Manu Blanco Valentin

Manu Blanco Valentin

he/him

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Publications

You can also find my articles on my Google Scholar profile.

A deep residual convolutional neural network for automatic lithological facies identification in Brazilian pre-salt oilfield wellbore image logs

Published in Journal of Petroleum Science and Engineering, 2019

A deep residual convolutional neural network for automatic lithological facies identification in Brazilian pre-salt oilfield wellbore image logs.

Recommended citation: Manuel Blanco Valentín, Clécio R Bom, Juliana M Coelho, Maury Duarte Correia, Márcio P De Albuquerque, Marcelo P de Albuquerque, Elisângela L Faria (2019). "A deep residual convolutional neural network for automatic lithological facies identification in Brazilian pre-salt oilfield wellbore image logs." Journal of Petroleum Science and Engineering. 179, 474–503.
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Estimation of permeability and effective porosity logs using deep autoencoders in borehole image logs from the Brazilian pre-salt carbonate

Published in Journal of Petroleum Science and Engineering, 2018

Estimation of permeability and effective porosity logs using deep autoencoders in borehole image logs from the Brazilian pre-salt carbonate.

Recommended citation: Manuel Blanco Valentin, Clecio R Bom, André Luiz Martins Compan, Maury Duarte Correia, Candida Menezes de Jesus, Anelise de Lima Souza, Marcio P de Albuquerque, Marcelo P de Albuquerque, Elisangela L Faria (2018). "Estimation of permeability and effective porosity logs using deep autoencoders in borehole image logs from the Brazilian pre-salt carbonate." Journal of Petroleum Science and Engineering. 170, 315–330.
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Bayesian deep networks for absolute permeability and porosity uncertainty prediction from image borehole logs from Brazilian carbonate reservoirs

Published in Journal of Petroleum Science and Engineering, 2021

Bayesian deep networks for absolute permeability and porosity uncertainty prediction from image borehole logs from Brazilian carbonate reservoirs.

Recommended citation: Clecio R Bom, Manuel Blanco Valentin, Bernardo MO Fraga, Jorge Campos, Bernardo Coutinho, Luciana O Dias, Elisangela L Faria, Marcio P de Albuquerque, Marcelo P de Albuquerque, Maury Duarte Correia (2021). "Bayesian deep networks for absolute permeability and porosity uncertainty prediction from image borehole logs from Brazilian carbonate reservoirs." Journal of Petroleum Science and Engineering. 201, 108361.
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In-pixel AI for lossy data compression at source for X-ray detectors

Published in Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment, 2023

In-pixel AI for lossy data compression at source for X-ray detectors.

Recommended citation: Manuel B Valentin, Giuseppe Di Guglielmo, Danny Noonan, Priyanka Dilip, Panpan Huang, Adam Quinn, Thomas Zimmerman, Davide Braga, Seda Ogrenci, Chris Jacobsen, others (2023). "In-pixel AI for lossy data compression at source for X-ray detectors." Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment. 1057, 168665.
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On a method for Rock Classification using Textural Features and Genetic Optimization

Published in arXiv e-prints, 2016

On a method for Rock Classification using Textural Features and Genetic Optimization.

Recommended citation: Manuel Blanco Valentin, Clecio Roque De Bom, Marcio Portes de Albuquerque, Marcelo Portes de Albuquerque, Elisangela Faria, Maury Duarte Correia, Rodrigo Surmas (2016). "On a method for Rock Classification using Textural Features and Genetic Optimization." arXiv e-prints. arXiv–1607.
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A cryogenic readout ic with 100 ksps in-pixel adc for skipper ccd-in-cmos sensors

Published in 2023 IEEE International Symposium on Circuits and Systems (ISCAS), 2023

A cryogenic readout ic with 100 ksps in-pixel adc for skipper ccd-in-cmos sensors.

Recommended citation: Adam Quinn, Manuel B Valentin, Thomas Zimmerman, Davide Braga, Seda Memik, Farah Fahim (2023). "A cryogenic readout ic with 100 ksps in-pixel adc for skipper ccd-in-cmos sensors." 2023 IEEE International Symposium on Circuits and Systems (ISCAS). 1–5.
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Aquisição de imagens ultrassônicas como experimento didático

Published in Revista Brasileira de Ensino de Física, 2018

O estudo das ondas sonoras com suas diversas aplicações é um tema presente na formação do estudante de ensino médio e superior que pode ser utilizado para demonstrar conceitos de física ondulatória de forma bastante didática. Neste trabalho discutimos um experimento visando uma…

Recommended citation: Manuel Blanco Valentín, Clécio R de Bom, Márcio P de Albuquerque, Marcelo P de Albuquerque, Elisângela L Faria, Maury D Correia (2018). "Aquisição de imagens ultrassônicas como experimento didático." Revista Brasileira de Ensino de Física. 40(2), e2503.
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Texture classification based on spectral analysis and haralick features

Published in Notas Técnicas, 2016

Texture classification based on spectral analysis and haralick features.

