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Member since October 30, 2005
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Eight years of extensive experience in design, research and development of different scale software solutions for high-accuracy real-time systems, with strong mathematical and statistical background. Substantial research in biometrics, with focus on unconstrained scenarios and uncooperative applications, and acceptance in the scientific community. Top quality development skills using latest technologies including Java, Objective-C, C++, Unix script and in-depth knowledge of MATLAB. Excellent communication, presentation and interpersonal skills.
$20 USD/hr
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Software Design Engineer

Aug 2015

Responsible for the specification, design, implementation, and integration and testing of the ASML products. Developing and realizing software solutions for high-accuracy real-time systems, solving problems in a multi-disciplinary team-effort. Manage technical complexities within the scope of influence and area of expertise, working autonomously.

Independent Consultant

Mar 2011 - Jun 2011 (3 months)

Engineering and deploying the statistics module for a professional sports mobile application, in coordination with an extensive team from different fields of expertise. Application was first place on AppStore top during several weeks. Objective-C, Cocoa, SQLite, XCode

Teacher Assistant

Sep 2009 - Jun 2011 (1 year)

Teach the practical classes on both Databases and Internet Technologies for the courses of Computer Science and Engineering, Information Systems Technologies and Sport Sciences. MySQL, PHP, HTML, JavaScript, CSS, Apache

Computer Vision Researcher

Oct 2008 - Jul 2015 (6 years)

Research, design and develop different scale applications in the field of computer vision, with strong mathematical and statistical background. Coordinate with multidisciplinary teams aiming at the development of a commercially viable prototype, with high-performance and real-time requirements. C/C++, MATLAB, OpenCV



2007 - 2009 (2 years)


2003 - 2007 (4 years)


2009 - 2014 (5 years)


Certified Scrum Master (2017)

Scrum Alliance

A Certified ScrumMaster® helps project teams properly use Scrum, increasing the likelihood of the project's overall success. CSMs understand Scrum values, practices, and applications and provide a level of knowledge and expertise above and beyond that of typical project managers. CSMs act as "servant leaders," helping the rest of the Scrum team work together and learn the Scrum framework. CSMs also protect the team from both internal and external distractions.


BioHDD: a dataset for studying biometric identification on heavily degraded data

Substantial efforts have been put into bridging the gap between biometrics and visual surveillance, in order to develop automata able to recognize human beings ‘in the wild’. This study focuses on biometric recognition in extremely degraded data, and its main contributions are three-fold: (1) announce the availability of an annotated dataset that contains high quality mugshots of 101 subjects, and large sets of probes degraded extremely by 10 different noise factors; (2) report the results of a mimicked wat

Periocular Biometrics: An Emerging Technology for Unconstrained Scenarios

The periocular region has recently emerged as a promising trait for unconstrained biometric recognition, specially on cases where neither the iris and a full facial picture can be obtained. Previous studies concluded that the regions in the vicinity of the human eye - the periocular region- have surprisingly high discriminating ability between individuals, are relatively permanent and easily acquired at large distances. Hence, growing attention has been paid to periocular recognition methods, on the perform

Facial Expressions: Discriminability of Facial Regions and Relationship to Biometrics Recognition

Facial expressions result from movements of muscular action units, in response to internal emotion states or perceptions, and it has been shown that they decrease the performance of face-based biometric recognition techniques. This paper focuses in the recognition of facial expressions and has the following purposes: 1) confirm the suitability of using dense image descriptors widely known in biometrics research (e.g., local binary patterns and histogram of oriented gradients) to recognize facial expressions

Iris Recognition: Analyzing the Distribution of the Iriscodes Concordant Bits

The growth in practical applications for iris bio- metrics has been accompanied by relevant developments in the underlying algorithms and techniques. Efforts are being made to minimize the tradeoff between the recognition error rates and data quality, acquired in the visible wavelength, in less controlled environments, over simplified acquisition protocols and varying lighting conditions. This paper presents an approach that can be regarded as an extension to the widely known Daugman’s method. Its basis is

Fusing color and shape descriptors in the recognition of degraded iris images acquired at visible wavelengths

Despite the substantial research into the development of covert iris recognition technologies, no machine to date has been able to reliably perform recognition of human beings in real-world data. This limitation is especially evident in the application of such technology to large-scale identification scenarios, which demand extremely low error rates to avoid frequent false alarms. Most previously published works have used intensity data and performed multi-scale analysis to achieve recognition, obtaining en

A Robust Eye-Corner Detection Method for Real-World Data

Corner detection has motivated a great deal of research and is particularly important in a variety of tasks related to computer vision, acting as a basis for further stages. In particular, the detection of eye-corners in facial images is important in applications in biometric systems and assisted- driving systems. We empirically evaluated the state-of-the-art of eye-corner detection proposals and found that they achieve satisfactory results only when dealing with high-quality data. Hence, in this paper, we

Segmenting the Periocular Region using a Hierarchical Graphical Model Fed by Texture / Shape Information and Geometrical Constraints

Using the periocular region for biometric recognition is an interesting possibility: this area of the human body is highly discriminative among subjects and relatively stable in appearance. In this paper, the main idea is that improved solutions for defining the periocular region-of-interest and better pose / gaze estimates can be obtained by segment- ing (labelling) all the components in the periocular vicinity. Accordingly, we describe an integrated algorithm for labelling the periocular region, that uses

Fusing iris and periocular information for cross-sensor recognition

Over the last years the usage of mobile devices has substantially grown, along with their capabilities and applications. Extending biometric technologies to such gadgets is quite desirable, as it would represent the ability to perform biometric recognition virtually anytime, anywhere, and by everyone. This paper focus on biometric recognition on mobile environments using the iris and periocular information as main traits, and its main contributions are three-fold: 1) announce the availability of an iris and

Iris Recognition: Preliminary Assessment about the Discriminating Capacity of Visible Wavelength Data

The human iris supports contactless data acquisition and can be imaged covertly. These factors give raise to the possibility of performing biometric recognition procedure with- out subjects’ knowledge and in uncontrolled data acquisition scenarios. The feasibility of this type of recognition has been receiving increasing attention, as is of particular interest in visual surveillance, computer forensics, threat assessment, and other security areas. In this paper we stress the role played by the spectrum of t

A fusion approach to unconstrained iris recognition

As biometrics has evolved, the iris has remained a preferred trait because its uniqueness, lifetime stability and regular shape contribute to good segmentation and recognition performance. However, commercially deployed systems are characterized by strong acquisition constraints based on active subject cooperation, which is not always achievable or even reasonable for extensive deployment in everyday scenarios. Research on new techniques has been focused on lowering these constraints without significantly i


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