Klashwerks is an Ottawa-based engineering design and Technology Company founded in 2016 that focuses on the emerging connected car market. They are currently developing an intelligent driver companion for smart car. One desirable feature of this product is to offer the possibility to drivers to interact with the device by simply using their hands. Gestures constitute indeed one of the most powerful modality for humans to interact with computers.
High-end chemical products, such as specialty polymers and pharmaceuticals, are important to provide a high quality of life. The effectiveness of these products is dependent on intensive development and consistent production. The focus of this project is developing new technology to improve both development and production of these products. To address product development issues, we are developing, modeling, experimental design and optimization tools that allow the rapid development of products.
The only constant in communications networks is change. Software defined networking (SDN) and elastic optical networking (EON) technologies enable adaptation to change but their implementation is impeded by the rigidity of network infrastructure and specifically the optical transport layer. Analogous to the term bare metal used to describe commodity electronics, bare glass photonics technology is need be developed so that all network functions electronic or optical are software defined.
Denial of service attacks deny a service, such as visiting a website or access to a network, by deliberately congesting the server or the network resources. In addition to delivering digital contents to end-users, content delivery networks (CDNs) are supposed to protect the content origins, such as Netflix or Amazon Video, against denial of service threats. However, denial of service attacks not only evade a CDNs protection but also exploit its resources to damage content providers and the CDN itself. As such, traditional security mechanisms are no longer sufficient.
Pintellect is Enterprise Social Software that gives employees access to the thoughts and ideas of the organizations influencers by encouraging them to share links to the internal files or external resources such as books, TED talks, podcasts, articles, etc. The objective for this project is to develop multiple algorithmic solutions for curated feed of content by department on the dashboard based on number of identified criteria.
Content Delivery Networks (CDNs) represent the up-to-date standard to transfer data through on-growing Internet. They are designed to manage traffic streams to avoid network problems. Despite the fact that CDNs attempt to satisfy security requirements (authentication, data privacy and integrity), they face rising innovative threats, observable in the cyber-space. The main objective of this project is to design, implement and test new methods to detect and prevent maliciousness in CDNs. We aim at building an alternative solution to classical Web Application Firewalls (WAFs).
We are in the process of creating and growing a team of researchers expert in the field of machine learning and data-mining. Ultimately, our aim is to create solutions to eliminate the need to manually define personalization strategies. We are in the process of signing partnership agreements with retailers capable of collecting large-scale datasets of customer behaviour. Through a data-sharing/consulting partnership we plan to perform research on the design of recommender systems customized for the data-sets available to brick and mortar retailers.
Networks are ubiquitous in our world. In broad terms, a networked control system consists of sensors, actuators and controllers interconnected and coordinated through a communication network. Networked control with distributed intelligence can open new directions in the industry of robotic entertainment allowing for pursuer-evader games to be played with multiple robots. The research proposed here will give a first step in this direction.
Environmental modelling and monitoring software systems, which are very important in assessing the effects of climate change, require open data from a large number of sources including all levels of government, NGOs such as watershed management authorities, consultants and business. This data needs to be brought together into internal databases and to be kept up-to-date to perform the required underlying computations. Collecting this data manually and keeping it current requires an incredible amount of error-prone manual labour.
Deep learning is currently the dominant machine learning technique as a result of state of the art performance in vision (Russakovsky, et al., 2015), speech (Amodei, et al., 2015) and natural language processing (Vinyals et al., 2015). The improvement in performance of these models is attributed to the availability of large datasets for training the models as well as software & hardware improvements that help accelerate the training process. Recurrent Neural Networks (RNNs) are one of the most powerful and popular frameworks for modeling sequential data such as speech and text.