Recommended citation: Manuel Blanco Valentin, Clécio Roque de Bom, Márcio P de Albuquerque, Marcelo P de Albuquerque, Elisângela L Faria, Maury D Correia (2016). "Texture classification based on spectral analysis and haralick features." Notas Técnicas. 6(1).
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Rock Texture Classification Using Spectral Analysis And Genetically Optimized Texture Features

Published in Computer Vision and Pattern Recognition (CVPR), 2016

Rock Texture Classification Using Spectral Analysis And Genetically Optimized Texture Features.

Recommended citation: Manuel Blanco Valentin, Clecio Roque De Bom, Marcio Portes de Albuquerque, Marcelo Portes de Albuquerque, Elisangela Faria, Maury Duarte Correia, Rodrigo Surmas (2016). "Rock Texture Classification Using Spectral Analysis And Genetically Optimized Texture Features." Computer Vision and Pattern Recognition (CVPR).
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Toward Reconfigurable In-Pixel Computing: A Fault-Tolerant Design Flow for Machine Learning Accelerators

Published in 2025 IEEE 33rd Annual International Symposium on Field-Programmable Custom Computing Machines (FCCM), 2025

Toward Reconfigurable In-Pixel Computing: A Fault-Tolerant Design Flow for Machine Learning Accelerators.

Recommended citation: Houxuan Guo, Manuel Blanco Valentín, Xiuyuan He, Seda Ogrenci (2025). "Toward Reconfigurable In-Pixel Computing: A Fault-Tolerant Design Flow for Machine Learning Accelerators." 2025 IEEE 33rd Annual International Symposium on Field-Programmable Custom Computing Machines (FCCM). 261–267.
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A Cryogenic Readout IC with 100 KSPS in-Pixel ADC for Skipper CCD-in-CMOS Sensors [Poster]

Published in Fermi National Accelerator Laboratory (FNAL), Batavia, IL (United States), 2021

A Cryogenic Readout IC with 100 KSPS in-Pixel ADC for Skipper CCD-in-CMOS Sensors [Poster].

Recommended citation: A Quinn, MB Valentin, T Zimmerman, D Braga, S Li, S Memik, F Fahim (2021). "A Cryogenic Readout IC with 100 KSPS in-Pixel ADC for Skipper CCD-in-CMOS Sensors [Poster]." Fermi National Accelerator Laboratory (FNAL), Batavia, IL (United States).
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Porous medium permeability estimation for well imagery and characterization using complex resistivity spectra

Published in NOTAS TÉCNICAS, 2018

Porous medium permeability estimation for well imagery and characterization using complex resistivity spectra.

Recommended citation: Manuel Blanco Valentin, Márcio Portes de Albuquerque, Marcelo Portes de Albuquerque, Elisângela L Farias, Clécio Roque De Bom, Maury Duarte Correia, Yann Le Guével (2018). "Porous medium permeability estimation for well imagery and characterization using complex resistivity spectra." NOTAS TÉCNICAS. 8(1).
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Desarrollo del sistema electrónico de control de navegación de un barco remolcador a escala

Published in Universitat Politècnica de Catalunya. Escola Universitària d'Enginyeria …, 2014

Desarrollo del sistema electrónico de control de navegación de un barco remolcador a escala.

Recommended citation: Manuel Blanco Valentín (2014). "Desarrollo del sistema electrónico de control de navegación de un barco remolcador a escala." Universitat Politècnica de Catalunya. Escola Universitària d'Enginyeria ….
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hls4ml: An open-source codesign workflow to empower scientific low-power machine learning devices

Published in arXiv preprint arXiv:2103.05579, 2021

Accessible machine learning algorithms, software, and diagnostic tools for energy-efficient devices and systems are extremely valuable across a broad range of application domains. In scientific domains, real-time near-sensor processing can drastically improve experimental design…

Recommended citation: Farah Fahim, Benjamin Hawks, Christian Herwig, James Hirschauer, Sergo Jindariani, Nhan Tran, Luca P Carloni, Giuseppe Di Guglielmo, Philip Harris, Jeffrey Krupa, others (2021). "hls4ml: An open-source codesign workflow to empower scientific low-power machine learning devices." arXiv preprint arXiv:2103.05579.
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The strong gravitational lens finding challenge

