Sofia Zaidenberg

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A position in computer science, contributing to the development of innovative applications.

• Committed computer science engineer with extended experience in designing approaches to solve research problems and implement functional end-user applications. As a student, won best internship award.
• Excellent teacher in IT, very appreciated by students, with a talent for clear explanation and presentation.
• Gifted with people and communication skills, rapid adaptation and learning. Efficient at producing written documents (first author of 10 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, JavaFX 2.0, Python, Qt, LaTeX, OSGi, Java EE 5, Maven, OpenCV, CMake, gdb, SQL among others.

• 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.

• 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.

• 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.

• 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.

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

• Implemented a graphical user interface to an Oracle database.
• Technical environment: C++, Visual C++ .NET, MFC.

• Subject: Reinforcement Learning of Context Models for Ubiquitous Computing
• Co-financed by CNRS and INRIA, in the PRIMA group of the LIG laboratory under the supervision of Pr. James Crowley and Pr. Patrick Reignier.
• Elaborated an approach to learn user preferences in a complex ubiquitous system and developed a distributed prototype dealing with a dynamic environment. Addressed difficulties coming from working with a real-world problem.
• Published 8 papers including 3 book chapters and 1 journal article.
• Technical environment: Java, OSGi, iPOJO, Java EE 5, Maven, Hibernate, Eclipse, NetBeans, JOnAS.
• Selected trainings: Summerschool on computer vision (2005), patents, scientific English.

• Selected courses: “Machine Learning”, “Bayesian Learning”, “3D Computer Vision”, “Image matching and recognition” and “Projective Geometry”.
• Graduating internship on “Learning context models for the recognition of scenarios” – publication of 1 paper.
• Final grade: 14.63/20, ranked 5^th/14

• Selected courses: “Advanced information systems”, “Network, security”, “Optimization”, “Robotics and Virtual Reality”, “Data mining”, “Graph Theory” and “Project Management”, “Accounting”, “Business Law”.
• Internships: automatic calibration of video-walls (won best intership award), creation in php of a tool to automatically generate html forms (with the database structure to store submissions) and creation in C++ of a graphical user interface to an Oracle database.
• Final grade: 16.19/20, ranked 3^rd/90

• Computer Languages: C++, Java, C, JavaFX 2.0, JavaScript, HTML, LaTeX, PHP, SQL, Ada, Pyton, bash scripting, AJAX
• Tools: OSGi, iPOJO, Java EE 5, JOnAS, Hibernate, Maven, CVS/SVN/GIT, Make, CMake, PostgreSQL, MySQL, Eclipse/NetBeans, Qt, OpenGL, UML, XML, XSD, gdb, valgrind, gprof, Visual C++
• Operating Systems: Linux (Debian, Fedora, Ubuntu), Windows XP/Vista/7
• Spoken Languages:
  • French: fluent
  • English: fluent (890/990 at the TOEIC test in 2003)
  • Russian: spoken – advanced, written – intermediate
  • German: spoken and written – intermediate
  • Spanish: spoken and written – beginner

• Won best internship award for engineering school (IIE) graduating internship “Auto-calibration of image walls” from the industrial sponsor (2004). Selection among the 90 students of the class.
• Volunteered for conference organization (2005, 2007, 2012).

Extra-curricular interests and activities include sports (running (completed a semi-marathon), yoga, roller hockey...) and reading (novels in French and English). Most valued activities are the ones involving communication and sharing with friends or new people, for an enriched and open mind.