NSERC Discovery Grants Program

Record-setting success rate for ÉTS researchers

Wednesday, June 5, 2019
charles despins
Charles Despins, Director of Faculty Affairs, Research and Partnerships

Several weeks ago, 31 researchers from ÉTS learned that, over the course of the next 5 years, they would have an opportunity to delve into the boldest and most promising ideas within their respective fields of research. Thanks to the Discovery Grants Program administered by the Natural Sciences and Engineering Research Council of Canada (NSERC), they will share a budget envelope totaling close to $1 million that is renewable annually for a period of 5 years. This is one of the largest amounts ever allocated to ÉTS researchers within the context of this Program. 

Charles Despins, Director of Faculty Affairs, Research and Partnerships at ÉTS, explained: “We are extremely proud of the success rate that our researchers attained during the most recent competition: 74% of those who submitted Grant requests received a positive response, which represents an 8% increase in the success rate compared to last year”.

claire samson dean research
Claire Samson, Dean of Research

According to Claire Samson, Dean of Research at ÉTS, there are a number of factors that played a role in this success. “Our researchers clearly impressed their peers, not only because of the quality of the projects they presented, but also because of the innovative character of those projects. I also believe that the high level of expertise among the professors we hire counts for something. In my opinion, it is significant that six of the eight early career researchers who submitted grant requests received a positive response”.   

ÉTS researchers can now test their hypotheses in a wide variety of fields, including Industry 4.0, artificial intelligence, network virtualization, new materials, edge computing and others. 

“Learning that they have received a Grant is always good news for researchers, and the level of enthusiasm really ramps up when it involves the NSERC Discovery Grants Program”, Ms. Samson pointed out.

A very competitive funding program

The NSERC Discovery Grants Program is one of the most competitive funding programs around. Every project that is presented in connection with this Program is evaluated by a peer review committee based on three criteria: the excellence of the researcher’s work, the value of the proposal and its contribution to the training of highly skilled personnel.

The exceptional success rate that ÉTS researchers have posted is even more remarkable in light of the fact that the program criteria have become stricter in recent years.  

It is also worth mentioning that the average sum granted to the 31 ÉTS professors in 2019 (approximately $33,000) is the highest ever received to date. 

In fact, considering that funding for Discovery Grants extends over a period of 5 years, there will actually be 132 ÉTS professors who receive funding under this Program. 

lucas hof ets
Lucas Hof, Professor-Researcher at ÉTS

Early career researchers at ÉTS make their mark!

ÉTS also performed extremely well within the context of a new category aimed at early career researchers, or those who have less than 3 years of research experience. Six of the eight early career researchers at ÉTS who submitted requests obtained a Grant, and they also received a supplemental amount of $12,500 for the first year of their funding. 

For these new researchers, receiving a Discovery Grant represents a turning point in their careers. It is worth noting that this is often a stepping stone to obtaining other grants.

According to Lucas Hof, a Professor-Researcher at ÉTS who obtained a Grant for the first time: “This Grant confirms the relevance and innovative nature of my project for the manufacturing sector.” The Grant will allow him to pursue a project related to the application of Industry 4.0 to circular manufacturing. 

Contributing to the economic development of Québec

Over and above the numbers and statistics, it is essential to keep in mind what is really important: These researchers generate ideas that may end up stimulating economic growth, transforming a field of research or helping a local or international colleague to resolve a long-standing problem.  

In short, research is a breeding ground the advancement of knowledge and the economic development of Québec. There is no doubt that the community of engineering researchers at ÉTS has what it takes to achieve all of these objectives – imagination, expertise and enthusiasm.

List of recipients from ÉTS - 2019 Competition

Ismail Ben Ayed
Systems Engineering
Optimization and learning algorithms for medical image interpretation

Conrad Boton
Construction Engineering
A systemic approach to designing Common Data Environments in construction

Vladimir Brailovski
Mechanical Engineering
Lattice-based shape memory and superelastic structures: Design, manufacture, modeling, and applications

Alan Carter
Construction Engineering
Optimization of bitumen-emulsion treated bituminous materials

Henri Champliaud
Mechanical Engineering
Heat Assisted Local Forming and Joining Processes: Simulation and Experimentation

Mohamed Cheriet
Systems Engineering
Data-driven modeling for understanding ancient documents from multimodal images

Éric David
Mechanical Engineering
Development of graphene and boron nitrate-based polymeric systems for electrical applications

Louis Dessaint
Electrical Engineering
Technical and economical optimization of a behind-the-meter battery system

Jean-Sébastien Dubé
Construction Engineering
Constitutional and distributional heterogeneity of contaminated soil and its influence on sampling uncertainty

Martine Dubé
Mechanical Engineering
Repair of thermoplastic composite structures by induction heating

Thomas Dupont
Mechanical Engineering
Study and development of materials structured for acoustic applications and low-frequency vibration 

Handy Fortin Blanchette
Electrical Engineering
Optimization of the design of SiCMOS and GaN converters used in distributed energy resources

Julien Gascon-Samson
Software and IT Engineering
Cloud-to-Edge Computing: A Unified Computational Paradigm

Mathias Glaus
Construction Engineering
Model of territorial metabolism for closed-loop residual waste streams

Lucas Hof
Mechanical Engineering
Development of circular manufacturing processes in the era of Industry 4.0

Armin Jabbarzadeh
Systems Engineering
Improving the Resilience and Sustainability of Intermodal Freight Transportation Systems

Simon Joncas
Systems Engineering
Conception and validation of analysis tools for transversely reinforced composite materials

Georges Kaddoum
Electrical Engineering
Intelligent networking for an autonomous Internet of underwater things: From smart cities to a smart world

Ammar Kouki
Electrical Engineering
Devices, Circuits, Processes and Tools for Reconfigurable and Programmable Power-Efficient Microwave Circuits

Louis Lamarche
Mechanical Engineering
GHG reduction through the use of natural refrigerants in energy efficiency applications

René Jr. Landry
Electrical Engineering
Universal Software-Defined Avionic Receiver (SDAR) for Robust and Resilient Positioning, Navigation and Timing (PNT)

Catherine Laporte
Electrical Engineering
Intelligent Ultrasound Imaging

Aris Leivadeas
Software and IT Engineering
From IoT to Cloud: A Network Function Virtualization end-to-end communication solution

Zhaoheng Liu
Mechanical Engineering
Optimization, vibration control and condition monitoring of collaborative robotic machining

Marie-José Nollet
Construction Engineering
Seismic fragility assessment of urban residential buildings constructed from masonry and wood

Rita Noumeir
Electrical Engineering
Decision support for intensive care

Éric Paquette
Software and IT Engineering
Geometry Processing Approaches for Defective Discrete Surfaces

Tan Pham
Mechanical Engineering
Modeling of keyhole-mode laser welding

Louis Rivest
Systems Engineering
Semantic representation of alternative conflict resolution methods for collaborative CAD 

Christine Tremblay
Electrical Engineering
Smart Optical Networks Enabled by Machine Learning

Lyne Woodward
Electrical Engineering
Optimal and intelligent management of the energy extracted from multi-unit systems

Information: 
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