Published in Astronomy & Astrophysics, 2019

Large-scale imaging surveys will increase the number of galaxy-scale strong lensing candidates by maybe three orders of magnitudes beyond the number known today. Finding these rare objects will require picking them out of at least tens of millions of images, and deriving scienti…

Recommended citation: R Benton Metcalf, M Meneghetti, Camille Avestruz, Fabio Bellagamba, Clécio R Bom, Emmanuel Bertin, Rémi Cabanac, F Courbin, Andrew Davies, Etienne Decencière, others (2019). "The strong gravitational lens finding challenge." Astronomy & Astrophysics. 625, A119.
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Automatic detection of fractures and breakouts patterns in acoustic borehole image logs using fast-region convolutional neural networks

Published in Journal of Petroleum Science and Engineering, 2020

Automatic detection of fractures and breakouts patterns in acoustic borehole image logs using fast-region convolutional neural networks.

Recommended citation: Luciana Olivia Dias, Clécio R Bom, Elisangela L Faria, Manuel Blanco Valentín, Maury Duarte Correia, Márcio P De Albuquerque, Marcelo P De Albuquerque, Juliana M Coelho (2020). "Automatic detection of fractures and breakouts patterns in acoustic borehole image logs using fast-region convolutional neural networks." Journal of Petroleum Science and Engineering. 191, 107099.
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A reconfigurable neural network ASIC for detector front-end data compression at the HL-LHC

Published in IEEE Transactions on Nuclear Science, 2021

A reconfigurable neural network ASIC for detector front-end data compression at the HL-LHC.

Recommended citation: Giuseppe Di Guglielmo, Farah Fahim, Christian Herwig, Manuel Blanco Valentin, Javier Duarte, Cristian Gingu, Philip Harris, James Hirschauer, Martin Kwok, Vladimir Loncar, others (2021). "A reconfigurable neural network ASIC for detector front-end data compression at the HL-LHC." IEEE Transactions on Nuclear Science. 68(8), 2179–2186.
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Smart pixel sensors: towards on-sensor filtering of pixel clusters with deep learning

Published in Machine Learning: Science and Technology, 2024

Smart pixel sensors: towards on-sensor filtering of pixel clusters with deep learning.

Recommended citation: Jieun Yoo, Jennet Dickinson, Morris Swartz, Giuseppe Di Guglielmo, Alice Bean, Douglas Berry, Manuel Blanco Valentin, Karri DiPetrillo, Farah Fahim, Lindsey Gray, others (2024). "Smart pixel sensors: towards on-sensor filtering of pixel clusters with deep learning." Machine Learning: Science and Technology. 5(3), 035047.
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John Mamish

Published in Seda Orgrenci-Memik, Thea Aarrestad, Hamza Javed, Vladimir Loncar, Maurizio Pierini, Adrian Alan Pol, Sioni Summers, Javier Duarte, Scott Hauck, Shih-Chieh Hsu, Jennifer Ngadiuba, Mia Liu, Duc Hoang, Edward Kreinar, and Zhenbin Wu, 2021

John Mamish.

Recommended citation: Farah Fahim, Benjamin Hawks, Christian Herwig, James Hirschauer, Sergo Jindariani, Nhan Tran, Luca P Carloni, Giuseppe Di Guglielmo, Philip Harris, Jeffrey Krupa, others (2021). "John Mamish." Seda Orgrenci-Memik, Thea Aarrestad, Hamza Javed, Vladimir Loncar, Maurizio Pierini, Adrian Alan Pol, Sioni Summers, Javier Duarte, Scott Hauck, Shih-Chieh Hsu, Jennifer Ngadiuba, Mia Liu, Duc Hoang, Edward Kreinar, and Zhenbin Wu.
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Developing a victorious strategy to the second strong gravitational lensing data challenge

Published in Monthly Notices of the Royal Astronomical Society, 2022

ABSTRACT Strong lensing is a powerful probe of the matter distribution in galaxies and clusters and a relevant tool for cosmography. Analyses of strong gravitational lenses with deep learning have become a popular approach due to these astronomical objects’ rarity…

Recommended citation: CR Bom, Bernardo Machado de Oliveira Fraga, Luciana Olivia Dias, Patrick Schubert, M Blanco Valentin, Cristina Furlanetto, Martín Makler, K Teles, M Portes de Albuquerque, R Benton Metcalf (2022). "Developing a victorious strategy to the second strong gravitational lensing data challenge." Monthly Notices of the Royal Astronomical Society. 515(4), 5121–5134.
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Deep learning in wide-field surveys: Fast analysis of strong lenses in ground-based cosmic experiments

