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Ingenuity Labs Research Institute

We are an interdisciplinary initiative at Queen’s University focused on combining Artificial Intelligence, Robotics, and Human Machine Interaction to create future intelligent systems and robotic machines that enhance human productivity, safety, performance, and quality of life.


Mental States of Attendees in Meetings

Inefficient meetings cost organizations billions of dollars every year. An important factor that contributes to this problem is a lack of accurate knowledge regarding conversations taking place at meetings as well as an objective analysis of cognitive and emotional states of attendees. Accurate transcription of conversations and analysis of cognitive and emotional states of attendees …


Phone-based object recognition and classification with deep learning

The project aims to develop machine learning models for identification of shoe SKUs. Both standard and deep learning models will be explored and tested on a variety of datasets (both publically available and those belonging to the company). New end-to-end deep learning models will be developed for better accuracy, run-time, and optimization with respect to …

VR equipment in Medical Office

Medical education, artificial intelligence and augmented reality

As a teaching strategy, simulation-based training has been around a long time. From aviation and space flight to the military, from law to policing, simulation has been used to create learning environments that reflect the real world, without putting the learner or other participants at risk.  A multidisciplinary group of faculty and post-doctoral researchers from …


Exploring Knowledge Base Population Technologies in Multiple Modalities

This project will mainly explore streaming multi-modal Knowledge Base Population (KBP) problems by considering both text and images. We expect to propose novel ideas that may help Alibaba’s technical challenges. Specifically, we aim to identify entities using both unstructured text data (e.g., image descriptions) and the corresponding images.  The aim is that, by creating models …

Type on Screen

Electronic Arts Software Bug De-Duplication

The goal of this project is to develop deep-learning based algorithms for identifying near-duplicates in a large collection of bug reports. Project tasks will consist of the following: Providing expert advice on the best deep-learning approaches to use for solving EA’s bug de-duplication problem. Designing, testing, and evaluating deep-learning algorithms to solve the bug deduplication …

Heshan on an Excavator

What Lies Beneath: Material Classification for Autonomous Excavators using Proprioceptive Force Sensing and Machine Learning

By Heshan Fernando, PhD Candidate, Offroad Robotics at Ingenuity Labs Brief description of research: The aim of this research is to develop a novel methodology for classifying excavation materials using only proprioceptive sensor data (e.g., forces, motions, vibrations, etc.) that are acquired from robotic excavators during digging and loading. In this preliminary work, we present …

Michael Fader

Chat with Student Researcher Michael Fader

Check out this video about Master’s student Michael Fader and his work at Ingenuity Labs with Autonomous Vehicles.

Chat with Student Researcher Rohan Bhambhoria

Check out this video about PhD student Rohan Bhambhoria and his work at Ingenuity Labs in developing a legal tool using artificial intelligence. More information about the research project can be found here:

Thomas Sears 2020 Vanier Scholar

Thomas Sears, 2020 Vanier Scholar

Congratulations to Thomas Sears, one of six 2020 Vanier Canada Graduate Scholars at Queen’s University! Thomas is a Ph.D. student in the Department of Electrical and Computer Engineering at Queen’s University, in Kingston, Canada. He is passionate about the exploration of space and connecting people with all things science and technology. He is a member …

Dr. Il-Min Kim – Using Neural Networks as Mathematical Solvers

Check out this video about Ingenuity Labs researcher Dr. Il-Min Kim discussing the use of Neural networks as Mathematical Solvers. Dr. Kim also Director of the Wireless Artificial Intelligence Laboratory (WAI Lab).