April 23, 2020 - Health + Digital Quebec
From artificial intelligence to robotics, through immersive technologies: various digital health applications have substantially developed.
Innovation is at the service of patients and medicine and is advantageous to rehabilitation as well as prevention. Research teams in companies as well as in academic or clinical environments develop innovative approaches and technologies related to virtual reality, big data or internet of things.
Throughout a dozen conferences and interventions, supported by a poster session and a demonstration area, you are invited to take the pulse of these inspiring approaches during the second edition of Health + Digital Quebec event.
An opportunity to dive into the world of health innovation and see how health and social services environment appropriates and develops digital technology!
08:00 AM-06:00 PM
Collège François-de-Laval - Salle des promotions
20 rue Port-Dauphin
Ville de Québec, QC G1...
April 20, 2020 - Artificial Intelligence meeting of Quebec 2020
Gathering about 600 participants, the artificial intelligence (AI) meeting of Quebec will be back for a third edition on April 20, 2020, as part of Digital Week. In the program: the most recent contributions according to artificial intelligence, and the international positioning of the Greater Quebec area in this domain. In parallel, the event proposes the discovery of this discipline for the less experienced in order to understand its implications and possibilities.
Thus, AI meeting of Quebec continues to enrich dialog between the ecosystem actors and the people who want to discover different facets of its applications. Raised reflections and exchanges between the participants contribute to the sustainable and ethical development of artificial intelligence, to a common understanding of the issues and to the establishment of a shared vision by the members of the industry.
During this event, the different facets of artificial intelligence will be explored, fr...
March 2, 2020 - Winter school in machine learning
March 2 to 6, 2020
Machine learning is a study field of artificial intelligence making interaction of a set of computer and statistical tools that allow the computer to "learn" from data. Therefore, it can perform functions or automatically answer to the questions without explicit programming.
Because digital transformation is already underway, all activity sectors have to integrate these novel technologies into their business process in order to remain competitive. Techniques are continually improving and the need to skilled and trained professionals for this type of approach is growing exponentially. For the second time, and during an intensive and highly applied training week, the winter School will allow candidates to participate in their field projects and will furnish data necessary to continue this learning in their workplace, research or studies.
Participants will benefit from the expertise of professors and professionals of big data research center (BDRC) of Laval...
October 28, 2019 - Quebec day for data valorization CRDM-IVADO 2019
Université Laval Center for Big Data Research (CRDM) and the Data Recovery Institute (IVADO) are pleased to invite you to the second edition of the Journée québécoise de valorisation des données!
This event is aimed at people involved in the field of big data at both the research and industry level and wishing to reflect on their work and their social significance.
In line with the first edition of 2018 that took place in Montreal (lien), this second edition in Quebec City will revolve around conferences and panels of experts in various fields including health, environment, governance, data and university-industry collaboration. Check out the full program ici for more details.
A dinner and a closing cocktail will be served, encouraging exchanges among participants and stakeholders.
Hope to see you there,
September 24, 2019 - New CRDM website!
The CRDM is getting a makeover. Take the time to visit the different parts of the new website.
Université Laval BDRC
The field of big data has been recognized as a priority area of development and highly promising by the Faculty of Science and Engineering and Université Laval.
Indeed, Big Data analysis is a challenge for a growing number of scientific disciplines considerating it merges problems of many domains to the same playing field.
With the contribution of researchers from five faculties, the Big Data Research Center (BDRC) is a catalyst for these multidiciplinary approaches. It intends to become a pivotal player in the field of massive data.
Our research areas
The field of bioinformatics faces a major problem: the researchers produce phenomenal amounts of data.
Since Bioinformatics covers "every aspect of computer science uses in the management, storage, analysis, processing, organization, comparison and dissemination of data relating to all biological sciences " (OQLF, 2005), the task is massive.
The BDRC is involved in multiple research projects related to important issues in bioinformatics :
Mathematical modeling and computational methods in biology.
The increase in analytical capacity faces an ever-growing quantity of produced data by the new high-speed technologies, like new generation sequencers, spectrometry mass, high throughput transcriptomics, and structural biology.
Algorithms development to analyze and structure quantity ever more impressive experimental data created in laboratory.
The use of heterogeneous datasets, or unstructured data, represents a major research challenge in processing big data. Different data can come under more than one form, which requires a complex model of data fusion.
The BDRC is actively involved in research projects related to important issues in non or partially structured data :
Multimodal model development, a data fusion model which makes it possible to exploit, for example, a set of image data accompanied by a set of textual data, corresponding to the textual descriptions of these images.
Approaches using machine learning, including deep learning which represents the state of the art in big data learning techniques.
Confidentiality, ethics and social acceptability
Confidentiality, integrity and respect for privacy are major concerns and must be taken into account. Indeed, all aspects of our daily lives are now massively managed by technological tools, which is critical in areas such as health, the economy or national security. Remote and heterogeneous sites must therefore have a particularly strict access control.
The MDRC collaborates on research projects whose subjects touch important issues in data privacy :
Improving confidentiality and integrity through access control mechanisms.
Application information flow control to have a better control over the way information is used once access is granted.
Methods development protecting the privacy of individuals when analyzing and sharing their personal information.