Synthetic population generation is the process of combining multiple socioeonomic and demographic datasets from various sources and at different granularity, and downscaling them to an individual level. Although it is a fundamental step for many data science tasks, an efficient and standard framework is absent. In this project, we propose a multi-stage framework called SynC […]

The general goal of this project is to improve the downstream tasks by learning better representations of the data, especially multimodal data pairs, like image/text pairs or user/item interaction pairs. The user/item interaction data plays an important role in e-commerce, and analyzing these data can help improve the banking system, e.g., recommendation, risk control, and […]

The recording of brain activity through neural Implantable Medical Devices (IMDs) has a wide range of applications, such as studying brain patterns for seizure detection or brain stimulation to alleviate motor disorders. Some IMDs communicate with an external interface platform, which offloads the recorded data from, programs, and supplies power to the IMD. However, existing […]

Businesses today struggle with manual operations such as paper-based processes and copying and pasting information from one system to another. These manual operations are costing companies hours of unnecessary labour, which trickles down to customers that are expecting on demand services. SOTI has developed a software product called SOTI SNAP that allows anyone to create […]

Unmanned aerial vehicles (UAV) have been deployed in many real-world applications such as payload delivery, agricultural laboring, and aerial photography. Based on GPS-based localization algorithms, these drones have achieved many advancements in industry automation. However, since common GPS receivers do not work indoors, an accurate computer vision (CV) technique is required to resolve the problem […]

Canadian public and private researchers have taken an interest in a new class of light-emitting materials, subphthalocyanines, which can produce better colour in OLED smartphone and television screens. The materials can be optimized for specific purposes by using slightly different ingredients in their synthesis, or by reacting them with other ingredients after synthesis, but most […]

The objective of this internship is to develop a Retail Credit Risk Scoring Model utilizing different alternate data sources and this model can give a credit score for people who has limited credit footprint. The intern will work on checking alternate data sources availability, Data Preparation, Feature selection, Evaluating models, tuning the model and documentations. […]

This research investigates how a neighbourhood in London, Ontario may be designed to be both sustainable and resilient, where “resilient” means capable of dealing with future shocks and stresses. One major future shock/stress will be climate change impacts, such as extreme temperature or precipitation. This research will also conduct preliminary energy modelling of a simplified […]

The Social Innovation Academy will be working with a network of Mitacs interns to support the financial analysis needs of social purpose organizations across Canada. These needs may include (but are not limited to): research of potential sectors; impact measurement; and financial modelling. In addition, interns will provide marketing, research, and financial analysis for social […]

Information and data are more accessible and abundant than ever before, but this presents challenges in the face of rising misinformation and mistrust in science. Large-scale datasets or “big data” is particularly suited to a set of statistical analyses called dimension reduction techniques that can reduce the complexity of a dataset while preserving its information, […]

Within the green sector in Toronto, the largest cluster is sustainable transportation, which makes up 38% of green jobs, and is the fastest growing cluster in the sector at 4.9% compared to the overall green sector at 3.9% and across all industries in Toronto at 1.9% (5-year average between 2015-2019). As such, in order to […]

Pharos has a data fusion platform for geospatial and spatiotemporal data. This project will extend the platform to cover additional data sources, such as flood risk data, and allow for the on-demand calculation of decision-relevant metrics. This requires an investigation of the underlying data, methods to combine sources, and development of pipelines for efficient automation. […]