linked to the present hardware, but also to a large extent to the control principles and the software used..
Situação: Concluído; Natureza: Pesquisa.
2014 - 2016
On-line Model-learning Policy Search
Descrição: Reinforcement learning is a powerful method for learning control policies in a variety of applications such as robotics, scheduling, and traffic and network congestion control. Because the environments in which such systems must work are forever changing, it is infeasible to pre-program a solution that works in all cases. Through trial and error, a reinforcement learning agent optimizes a control policy for the desired task without prior knowledge of the environment. However, especially in robotics its applicability has thus far been limited by long learning times. In this project, we aim to develop fully on-line model-learning policy search techniques, thereby combining the low number of trials of model-learning policy search with the short computation time of on-line methods. We have recently developed such an on-line model learning method in the context of value-based reinforcement learning, where we achieved a speedup of two orders of magnitude over standard on-line techniques. An effective combination of the two should allow effcient learning of complex control policies for systems with many state variables..
Situação: Concluído; Natureza: Pesquisa.
Alunos envolvidos: Graduação: (1) .
Integrantes: Wouter Caarls - Integrante / Daniel Sadoc Menasche - Coordenador.
2013 - 2017
Factory-in-a-day
Descrição: Be it the packing and quality checking of fruit, the polishing of steel moulds or the filling of a spray-painting machine, all these processes have one thing in common: they are usually done manually because there is no robot or automated process that can do the job as efficient as a human worker. Today, setting up a robotic system takes at least 3 months and the costs are immense. SMEs usually only have small production batches due to seasonal on-off production. State-of-the-art systems don?t provide the flexibility they need to stay competitive on a global market. For these reasons SMES in Europe rarely use advanced robot technology. Using innovative design templates and parameterized learning by demonstration through domain-specific task libraries, the Factory-in-a-day project aims to reduce the installation time to a single day..
Situação: Concluído; Natureza: Pesquisa.
2007 - 2010
FLUOROMAG
Descrição: The project of the consortium has two elements. The first is the development of other classes of still smaller NPs, i.e. with sizes below 10 nm (less than a millionth of a cm): fluorescent noble-metal "nanodots" and magnetic NPs. These materials are superior to conventional fluorophores in that they exhibit extreme photo- and chemical stability. The nanodots should have reduced toxicity and greater target accessibility than quantum dots, yet offer a similar detection sensitivity. They will be derivatized and tested for specific recognition of biomolecules such as tumor markers (for breast cancer) and global viral disease (Hepatitis C and Dengue Fever). Other core-shell "onion-like" NPs developed by the partner in Santiago de Compostela have diverse and strong magnetic properties and will be tested for their application in micro-chip and MRI diagnostics. In a parallel effort, several of the partners will optimize the design and performance of a new type of high-speed, sensitive, optically sectioning microscope known as the Programmable Array Microscope (PAM), for use in both the basic research and medical communities. The PAM is very versatile in that it implements many imaging modalities and has been under development in the Molecular Biology Dept. for the past 10 years. It has single-NP sensitivity, and is ideally suited for measurements of thick samples such as tissue slices and patterned arrays, important objects for diagnostic tests..
Situação: Concluído; Natureza: Pesquisa.
2006 - 2012
FALCON
Descrição: The challenge to develop a fully integrated and automated logistics warehouse as a complex ?system-of-systems?, is to increase performance under stochastic conditions whilst maintaining reliability. Basically the research projects comprises of three lines of attention: 1. Through high-level simulation, system-level requirements can be decomposed and propagated to the component level. 2. Developing specific mechatronic components, as well as the redesign and evaluation of both the overall system- and component architectures. 3. Reliable integration of components into systems requires a system-level control approach that involves the appropriate sensors and actuators, as well as relevant in formation architectures to synchronize the virtual world with the real world. In addition to these research topics, the integrity of the relationship between the conceptual design and its actual implementation is addressed as a crucial condition for achieving the correct level of dependability of the resulting system-of-systems..
Situação: Concluído; Natureza: Pesquisa.
2002 - 2008
SMARTCAM
Descrição: The advent and subsequent popularity of low cost, low power CMOS vision sensors enables us to integrate processing logic on the camera chip itself, thereby creating so-called smart sensors. The SmartCam project investigates these new opportunities and contributes to a better and more quantitatively guided design trajectory. In particular, it will investigate the impact of current applications, define relevant architectural parameters and develop an architectural template, enhance existing application mapping environments for SIMD (Single-Instruction, Multiple-Data) and ILP (Instruction-Level Parallel) processors, and perform two case studies. The work will focus on creating an environment for exploring the design space parametrized by the architectural template and integrating this with the application mapping environment..
Situação: Concluído; Natureza: Pesquisa.
Alunos envolvidos: Mestrado acadêmico: (0) Doutorado: (2) .
Integrantes: Wouter Caarls - Integrante / Pieter Jonker - Coordenador / Henk Corporaal - Integrante / Hamed Fatemi - Integrante.