Published in arXiv preprint arXiv:1911.06341, 2019

Searches and analyses of strong gravitational lenses are challenging due to the rarity and image complexity of these astronomical objects. Next-generation surveys (both ground- and space-based) will provide more opportunities to derive science from these objects, but only if the…

Recommended citation: Clecio Bom, Jason Poh, Brian Nord, Manuel Blanco-Valentin, Luciana Dias (2019). "Deep learning in wide-field surveys: Fast analysis of strong lenses in ground-based cosmic experiments." arXiv preprint arXiv:1911.06341.
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hls4ml: A flexible, open-source platform for deep learning acceleration on reconfigurable hardware

Published in ACM Transactions on Reconfigurable Technology and Systems, 2025

We present hls4ml , a free and open-source platform that translates machine learning (ML) models from modern deep learning frameworks into high-level synthesis (HLS) code that can be integrated into full designs for field-programmable gate…

Recommended citation: Jan-Frederik Schulte, Benjamin Ramhorst, Chang Sun, Jovan Mitrevski, Nicolò Ghielmetti, Enrico Lupi, Dimitrios Danopoulos, Vladimir Loncar, Javier Duarte, David Burnette, others (2025). "hls4ml: A flexible, open-source platform for deep learning acceleration on reconfigurable hardware." ACM Transactions on Reconfigurable Technology and Systems.
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hls4ml: An open-source codesign workflow to empower scientific low-power machine learning devices. arXiv

Published in arXiv preprint arXiv:2103.05579, 2021

Accessible machine learning algorithms, software, and diagnostic tools for energy-efficient devices and systems are extremely valuable across a broad range of application domains. In scientific domains, real-time near-sensor processing can drastically improve experimental design…

Recommended citation: F Fahim, B Hawks, C Herwig, J Hirschauer, S Jindariani, N Tran, LP Carloni, G Di Guglielmo, P Harris, J Krupa, others (2021). "hls4ml: An open-source codesign workflow to empower scientific low-power machine learning devices. arXiv." arXiv preprint arXiv:2103.05579.
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Smart Pixels: In-pixel AI for on-sensor data filtering

Published in 2024 IEEE Nuclear Science Symposium (NSS), Medical Imaging Conference (MIC) and Room Temperature Semiconductor Detector Conference (RTSD), 2024

Smart Pixels: In-pixel AI for on-sensor data filtering.

Recommended citation: Benjamin Parpillon, Chinar Syal, Jieun Yoo, M Swartz, G Di Guglielmo, A Bean, D Berry, M Blanco Valentin, K DiPetrillo, A Badea, others (2024). "Smart Pixels: In-pixel AI for on-sensor data filtering." 2024 IEEE Nuclear Science Symposium (NSS), Medical Imaging Conference (MIC) and Room Temperature Semiconductor Detector Conference (RTSD). 1–2.
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Smartpixels: Towards on-sensor inference of charged particle track parameters and uncertainties

Published in arXiv preprint arXiv:2312.11676, 2023

The combinatorics of track seeding has long been a computational bottleneck for triggering and offline computing in High Energy Physics (HEP), and remains so for the HL-LHC. Next-generation pixel sensors will be sufficiently fine-grained to determine angular information of the c…

Recommended citation: Jennet Dickinson, Rachel Kovach-Fuentes, Lindsey Gray, Morris Swartz, Giuseppe Di Guglielmo, Alice Bean, Doug Berry, Manuel Blanco Valentin, Karri DiPetrillo, Farah Fahim, others (2023). "Smartpixels: Towards on-sensor inference of charged particle track parameters and uncertainties." arXiv preprint arXiv:2312.11676.
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Ultrasound image acquisition as a didactic tool

Published in Revista Brasileira de Ensino de Física, 2018

Ultrasound image acquisition as a didactic tool.

Recommended citation: M Valentín, C de Bom, M de Albuquerque, ECorreia M Faria (2018). "Ultrasound image acquisition as a didactic tool." Revista Brasileira de Ensino de Física. 40(2).
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arXiv: hls4ml: A Flexible, Open-Source Platform for Deep Learning Acceleration on Reconfigurable Hardware

Published in Unpublished, 2025

arXiv: hls4ml: A Flexible, Open-Source Platform for Deep Learning Acceleration on Reconfigurable Hardware.

