Innovative Projects Realized

Investigations into the mechanism of action and potential in idiopathic pulmonary fibrosis of the novel ruthenium based therapeutic BOLD-100

Idiopathic pulmonary fibrosis (IPF) is a chronic and fatal disease lung disease with unknown cause. There are limited treatment options for IPF and investigations into new treatment options is needed. BOLD-100 is a clinical-stage small molecule that is currently being investigated as a treatment option in oncology and viral infections. The pathway that BOLD-100 impacts, the unfolded protein response, is important in IPF and therefore this project’s objective is to use preclinical models to test whether BOLD-100 can affect development of IPF. The interns will gain experience using a range of different models to test an industry backed compound and will interaction with industry veterans at the partner organization, Bold Therapeutics. Bold Therapeutics will benefit by utilizing the expertise of the Ask laboratory to potentially expand the potential of BOLD-100 into IPF.

Development and Validation of a Protein-Protein Interactions Modeling Platform for Rapid Affinity Predictions and Pharmaceutical Applications

Developing a drug for new diseases cannot only be challenging but also time consuming. From the identification of a druggable target to a compound which can improve a condition it usually takes more than 12 years. Since there is basically an infinite number of possible compounds which can be turned into a drug it is literally the problem of finding a needle in a haystack. The trial and error method of making molecules in the laboratory and testing their efficiency has been proven successful for over a century. However, with ever growing numbers of druggable molecules, diseases and classes of drugs, this traditional workflow has become too time consuming. Efficient computer models can help rationally pre-select a much smaller number of potential drug candidate compounds which can then selectively been tested. This internship aims at testing and enhancing the predictability of a computational tool capable of guiding the development of a new emerging class of drugs, stimulating the human immune system. These drugs, called antibodies, can cure the condition by finding and interacting with their target.

Deployment of motion platform control architecture for a high-fidelity driving experience in simulators

Realistic driving experience in motion simulators is a key element for the impressiveness of the VR based simulators. In the driving simulator the free motion of the vehicle is mapped to a motion platform with limited workspace by filtering out the motion and scaling it down with a motion cueing algorithm. These algorithms should be designed in such a way to give a feeling to the users as if they are driving a real vehicle.
The output of the previous stage needs to be fed to actuators of a simulator so that they can apply the required forces and torques to the system to generate the desired motion cues to the user. However, these forces are felt by the user in terms of accelerations and the media between the user and the actuators is the structure and dynamics of the simulator. Therefore, one needs to know the model of the simulator. Then, there is a need to interpret these desired feelings by the user in terms of the actuator forces and motor torques which are obtained by a set of secondary control filters. Therefore, we need to first identify a mathematical model of the platform and tune its parameters.

Diagnostics and Explainable Machine Learning Models

Despite the advances of Machine Learning, the models are still being considered black-boxes that are difficult to diagnose and explain. The model performance diagnostic measures are critical to the assessment of the model’s relevance, accuracy and robustness. Good models’ performance is the primary enabler of their successful deployment in real-life applications. However, even if the models perform well, it is not known why the models predict the way they do, that is, which input variables are responsible for the models’ predictions. The purpose of the research is two-prone: 1) to identify the relationship between the measures of model performance and recommend which measures should be used in the model production environment, and, 2) develop the methodology of explaining machine learning models in terms of the models’ inputs, as well as, other, potentially relevant, variables, not selected in the model.

Génération de modèles 3D humains à partir d’images 2D et de nuages de points

L’objectif principal est de mettre à disposition de notre partenaire industriel Bodyform3D des outils informatisés innovants afin d’améliorer et d’enrichir leurs technologies (plateforme d’acquisition et de modélisation 3D) pour répondre à des besoins dans le domaine médical avec une application pour le traitement en urgence des grands brûlés ou pour la mensuration de sujets pour la génération d’avatars.

Small molecule agonists of SHIP1 for treatment of inflammatory disease

Activation of the immune system is necessary for defense against pathogens and injury, but just as important are the processes to turn this inflammatory response once the infection or injury has been resolved. Inappropriate prolongation of immune cell activation results in inflammatory diseases such as inflammatory bowel disease, asthma and arthritis. The University of British Columbia (UBC) partners in this project have previously shown that activating the intrinsic braking system in cells, a protein called SHIP1, using small molecule compounds can reverse inflammation. We propose to optimize the chemical and biological property of these compounds so that they can be tested in humans for treatment of inflammatory disease. ZebraPeutics Inc has license these compounds from UBC to support their development and subsequent testing in human clinical trials. The work proposed in this application will support this goal.