Revisor de periódico


2011 - 2011
Periódico: IEEE Transactions on Neural Networks
2013 - Atual
Periódico: IEEE Transactions on Neural Networks and Learning Systems
2013 - Atual
Periódico: Biological Cybernetics
2012 - Atual
Periódico: Journal of Real-Time Image Processing
2010 - Atual
Periódico: IEEE Transactions on Automation Science and Engineering
2013 - Atual
Periódico: Cluster Computing
2014 - Atual
Periódico: Asian Journal of Control
2015 - Atual
Periódico: Artificial Intelligence Review


Áreas de atuação


1.
Grande área: Outros / Área: Robótica, Mecatrônica e Automação.
2.
Grande área: Ciências Exatas e da Terra / Área: Ciência da Computação / Subárea: Sistemas de Computação/Especialidade: Arquitetura de Sistemas de Computação.


Idiomas


Holandês
Compreende Bem, Fala Bem, Lê Bem, Escreve Bem.
Inglês
Compreende Bem, Fala Bem, Lê Bem, Escreve Bem.
Alemão
Compreende Razoavelmente, Fala Razoavelmente, Lê Razoavelmente, Escreve Pouco.
Português
Compreende Razoavelmente, Fala Razoavelmente, Lê Bem, Escreve Razoavelmente.


Prêmios e títulos


2002
Cum Laude, University of Amsterdam.


Produções



Produção bibliográfica
Artigos completos publicados em periódicos

1.
CALLI, BERK2018CALLI, BERK ; Caarls, Wouter ; WISSE, MARTIJN ; JONKER, PIETER P. . Active Vision via Extremum Seeking for Robots in Unstructured Environments: Applications in Object Recognition and Manipulation. IEEE Transactions on Automation Science and Engineering, v. 15, p. 1810-1822, 2018.

2.
KORYAKOVSKIY, IVAN2018KORYAKOVSKIY, IVAN ; KUDRUSS, MANUEL ; VALLERY, HEIKE ; BABUSKA, ROBERT ; Caarls, Wouter . Model-Plant Mismatch Compensation Using Reinforcement Learning. IEEE Robotics and Automation Letters, v. 3, p. 2471-2477, 2018.

3.
REIFFERS-MASSON, ALEXANDRE2017REIFFERS-MASSON, ALEXANDRE ; HARGREAVES, EDUARDO ; ALTMAN, EITAN ; Caarls, Wouter ; MENASCHÉ, DANIEL S. . Timelines are Publisher-Driven Caches. Performance Evaluation Review, v. 44, p. 26-29, 2017.

4.
KORYAKOVSKIY, IVAN2017KORYAKOVSKIY, IVAN ; KUDRUSS, MANUEL ; BABU?KA, ROBERT ; Caarls, Wouter ; KIRCHES, CHRISTIAN ; MOMBAUR, KATJA ; SCHLÖDER, JOHANNES P. ; VALLERY, HEIKE . Benchmarking model-free and model-based optimal control. Robotics and Autonomous Systems (Print), v. 92, p. 81-90, 2017.