Recommended citation: Jan-Frederik Schulte, Ho Fung Tsoi, Noah Paladino, Abhijith Gandrakota, Sioni Summers, Daniel Diaz, Javier Campos, Enrico Lupi, Philip Harris, Christian Herwig, others (2025). "arXiv: hls4ml: A Flexible, Open-Source Platform for Deep Learning Acceleration on Reconfigurable Hardware."
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Sensor Co-design for smartpixels

Published in arXiv preprint arXiv:2510.06588, 2025

Pixel tracking detectors at upcoming collider experiments will see unprecedented charged-particle densities. Real-time data reduction on the detector will enable higher granularity and faster readout, possibly enabling the use of the pixel detector in the first level of the trig…

Recommended citation: Danush Shekar, Ben Weiss, Morris Swartz, Corrinne Mills, Jennet Dickinson, Lindsey Gray, David Jiang, Mohammad Abrar Wadud, Daniel Abadjiev, Anthony Badea, others (2025). "Sensor Co-design for smartpixels." arXiv preprint arXiv:2510.06588.
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Radiation-Hard Smart-Pixel Detector ASIC ReadOut with Digital AI in 28nm

Published in Fermi National Accelerator Laboratory (FNAL), Batavia, IL (United States), 2024

Radiation-Hard Smart-Pixel Detector ASIC ReadOut with Digital AI in 28nm.

Recommended citation: Benjamin Parpillon, Anthony Badea, Chinar Syal, Corrinne Mills, Douglas Berry, Farah Fahim, Giuseppe Di Guglielmo, Jennet Dickinson, Jieun Yoo, Jim Hirschauer, others (2024). "Radiation-Hard Smart-Pixel Detector ASIC ReadOut with Digital AI in 28nm." Fermi National Accelerator Laboratory (FNAL), Batavia, IL (United States).
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Smart Pixels: Algorithm design and hardware testing for a 28m ROIC for future pixel trackers

Published in APS April Meeting Abstracts, 2024

Smart Pixels: Algorithm design and hardware testing for a 28m ROIC for future pixel trackers.

Recommended citation: Carissa Kumar, Emily Pan, Karri Dipetrillo, Anthony Badea, Jennet Dickinson, Jieun Yoo, Morris Swartz, Giuseppe Di Guglielmo, Alice Bean, Douglas Berry, others (2024). "Smart Pixels: Algorithm design and hardware testing for a 28m ROIC for future pixel trackers." APS April Meeting Abstracts. 2024, F14–005.
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Neural network accelerator for universal quantum control

Published in APS March Meeting Abstracts, 2023

Neural network accelerator for universal quantum control.

Recommended citation: A Baris Ozguler, Giuseppe Di Guglielmo, Manuel Blanco Valentín, David Xu, Nhan Tran, Gabriel Perdue, Luca Carloni, Farah Fahim (2023). "Neural network accelerator for universal quantum control." APS March Meeting Abstracts. 2023, F71–006.
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arXiv: hls4ml: An Open-Source Codesign Workflow to Empower Scientific Low-Power Machine Learning Devices

Published in Unpublished, 2021

arXiv: hls4ml: An Open-Source Codesign Workflow to Empower Scientific Low-Power Machine Learning Devices.

Recommended citation: Farah Fahim, James Hirschauer, Yingyi Luo, Christian Herwig, Sioni Summers, Philip Harris, Jeffrey Krupa, Duc Hoang, Edward Kreinar, Maurizio Pierini, others (2021). "arXiv: hls4ml: An Open-Source Codesign Workflow to Empower Scientific Low-Power Machine Learning Devices."
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Search for an Exotic S=-2, Q=-2 Baryon Resonance in Proton-Proton Interactions at sqrt s_ NN = 17.3 GeV

Published in Fermi National Accelerator Laboratory (FNAL), Batavia, IL (United States), 2019

Search for an Exotic S=-2, Q=-2 Baryon Resonance in Proton-Proton Interactions at sqrt s_ NN = 17.3 GeV.

Recommended citation: CR Bom, J Poh, B Nord, M Blanco-Valentin, LO Dias (2019). "Search for an Exotic S=-2, Q=-2 Baryon Resonance in Proton-Proton Interactions at sqrt s_ NN = 17.3 GeV." Fermi National Accelerator Laboratory (FNAL), Batavia, IL (United States).
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Notas Técnicas CBPF-NT-002/18 fevereiro 2018

Published in Unpublished, 2018

Notas Técnicas CBPF-NT-002/18 fevereiro 2018.

Recommended citation: Manuel Blanco Valentın, Márcio P de Albuquerque, Marcelo P de Albuquerque, Elisângela L Faria, Yann Le Guével, Clécio Roque de Bom, Maury D Correia (2018). "Notas Técnicas CBPF-NT-002/18 fevereiro 2018."
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