Photo of myself (supposedly)

Antonio Rodríguez Hidalgo

Data scientist and PHD Candidate

Cell: (+34) 916248805
Address: Avda. de la Universidad, 30. PC: 28911, Leganés, Madrid. Office 4.2.A01
Email:

Linkedin profile

I am interested in artificial intelligence and machine learning methodologies such as ensemble algorithms and deep learning approaches. In fact, I find inspiring the last developments of Convolutional Neural Networks (CNN) applied to auditory and visual information.

Nowadays, I am developing my career in Universidad Carlos III de Madrid. The researches where I have taken part in the past are related with brain tumour segmentation using MRI and automatic vehicle tracking from road traffic cameras. Moreover, I have experience working with saliency detection and acoustic event detection algorithms.

Currently I am finishing my PhD thesis, and I am looking forward to the next challenge to come.

Professional Experience

PhD Candidate Multimedia Processing Group (UC3M), 2015 - Present

    I research and develop algorithms in order to compute auditory saliency, although I am also interested in the particular case of audiovisual saliency.

    Relevant topics: Saliency and attention, speech and audio processing, multimedia information, machine learning techniques, statistical fusion.

Research Visitor Chait Lab - University College London, 2018 (4 months)

    During this period of time I collaborated with the Chait Lab under the supervision of Maria Chait, an expert in the field of hearing neuroscience. My collaboration consisted of processing MEG data using Fieldtrip, a Matlab toolbox specifically designed for the analysis of EEG/MEG data. We tried to analyze and understand human responses when subjects listened to certain acoustic sequences of tones. More details about this research and results will be revealed in the future.

    Relevant topics: EEG, MEG, Matlab, Brain coding

Research AssistantMultimedia Processing Group (UC3M) , 2015

    I worked with the Multimedia Processing Group (aka GPM) of Universidad Carlos III de Madrid in the development of a tool to improve safety on road traffic.
    My contribution to the project was the implementation of an algorithm that was in charge of tracking vehicles that appeared on camera, considering that the videos we used had a really low resolution. Our proposal was a modified version of a particle filter, that used a background substraction algorithm in order to ease the tracking process, even when it faced dense traffic situations.

    Ref: SPIP20141507. Ministerio del Interior. Dirección General de Tráfico.

    Relevant topics: Vehicle tracking, Bayesian filtering, particle filtering, computer vision.

Assistant studentUniversidad Carlos III de Madrid (UC3M), 2014 - 2015

    I received a grant to collaborate with the Multimedia Processing Group (GPM) of Universidad Carlos III de Madrid to develop an algorithm to segment brain tumors automatically from MRI (Magnetic Resonance Imaging).

    Relevant topics: Medical imaging, MRI, machine learning.

Projects

"Saliency and Attention: Multimodality, Context-Awareness, Self-Adaptation and Bio-inspiration"

    Official name: “Saliencia y Atención: Multimodalidad, Context-Awareness, Auto-Adaptación y Bioinspiración”
    Ref: TEC2014-53390-P. Ministerio de Economía y Competitividad.
    Universidad Carlos III de Madrid.
    2015 - 2017

    IPs:

    Dr. Ascensión Gallardo-Antolín (gallardo@tsc.uc3m.es)
    Dr. Carmen Peláez-Moreno (carmen@tsc.uc3m.es)

"Robust techniques of artificial vision and their aplication to smart transport systems in order to improve road safety, movility and traffic management"

    Official name: “Técnicas robustas de visión artificial y su aplicación a los sistemas inteligentes de transporte para la mejora de la seguridad vial, la movilidad y la gestión del tráfico"
    Ref: SPIP20141507. Ministerio del Interior. Dirección General de Tráfico.
    Universidad Carlos III de Madrid.
    2014 - 2015

    IP: Dr. Fernando Díaz-de-María (fernando.diaz@uc3m.es)
Skills

Specific skills

Machine learning: supervised and unsupervised algorithms, feature extraction and selection, etc.

Deep Learning: algorithms for auditory event classification, mainly.

Signal processing: signal filtering, noise reduction, speech processing, voice activity detection, etc.

Computer vision techniques and algorithms: image recognition, object tracking, etc.

Programming skills

    Matlab: Highly experienced (more than 8 years of daily use).

    Python and some of its machine learning toolkits: scikit, pandas, numpy, etc.

    Keras API for Deep Learning

Computer skills

    Linux (regular user).

Secondary skills and knowledge...

    Spark (pyspark), C and Java programming, R programming, HTML, MySQL, JavasCript, Servlets

Courses and other merits

Finalist (2nd) at the best journal article award of the RTTH2018

Red Temática en Tecnologías del Habla (RTTH)

LXMLS: Lisbon Machine Learning School2016

Instituto Superior Técnico (IST) - Lisbon

    Topics of the school: This summer school mainly focused on some Machine Learning topics and how they were used to solve Natural Language Processing (NLP) tasks. The instructors and speakers provided both theoretical and practical knowledge about those techniques.

Education

Ph.D Program in Multimedia and Communication 2015 - Present

Universidad Carlos III de Madrid

    Topics of research: Speech and audio processing, auditory and audiovisual saliency, machine learning

Master's Degree: Multimedia and Communications 2015 - 2016

Universidad Carlos III de Madrid

    Major: Machine learning, data analysis, speech processing, computer vision

Master's Degree: Telecommunication Engineering 2014 - 2016

Universidad Carlos III de Madrid

    Major: RF systems, telecom. network protocols, multimedia processing, machine learning

Bachelor's Degree: Telecommunication Engineering 2010 - 2014

Universidad de Granada

    Major: Telecommunications systems and Digital Signal Processing

Publications
Antonio Rodríguez-Hidalgo; Carmen Peláez-Moreno; Ascensión Gallardo-Antolín, "The Robustness of Echoic Log-Surprise Auditory Saliency Detection", IEEE Access (2018), 6, pp. 72083-72093. DOI: 10.1109/ACCESS.2018.2882055

Antonio Rodríguez-Hidalgo; Carmen Peláez-Moreno; Ascensión Gallardo-Antolín, "Echoic log-surprise: a multi-scale scheme for acoustic saliency detection", Expert Systems With Applications (2018), 114, pp. 255-266. DOI: 10.1016/j.eswa.2018.07.018

Antonio Rodríguez-Hidalgo; Carmen Peláez-Moreno; Ascensión Gallardo-Antolín, "Towards multimodal saliency detection: an enhancement of audio-visual correlation estimation", 2017 IEEE International Conference Series on ICCI*CC. DOI: 10.1109/ICCI-CC.2017.8109785

Antonio Rodriguez-Hidalgo; Ascensión Gallardo-Antolín; Carmen Peláez-Moreno, "Towards aural saliency detection with logarithmic Bayesian Surprise under different spectro-temporal representations", Proceedings of Iberspeech (2016), pp. 99-108, Lisbon. Link!

Rodriguez-Hidalgo, Antonio; Gomez, Angel M.; Bochud, Nicolas; Soto, Juan M.; Peinado, Antonio M., "A clustering-based damage segmentation for ultrasonic C-Scans of CFRP plates", 2015 IEEE International Ultrasonics Symposium (IUS). DOI: 10.1109/ULTSYM.2015.0130