5.
PALMA, BRUNO2016PALMA, BRUNO ; LIMA, CABRAL ; Caarls, Wouter ; VETTORAZZI, DANILO . Wich Probabilistic Roadmap method should be used by a robot in an actual environment? An analysis of the main methods through simulations. Revista IEEE América Latina, v. 14, p. 2020-2025, 2016.

6.
WOLFSLAG, W.J.2015WOLFSLAG, W.J. ; PLOOIJ, M.C. ; Caarls, W. ; VAN WEPEREN, S. ; LOPES, G.A.D. . Dissipatively actuated manipulation. Control Engineering Practice, v. 34, p. 68-76, 2015.

7.
Caarls, Wouter2015 Caarls, Wouter; SCHUITEMA, ERIK . Parallel Online Temporal Difference Learning for Motor Control. IEEE Transactions on Neural Networks and Learning Systems, v. 27, p. 1-1, 2015.

8.
AKMAN, OYTUN2013AKMAN, OYTUN ; POELMAN, RONALD ; CAARLS, WOUTER ; JONKER, PIETER . Multi-cue hand detection and tracking for a head-mounted augmented reality system. Machine Vision and Applications (Internet), v. 24, p. 931-946, 2013.

9.
CAARLS, W.2011 CAARLS, W.; RIEGER, B. ; DE VRIES, A.H.B. ; ARNDT-JOVIN, D.J. ; JOVIN, T.M. . Minimizing light exposure with the programmable array microscope. Journal of Microscopy (Print), v. 241, p. 101-110, 2011.

10.
KANTELHARDT, SVEN R.2010KANTELHARDT, SVEN R. ; CAARLS, WOUTER ; DE VRIES, ANTHONY H. B. ; HAGEN, GUY M. ; JOVIN, THOMAS M. ; SCHULZ-SCHAEFFER, WALTER ; ROHDE, VEIT ; GIESE, ALF ; ARNDT-JOVIN, DONNA J. . Specific Visualization of Glioma Cells in Living Low-Grade Tumor Tissue. Plos One, v. 5, p. e11323, 2010.

11.
CAARLS, WOUTER2010CAARLS, WOUTER; SOLEDAD CELEJ, M. ; DEMCHENKO, ALEXANDER P. ; JOVIN, THOMAS M. . Characterization of Coupled Ground State and Excited State Equilibria by Fluorescence Spectral Deconvolution. Journal of Fluorescence, v. 20, p. 181-190, 2010.

12.
CELEJ, M. SOLEDAD2009CELEJ, M. SOLEDAD ; CAARLS, WOUTER ; DEMCHENKO, ALEXANDER P. ; JOVIN, THOMAS M. . A Triple-Emission Fluorescent Probe Reveals Distinctive Amyloid Fibrillar Polymorphism of Wild-Type α-Synuclein and Its Familial Parkinson-s Disease Mutants. Biochemistry, v. 48, p. 7465-7472, 2009.

13.
HAGEN, GUY M.2009HAGEN, GUY M. ; CAARLS, WOUTER ; LIDKE, KEITH A. ; DE VRIES, ANTHONY H.B. ; FRITSCH, CORNELIA ; BARISAS, B. GEORGE ; ARNDT-JOVIN, DONNA J. ; JOVIN, THOMAS M. . Fluorescence recovery after photobleaching and photoconversion in multiple arbitrary regions of interest using a programmable array microscope. Microscopy Research and Technique (Online), v. 72, p. 431-440, 2009.

