The City of Toronto wishes to assemble a comprehensive set of available historical neighbourhood-scale Census data. While a wealth of historical Canadian Census data exist in the public domain, it is largely inaccessible to users who lack specialized training and skills due fragmentation of data holdings and their storage in different formats. Making use of […]

The abundance of electronic health record (EHR) data has accelerated the adoption of data-driven methods to automate various tasks ranging from patient care to resource management in hospitals around the world. The use of specific types of data such as X-ray images, doctor’s note and others have been used individually to implement machine learning models […]

The proposed research would use AI to create an application called Barrelfish that will help in the recruitment process. The project focuses on lowering the time it takes to discover data, screen applicants, and retrieve recommendations. Clients will be able to select employees based on their skills, abilities, and experiences, as well as conduct virtual […]

With the ultimate goal of enhancing Nexxt Intelligence’s market research SaaS platform, inca, this project will create a robust, scalable algorithm for clustering consumer utterances into groups which are useful to ad-hoc market research objectives, and interpretable via natural language descriptions to market researchers. Due to the multifaceted and nuanced nature of consumer opinions and […]

The proposed Creativity and Sustainability post-doctoral fellowship will be situated at Mass Culture (MC), and executed in cooperation with University of Toronto Scarborough’s (UTSC) Urban Just Transitions (UJT). Over the years, MC and the scholars involved in UJT have experimented with various forms of community-engaged methods in order to generate impactful research that will inform […]

Computer Games are one of the key use cases of graphics cards of AMD. To ensure highest quality and performance, extensive testing of graphics hardware and software is required. However, much of this gameplay testing is manual and requires significant efforts due to varying styles in games and their versions. In this context, an open […]

XLScout uses Natural Language Processing (NLP), Machine Learning (ML), and Innovation/Scientific principles to deliver actionable intelligence and accelerate innovation by analyzing large patent and research databases. The company is eliminating the pain of manually going through document and quickly providing relevant information to support data-driven strategic decisions. Presently XLScout hosts a data vault of over […]

Recent advancements in deep reinforcement learning (RL) have enabled incredible breakthroughs on a wide variety of problems in which computer systems are required to learn through interacting with the environment with no or minimal human intervention. An example of this is DeepMind’s AlphaGo agent, which taught itself to play Go at a superhuman performance. Deep […]

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 over-arching goal of the project is to explore the use of several recently developed self-supervised image representation learning methods in an attempt to improve performance across several biologically relevant benchmarking tasks at Recursion. At recursion, deep-learning based models are used to generate feature embeddings for our imaging data and these embeddings to generate downstream […]

Regulatory agencies publish several documents that outline the approval process of drugs. These contain valuable information on a drug’s safety, efficacy, etc. along with the feedback of reviewers from the agencies. Current technologies apply machine learning techniques to extract and categorize the unstructured text found in these documents. However, it does not accurately capture information […]

Physical activity is a crucial part of cardiovascular disease and prevention. Some of the most important clinical measurements relate to how effectively the body is able to consume and use oxygen to fuel muscles. However, these clinical measurements require complex technologies that make it only feasible in a laboratory environment. New technologies will be needed […]