Inspired by needs for haptic support of large motions on a surface in applications like embodied conceptual learning, commercial design, and 2D virtual/augmented reality, we at SPIN lab at the University of British Columbia made a ballpoint drive system called Magic Pen [1]. This novel approach circumvents conventional constraints by imposing a new one: motion […]

Recreational cannabis was legalized on Oct 17th, 2018. Internationally, some countries have already legalized or are going to legalize the recreational/medical cannabis products. Unfortunately, there are not much data available for stakeholders to make decisions in a data-driven way. However, the government, industry and community are hungry to obtain statistical data to understand the impact […]

We envision a future where it will be possible to lavish the same attention on individual plants in a large prairie crop farm as one might on those in a backyard garden. As camera sensors shrink in size, and self-driving vehicles continue to improve, such an idea is no longer the realm of science fiction. […]

The layout drawing is the popular format in the Oil & Gas industry to illustrate the design of layouts and the internal equipment. The complex drawings contain primary shapes, indicative lines and textual annotations. So far the expert knowledge is still required to understand, modify and create such documents. The proposed project is to develop […]

The goal of this project that will be conducted in collaboration with Heyday is to create a technology that uses a given messaging platform (e.g. Facebook Messenger, web chat widget) that allows users to communicate easily and smoothly with their preferred brands or retailers. This technology should allow the automation of answers and interaction between […]

The purpose of this project is to investigate self-adaptive forecasting and anomaly prediction algorithms based on deep neural networks (DNNs). DNNs present a compelling technology due to their wide-spread availability through open-source projects (e.g. TensorFlow, MXNet). However, usability of DNNs in scenarios outside of image, speech or text pattern recognition is mostly unproven. This project […]

Deep neural network (DNN) is a class of machine learning algorithms which is inspired by biological neural networks. DNNs are themselves general function approximations, which is the reason they can be applied to almost any machine learning problem. Their applications can be found in visual object recognition in computer vision, translating texts in unsupervised learning, […]

Networks are moving towards being adaptive. This means that automation will be used to replace processes which are today highly manual. This project proposes a development of knowledge in the area of algorithms required to enable adaptive networks. The project will train two PhD students to understand optical networks and devise optimization algorithms in the […]

The project is about removing noise from video signals, for example, those taken by a professional cinema camera. In this project, we propose to develop a commercially capable noise reduction framework based on one of our patents to noise reduction. A commercial noise reduction is required to automatically recognize the type of noise piesent in […]

The project entails the creation of a program that will capture data from building sensors. It will analyze that data and predict future trends based on the data collected over a period of time. It will also graph data from sensors over a period of time. Currently both are done manually, take a significant amount […]

In this project, we will explore novel modeling methods to predict oil prices, based on a combination of machine learning methods with dynamic multiresolution analysis. The objective is to develop a software to better forecast oil prices. Oil is the world’s leading fuel, and its prices have a big impact on the global environment, the […]

Software-defined networking (SDN) technology is an approach to cloud computing that facilitates network management and enables programmatically efficient network configuration in order to improve network performance and monitoring. SDN suggests centralizing network intelligence in one network component by disassociating the forwarding process of network packets (data plane) from the routing process (control plane). The control […]