14.
ARNDT-JOVIN, D.J.2009ARNDT-JOVIN, D.J. ; KANTELHARDT, S.R. ; CAARLS, W. ; DE VRIES, A.H.B. ; GIESE, A. ; JOVIN, T.M. . Tumor-Targeted Quantum Dots Can Help Surgeons Find Tumor Boundaries. IEEE Transactions on Nanobioscience, v. 8, p. 65-71, 2009.

15.
CAARLS, W.2006CAARLS, W.. Skeletons and Asynchronous RPC for Embedded Data and Task Parallel Image Processing. IEICE Transactions on Information and Systems, v. E89-D, p. 2036-2043, 2006.

Capítulos de livros publicados
1.
HAGEN, GUY M. ; LIDKE, KEITH A. ; Rieger, Bernd ; Lidke, Diane S. ; Caarls, Wouter ; ARNDT-JOVIN, DONNA J. ; JOVIN, THOMAS M. . Dynamics of Membrane Receptors: Single-molecule Tracking of Quantum Dot Liganded Epidermal Growth Factor. Single Molecule Dynamics in Life Science. 1ed.: Wiley-VCH Verlag GmbH & Co. KGaA, 2009, v. , p. 117-130.

Trabalhos completos publicados em anais de congressos
1.
ALVAREZ, S. A. ; CAARLS, W. ; LIMA, P. M. V. . Weightless Neural Network for High Frequency Trading. In: International Joint Conference on Neural Networks, 2018, Rio de Janeiro. Proc. IJCNN 2018, 2018.

2.
KORYAKOVSKIY, I. ; VALLERY, H. ; BABU?KA, ROBERT ; CAARLS, W. . Evaluation of Physical Damage Associated with Action Selection Strategies in Reinforcement Learning. In: 20th IFAC World Congress, 2017, Toulouse. Proc. 20th IFAC World Congress, 2017.

3.
CAARLS, WOUTER; Eduardo Hargreaves ; MENASCHE, D. S. . Q-caching: an integrated reinforcement-learning approach for caching and routing in information-centric networks. In: XXXIV Simpósio Brasileiro de Redes de Computadores e Sistemas Distribuídos, 2016, Salvador, Bahia, Brazil. Anais do SBRC 2016. Porto Alegre: Sociedade Brasileira de Computação, 2016. p. 366-379.

4.
Kimberly McGuire ; Masato Tsukada ; Boris Lenseigne ; Wouter Caarls ; Masato Toda ; Pieter Jonker . A Novel Method for Simultaneous Acquisition of Visible and Near-Infrared Light Using a Coded Infrared-Cut Filter. In: Computer Analysis of Images and Patterns, 2015, Valletta. 16th International Conference, CAIP 2015, Valletta, Malta, September 2-4, 2015 Proceedings, Part I, 2015. v. 9256. p. 174-185.

5.
Bruno Costa ; Wouter Caarls ; Daniel Sadoc Menasche . Dyna-MLAC: Trading Computational and Sample Complexities in Actor-Critic Reinforcement Learning. In: Brazilian Conference on Intelligent Systems, 2015, Natal. Proc. Brazilian Conference on Intelligent Systems, 2015.

6.
BHARATHEESHA, MUKUNDA ; Caarls, Wouter ; WOLFSLAG, WOUTER JAN ; WISSE, MARTIJN . Distance metric approximation for state-space RRTs using supervised learning. In: 2014 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2014), 2014, Chicago. 2014 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2014. p. 252-257.

7.
PEN, JURREN ; Caarls, Wouter ; WISSE, MARTIJN ; BABUSKA, ROBERT . Evolutionary co-optimization of control and system parameters for a resonating robot arm. In: 2013 IEEE International Conference on Robotics and Automation (ICRA), 2013, Karlsruhe. 2013 IEEE International Conference on Robotics and Automation. p. 4195.

8.
MEIJDAM, H. J. ; PLOOIJ, M. C. ; CAARLS, W. . Learning while preventing mechanical failure due to random motions. In: 2013 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2013), 2013, Tokyo. 2013 IEEE/RSJ International Conference on Intelligent Robots and Systems. p. 182.