Digital Media Products Associate

Yalty Software is a start up aiming to resolve pain points in the e-commerce ecosystem. We have been working with student teams from CDM and BCIT to create parts of our total platform. We had been in the process of a funding round in February/March when the uncertainty caused by COVID-19 slowed or stopped investment into start ups like ours. However, we feel that time to market is important so we have been continuing our work. Our ability to hire talented staff iskey to helping us get our product to market and will solidify our ability to raise funds in the future. Our platform will eventually integrate with Shopify eRetailers through the Shopify platform. We expect this solution to take an extended period of time. Short-term, we will create up to ten Shopify e-retailers to prove the business model and generate revenues. The intern will be responsible for delivering the final result: ten operating Shopify stores together with the various social media marketing devices that would be considered typical.

Forest Stewardship Group Development

For the past six years, Ecotrust Canada has managed a group licence for FSC Canada
(http://ecotrust.ca/ fsc) . This group licence allows smaller woodlot owners and chain of custody
businesses to have FSC certification at a much lower cost. The program has proven to be very
successful but has not yet reached a break even financing level.
The project will build off of recommendations provided in Ecotrust’s 2012 FSC group certification
business plan, and look at identifying where added values (costs, benefits and differentiation
strategies, etc.) exist for new potential members. Recommendations for how Ecotrust and its
members can gain broader exposure, improve accessibility to consumer market, create alliances with
relevant organizations, and raise awareness about the benefits of supporting sustainable business
practices will be developed. Opportunities for Ecotrust to provide additional consulting services to its
members will also be identified.

Autonomous Mission Planning and Simulation Software Design for Unmanned Surface Vehicles

Ocean industries and researchers need the on-site oceanographic and environmental data, but collecting that data is costly, challenging, and time-consuming. Unmanned surface vehicles (USVs) offer a promising solution for marine data collection. Equipped with oceanographic sensors, cameras and communication devices, the USV Data Xplorer developed by Open Ocean Robotics can voyage for extended periods thanks to the additionally generated solar energy from the USV’s solar panels. Mission range and the travel path for fulfilling the specified task will be dependent on the geographical location of the task area, energy management of the USV, and environmental conditions. Therefore, research on autonomous mission planning based on various practical factors is desirable and will play an instrumental role in the USV product development. An offline mission planner will be designed to predict and schedule a feasible task considering the following factors: the energy generated by the solar panels, power consumption of the USV, and impact of mission-specific environmental conditions including prevailing wind speeds, average currents, sunlight level, etc. A simulation software will be developed by integrating the above-mentioned algorithms and modules.

Analyse adaptative de flux de trafic réseau pour la cybersécurité

Malgré les efforts consacrés à la détection des problèmes de sécurité dans les systèmes informatiques, de nombreux défauts s’échappent sur le terrain, provoquant de graves défaillances et d’énormes pertes financières. Pour identifier la nature des problèmes, les développeurs de logiciels s’appuient fortement sur l’analyse des journaux (logs), générés lors des exécutions du système. Les logs sont également utilisés dans la détection des intrusions de sécurité, l’analyse des performances et le diagnostic des pannes. Cependant, les logs ont toujours été difficiles à utiliser.

L’objectif de ce projet est d’explorer l’utilisation de l’analyse des logs et des techniques d’apprentissage machine (spécialement algorithmes Random Forest et apprentissage par renforcement) pour la détection précoce d’anomalies de sécurité dans le trafic réseau et étudier si et comment ces nouveaux algorithmes peuvent être appliqués aux logs de Devicom. Nous nous concentrons en particulier sur les flux de trafic IP. Ceux-ci contiennent souvent assez d’information pour déceler une attaque en cours, mais le problème du volume intraitable de données est particulièrement saillant.

Nous examinerons également la pratique de l’exploitation de logs et proposerons des recommandations.

Induction Heating Supply

Electrical heating of oil sands allows for production in situ in a mode similar to conventional liquid oil production. This avoids disturbing and redistributing the overburden and production sands. A further advantage of electrical heating is that the power consumption can be matched to the availability of sources such as wind power.

Marketing and Project Managers

Founded in 2018, The En Lab Coworking Space is headquartered in Richmond BC, and the business scope mainly covers three aspects: Coworking Space Rental, Management Consulting, and Investment. The Marketing and Project Manager/Intern works closely with the CEO of the corporation and the business development team. The position is considered entry-level to start, with providing of extensive training in marketing strategies, direct advertising, promotional techniques, consumer market research, marketing and business management, public relations and public speaking, customer service, and sales.