Experience — Sofia Zaidenberg

Objective: A position teaching computer science, specializing in teaching computer languages.
Summary:

Excellent teacher in IT, very appreciated by students, with a talent for clear explanation and presentation.
Committed computer science engineer with extended experience in designing approaches to solve research problems and implement functional end-user applications. As a student, won an award for best internship of the year.
Gifted with people and communication skills, rapid adaptation and learning. Efficient at producing written documents (first author of 8 scientific papers).
Extensive knowledge of machine learning, pervasive computing and computer vision, as well as many tools useful for implementation and design.
Skills include: C++, Java, Scala, Ruby, Ruby on Rails, Qt, QtQuick 2.2, LATEX, OSGi, Java EE 5, Maven, OpenCV, CMake, gdb, SQL among others.

Experiences

Detailed Description

Proposed an algorithm to detect and track groups of people in subway video-surveillance for the European project VANAHEIM.
Developed using the team’s Scene Understanding Platform, tested, evaluated, prepared demonstrations and presentations, published 2 papers. Integrated into the common project platform.
Initiated frequently interactions with team members, including guiding of PhD students, in an international office environment. Created documentation of internal tools.
Organized the Human Activity and Vision Summer School in collaboration with the VANAHEIM project.
Technical environment: C++, Qt, OpenCV 2.3.1, NetBeans, CMake, gdb, valgrind, corba, wiki.

Company website

Detailed Description

Taught IT at Bachelor’s level: a total of over 330 hours including algorithmics, programming (Java, C++, C, Ada), object oriented systems design and distributed architectures. Ran the class “Programming by components”. Engaged in fruitful collaboration with other members of the teaching staff. Prepared examination subjects, lectures and practical projects. Graded, supervised practical work, lectured.
Lead research in Ambient Intelligence. Co-supervised a master student on the subject of genetic learning of neural networks for situation recognition.
Developed an approach to recognize high-level user activities on a computer (such as writing paper, sorting pictures, working) using recurrent neural networks genetically learned from user-labeled training data consisting in keyboard and mouse events associated with an activity label.
Technical environment: Java, OSGi, iPOJO, Maven, Hibernate, Castor, Eclipse, NetBeans, JOnAS.

Company website

http://www-prima.imag.fr/

Leading research on the topic "Learning context models for the recognition of scenarios" for the European project CAVIAR.

Detailed Description

Proposed an approach for learning context models for the recognition of scenarios. Developed an automatic method based on Hidden Markov Models for recognizing scenarios in videos given the learned models on training videos. Tested and evaluated the method in different conditions.
Integrated the resulting software as a contribution to the European project CAVIAR, wrote a deliverable and published 1 paper as main author and 1 as co-author.
Technical environment: Java, Eclipse.

Company website

http://www-prima.imag.fr/

Detailed Description

Developed a software for automatic calibration of image-walls (a display surface formed by several video-projectors). The team used the software until the dismantling of the image-wall.
Technical environment: C++, make, OpenCV, Qt, OpenGL.

Company website

Detailed Description

Designed and implemented a generator of HTML forms (with the database structure to store submissions).
Technical environment: php, HTML, PostgreSQL.

Company website

Detailed Description

Company website

http://www.enerdata.net/

Sofia Zaidenberg