9.
CALLI, BERK ; Caarls, Wouter ; JONKER, PIETER ; WISSE, MARTIJN . Comparison of extremum seeking control algorithms for robotic applications. In: 2012 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2012), 2012, Vilamoura-Algarve. 2012 IEEE/RSJ International Conference on Intelligent Robots and Systems. p. 3195.

10.
VAN VLIET, B. ; CAARLS, W. ; SCHUITEMA, E. ; JONKER, P.P. . Accelerating reinforcement learning on a robot by using subgoals in a hierarchical framework. In: Benelux Conference on Artificial Intelligence, 2011, Ghent. Proc. 23rd Benelux Conference on Artificial Intelligence, 2011.

11.
SCHUITEMA, E. ; CAARLS, W. ; WISSE, M. ; JONKER, P.P. ; BABUSKA, R. . The Effects of Large Disturbances on On-Line Reinforcement Learning for a Walking Robot. In: Benelux Conference on Artificial Intelligence, 2010, Luxembourg. Proc. 22nd Benelux Conference on Artificial Intelligence, 2010.

12.
CAARLS, W.; JONKER, P.P. ; CORPORAAL, H. . Algorithmic skeletons for stream programming in embedded heterogeneous parallel image processing applications. In: , 2006, Rhodes Island. . p. 9 pp..

13.
CAARLS, W.; JONKER, P.P. ; CORPORAAL, H. . Skeletons and Asynchronous RPC for Embedded Data- and Task Parallel Image Processing. In: IAPR Conference on Machine Vision Applications, 2005, Tsukuba Science City. Proc. 9th IAPR Conference on Machine Vision Applications, 2005. p. 384-387.

14.
BROERS, H. ; CAARLS, W. ; JONKER, P.P. ; KLEIHORST, R.P. . Architecture Study for Smart Cameras. In: EOS Conference on Industrial Imaging and Machine Vision, 2005, Munich. Proc. EOS Conference on Industrial Imaging and Machine Vision, 2005. p. 39-49.

15.
MANTZ, F. ; JONKER, P.P. ; CAARLS, W. . Behavior-Based Vision on a 4 Legged Soccer Robot. In: Robocup conference, 2005, Osaka. Lecture Notes in Computer Science, 2005. v. 4020. p. 480-487.

16.
JONKER, P.P. ; CAARLS, W. . Application Driven Design of Embedded Real-Time Image Processors. In: Advanced Concepts for Intelligent Vision Systems, 2003, Ghent. Proc. Advanced Concepts for Intelligent Vision Systems, 2003. p. 1-8.

17.
CAARLS, W.; JONKER, P.P. . Benchmarks for SmartCam Development. In: Advanced Concepts for Intelligent Vision Systems, 2003, Ghent. Proc. Advanced Concepts for Intelligent Vision Systems 2003, 2003. p. 81-86.

Resumos expandidos publicados em anais de congressos
1.
HAGEN, GUY M. ; CAARLS, W. ; THOMAS, M. ; HILL, A. ; LIDKE, K.A. ; Rieger, Bernd ; FRITSCH, CORNELIA ; VAN GEEST, B. ; JOVIN, THOMAS M. ; ARNDT-JOVIN, DONNA J. . Biological applications of an LCoS-based PROGRAMMABLE ARRAY MICROSCOPE (PAM). In: Photonic West 2007, BiOS, 2007, San Jose, CA. Proc. SPIE, 2007. v. 6441.

2.
CAARLS, W.; JONKER, P.P. ; CORPORAAL, H. . Data- and Task Parallel Image Processing on a Mixed SIMD-ILP Platform using Skeletons and Asynchronous RPC. In: PROGRESS Workshop on Embedded Systems, 2004, Nieuwegein. Proc. 5th PROGRESS Workshop on Embedded Systems, 2004.

