Liquefaction is a destructive phenomenon which usually takes place after an earthquake in areas with water-saturated soil or sand. During the liquefaction process, soil loses its strength and can no longer support structures and buildings which often leads to their destruction. To prevent damages associated with liquefaction, it is critical to study this phenomenon and […]

This project aims to further develop cost-effective methods for characterizing fluid flow fields in high-energy tidal channels, with a focus on use of low-profile drifters to calibrate and validate numerical models of ocean flows. The project will focus on the Finite-Volume Community Ocean Model (FVCOM) used by Acadia and Luna Ocean, primarily for tidal energy […]

The project is a partnership between Polytechnique Montréal, HEC Montréal, UQAM and JDA Canada. JDA Labs is investigating new approaches to help incorporate “big data” science and analytics into everyday supply chain decisions. It relies on new approaches that employ sensor technologies, new analytic capabilities and simulation techniques to not just sense and respond, but […]

Insurance companies heavily fund marketing campaigns such as, for instance, customer retention or cross-sell initiatives. Uplift modeling aims at predicting the causal effect of an action such as medical treatment or a marketing campaign on a particular individual by taking into consideration the response to an action. Typically, the result of an uplift model is […]

Medicago, a clinical-stage biopharmaceutical company, has the potential to rapidly develop a vaccine in response to a newly sequenced influenza strain, allowing for large-scale vaccination of the population very early during a pandemic. The company would like to know how many doses of vaccine is required and what distribution strategies should be used to maximize […]

Radars are being used more and more in critical sites such as airports, military bases and borders for surveillance of huge areas to detect unwanted intrusions. Determination of the type of each target is essential for such systems to identify the nature of the intrusion and avoid false and nuisance alarms. This thesis is focused […]

In this project, we address the problem of designing artificial learning-based methodology adapted to currency exchange risk valuation and classification. The goal is then twofold: 1) design and implement client risk classification methodology based on currency risk exposure and, 2) study the problem of dynamical optimal allocation within currency-risk hedging portfolios using non-parametric forecasting methods. […]

The internship will consist of studying, building, implementing and testing so called factors that are used to characterize the equities, commodities and currencies that the company invests in. These factors can be thought of as characteristics relating a group of securities that is important in explaining their returns and risk. My task will be first […]

Over the last few years, the data revolution occurred with the emergence of “Big data”. In medical field, the term big data refers to large databases in terms of patients and/or information from varied sources. Nevertheless, heterogeneity is encountered in this kind of data. Indeed, data arise from different medical centers. Furthermore, we can’t perform […]

Natural disasters that are associated to the atmosphere (known as atmospheric perils) such as hurricanes, tornadoes and hail, flooding, drought, and wildfire, caused over $100 billion in damage throughout the world in 2015. Insurance companies often cannot afford to be responsible when such catastrophes occur, and so they purchase insurance to protect themselves (called reinsurance) […]

A critical issue in the oil and gas industry is to quantify the composition of fluids flowing back from the hydraulic fracturing process. This quantification is usually carried out by a manual process (frequently via a visual test) to estimate the water and oil produced from a well flow back process. A sample of these […]

Machine learning is the concept where a computer can be trained to recognize data and predict future outcomes based on the trends that exist in the data. This method of analysis has not been used on engine data, specifically in-line oil. Oil is an engine’s lifeblood and a lot of data can be collected and […]