3.
CAARLS, W.; JONKER, P.P. ; CORPORAAL, H. . SmartCam Design Framework. In: PROGRESS Workshop on Embedded Systems, 2003, Nieuwegein. Proc. 4th PROGRESS Workshop on Embedded Systems, 2003.

4.
CAARLS, W.; JONKER, P.P. ; CORPORAAL, H. . SmartCam: Devices for Embedded Intelligent Cameras. In: PROGRESS Workshop on Embedded Systems, 2002, Utrecht. Proc. 3rd PROGRESS Workshop on Embedded Systems, 2002.

Resumos publicados em anais de congressos
1.
CALLI, B. ; CAARLS, W. ; LEI, Q. ; WISSE, M. ; JONKER, P.P. . SMAG: Simultaneous Modeling and Grasping. In: RSS 2013 Workshop: Manipulation with Uncertain Models, 2013, Berlin. RSS 2013 Workshop: Manipulation with Uncertain Models, 2013.

2.
DE BEULE, P.A.A. ; DE VRIES, ANTHONY H. B. ; CAARLS, W. ; ARNDT-JOVIN, DONNA J. ; JOVIN, THOMAS M. . A Generation-3 Programmable Array Microscope with Digital Micro-Mirror Device. In: 54th Annual Meeting of the Biophysical Society, 2010, San Fransisco, CA, USA. Biophysical Journal, 2010. v. 98. p. 178a-178a.

3.
HAGEN, GUY M. ; CAARLS, W. ; LIDKE, K.A. ; DE VRIES, ANTHONY H.B. ; FRITSCH, CORNELIA ; BARISAS, B. GEORGE ; ARNDT-JOVIN, DONNA J. ; JOVIN, THOMAS M. . FRAP and Photoconversion in Multiple Arbitrary Regions of Interest Using a Programmable Array Microscope (PAM). In: 58th Annual Meeting of the Biophysical Society, 2009, San Fransisco, CA, USA. Biophysical Journal, 2009. v. 96. p. 281a-281a.

4.
CAARLS, W.; DE VRIES, ANTHONY H. B. ; ARNDT-JOVIN, DONNA J. ; JOVIN, THOMAS M. . Arbitrary and Dynamic Patterning in a Programmable Array Microscope. In: Focus on Microscopy 2009, 2009, Krakow. Proc. Focus on Microscopy 2009, 2009. p. 137-137.

5.
CAARLS, W.; CELEJ, M. SOLEDAD ; DEMCHENKO, ALEXANDER P. ; JOVIN, THOMAS M. . Multiwavelength ratiometric fluorescence sensing. In: Methods and Applications of Fluorescence 2009, 2009, Budapest. Proc. Methods and Applications of Fluorescence 2009, 2009. p. 184-184.

6.
JOVIN, THOMAS M. ; HAGEN, GUY M. ; CAARLS, W. ; ARNDT-JOVIN, DONNA J. . Live cell microscopy of growth-factor dependent signal transduction pathways with a Programmable Array Microscope (PAM). In: 17th Annual Meeting of the German Society of Cytometry (DGfZ), 2007, Regensburg. Cytometry Part A, 2007. v. 71A. p. 745-746.

7.
ARNDT-JOVIN, DONNA J. ; HAGEN, GUY M. ; CAARLS, W. ; HILL, A. ; JOVIN, THOMAS M. . Biological applications of an LCoS-based programmable array microscope (PAM). In: 17th Annual Meeting of the German Society of Cytometry (DGfZ), 2007, Regensburg. Cytometry Part A, 2007. v. 71A. p. 512-512.

Artigos aceitos para publicação
1.
CALLI, B. ; Caarls, W. ; WISSE, M. ; JONKER, P. . Viewpoint optimization for aiding grasp synthesis algorithms using reinforcement learning. Advanced Robotics, 2018.

Apresentações de Trabalho
1.
CAARLS, W.. Parallel DYNA. 2013. (Apresentação de Trabalho/Simpósio).

2.
CAARLS, W.. Parallel Real-Time Reinforcement Learning. 2011. (Apresentação de Trabalho/Simpósio).

3.
CAARLS, W.. GPU Programming Paradigms. 2010. (Apresentação de Trabalho/Simpósio).


Produção técnica
Programas de computador sem registro
1.
CAARLS, WOUTER; KORYAKOVSKIY, I. ; Manuel Kudruss . Generic Reinforcement Learning Library. 2015.



Patentes e registros



Patente

A Confirmação do status de um pedido de patentes poderá ser solicitada à Diretoria de Patentes (DIRPA) por meio de uma Certidão de atos relativos aos processos
1.
 JOVIN, THOMAS M. ; CAARLS, WOUTER ; DE VRIES, ANTHONY H.B. . Optical modulator device and spatio-temporally light modulated imaging system. 2011, Estados Unidos.
Patente: Privilégio de Inovação. Número do registro: US9279971B2, título: "Optical modulator device and spatio-temporally light modulated imaging system" , Instituição de registro: United States Patent and Trademark Office. Depósito: 18/03/2011; Concessão: 08/03/2016.



Orientações



Orientações e supervisões em andamento
Dissertação de mestrado
1.
Nicolai Rutkevich. Intelligent Control of a Drone-Based Virtual Robotic Arm. Início: 2018. Dissertação (Mestrado em Engenharia Elétrica) - Pontifícia Universidade Católica do Rio de Janeiro. (Coorientador).

2.
Joao Marcelo Guimaraes Soares. Aprendizado por Reforço Visual no Mundo Real. Início: 2018. Dissertação (Mestrado em Engenharia Elétrica) - Pontifícia Universidade Católica do Rio de Janeiro. (Orientador).

3.
Franklin Cardeñoso Fernández. Otimização de Hiperparâmetros para Aprendizado por Reforço. Início: 2018. Dissertação (Mestrado em Engenharia Elétrica) - Pontifícia Universidade Católica do Rio de Janeiro. (Orientador).

4.
Evelyn Batista. Aprendizado por Reforço Profundo Visual. Início: 2017. Dissertação (Mestrado em Engenharia Elétrica) - Pontifícia Universidade Católica do Rio de Janeiro. (Orientador).

5.
Roberto Bandeira de Mello. Aprendizado por Reforço Profundo para Sistemas Multiagentes. Início: 2017. Dissertação (Mestrado em Engenharia Elétrica) - Pontifícia Universidade Católica do Rio de Janeiro. (Coorientador).

6.
Guilherme Wilson Ribeiro. Aprendizado por Reforço para Sistemas Multiagentes. Início: 2017. Dissertação (Mestrado em Engenharia Elétrica) - Pontifícia Universidade Católica do Rio de Janeiro. (Orientador).

7.
Pedro Chataignier. Óculos de Direcionamento de Cegos. Início: 2017. Dissertação (Mestrado em Engenharia Elétrica) - Pontifícia Universidade Católica do Rio de Janeiro. (Orientador).

8.
Gabriel Lins Tenório. Classificação de Imagens Hiperespetrais. Início: 2017. Dissertação (Mestrado em Engenharia Elétrica) - Pontifícia Universidade Católica do Rio de Janeiro. (Orientador).

Tese de doutorado
1.
Renata Oliveira. Aprendizado por Reforço Profundo Hierárquico. Início: 2017. Tese (Doutorado em Engenharia Elétrica) - Pontifícia Universidade Católica do Rio de Janeiro. (Orientador).

2.
Ivan Koryakovskiy. Safer Reinforcement Learning for Robotics. Início: 2014. Tese (Doutorado em Mechanical, Maritime and Materials Engineering) - Delft University of Technology. (Coorientador).


Orientações e supervisões concluídas
Dissertação de mestrado
1.
Samara Alvarez Alves. Negociação no mercado financeiro utilizando a rede neural sem peso WiSARD. 2017. Dissertação (Mestrado em Programa de Pós-Graduação em Informática) - Universidade Federal do Rio de Janeiro, . Coorientador: Wouter Caarls.

2.
Bruno Pereira Palma. PRM-EB UM NOVO ALGORITMO PARA A OTIMIZAÇÃO DE PRM BASEADO NA TEORIA DE APOSTAS. 2016. Dissertação (Mestrado em Programa de Pós-Graduação em Informática) - Universidade Federal do Rio de Janeiro, . Coorientador: Wouter Caarls.

3.
Jorn Postma. Speeding Up Reinforcement Learning with Graphics Processing Units. 2015. Dissertação (Mestrado em Biomechanical Design) - Delft University of Technology, . Orientador: Wouter Caarls.

4.
Bruno Sousa Campos da Costa. Trading Between Sampling and Computation in Reinforcement Learning. 2015. Dissertação (Mestrado em Informática) - Universidade Federal do Rio de Janeiro, . Coorientador: Wouter Caarls.

5.
Hendrik Meijdam. Learning while preventing mechanical failure due to random motions. 2013. Dissertação (Mestrado em Biomechanical Design) - Delft University of Technology, . Orientador: Wouter Caarls.

6.
Bas Vennemann. Sample-Efficient Reinforcement Learning for Walking Robots. 2013. Dissertação (Mestrado em Biomechanical Design) - Delft University of Technology, . Orientador: Wouter Caarls.

7.
Martijn Zeestraten. Robot-learning using a Tree-based Policy Representation. 2013. Dissertação (Mestrado em Biomechanical Design) - Delft University of Technology, . Coorientador: Wouter Caarls.

8.
Mart Moerdijk. Learning to walk using minimum prior knowledge: And a small hexapod robot. 2013. Dissertação (Mestrado em Biomechanical Design) - Delft University of Technology, . Orientador: Wouter Caarls.

9.
Jurren Pen. Evolutionary Co-Optimisation of Control and System Parameters for a Resonating Robot Arm. 2012. Dissertação (Mestrado em Systems and Control) - Delft University of Technology, . Coorientador: Wouter Caarls.

10.
Bart van Vliet. Accelerating reinforcement learning on a robot by using subgoals in a hierarchical framework. 2011. Dissertação (Mestrado em Biomechanical Design) - Delft University of Technology, . Coorientador: Wouter Caarls.

11.
Merel van Diepen. Avoiding failure states during reinforcement learning. 2011. Dissertação (Mestrado em Biomechanical Design) - Delft University of Technology, . Coorientador: Wouter Caarls.

12.
Jan van der Horst. Development and implementation of a real-time stereo camera. 2006. Dissertação (Mestrado em Applied Physics) - Delft University of Technology, . Coorientador: Wouter Caarls.

13.
Floris Mantz. A Robust Behaviour-Based Hierarchical Vision System with Local Colour Tables and Use of Behaviour and Location Information. 2005. Dissertação (Mestrado em Applied Physics) - Delft University of Technology, . Coorientador: Wouter Caarls.



Inovação



Patente
1.
 JOVIN, THOMAS M. ; CAARLS, WOUTER ; DE VRIES, ANTHONY H.B. . Optical modulator device and spatio-temporally light modulated imaging system. 2011, Estados Unidos.
Patente: Privilégio de Inovação. Número do registro: US9279971B2, título: "Optical modulator device and spatio-temporally light modulated imaging system" , Instituição de registro: United States Patent and Trademark Office. Depósito: 18/03/2011; Concessão: 08/03/2016.


Programa de computador sem registro
1.
CAARLS, WOUTER; KORYAKOVSKIY, I. ; Manuel Kudruss . Generic Reinforcement Learning Library. 2015.




Página gerada pelo Sistema Currículo Lattes em 19/10/2018 às 20:02:43