Innovative Projects Realized

Predicting the bond dissociation enthalpies in lignin-derived molecules using quantum machine learning models

Bond dissociation enthalpy (BDE) is a fundamental chemical property for predicting molecular stability and reactivity. BDEs are crucial for understanding antioxidant efficiency, enzyme catalysis, surface functionalization chemistry, and drug discovery. This project will focus on predicting BDEs for C-O and C-C bond types in lignin-derived molecules, essential for efficient lignin decomposition processes in biofuel production and renewable chemicals. Computational approaches such as density functional theory (DFT) are computationally expensive which limit the size and diversity of BDE dataset for lignin-relevant systems. To address this challenge, we propose an active learning framework combined with Bayesian optimization which iteratively identifies the most informative BDE data points. We will use classical machine learning models to generate high-quality BDE data and minimize the requirements of costly DFT calculations. In addition, we will focus on the potential of quantum models, leveraging properties such as entanglement and superposition. We will develop a “quantum” active learning framework which will enable a more efficient exploration of chemical spaces in lignin-related systems. The use of quantum models will further enhance predictive capabilities by efficiently handling data-scarce scenarios. This work will contribute towards the efficient utilization of biomass for renewable energy applications.

Development of an Augmented Reality Laparoscopic Training System for Gynecological Surgeries

This project aims to create a training system for laparoscopic procedures focused on gynecological surgeries using a 3D-printed torso phantom. The mannequin features apertures for inserting laparoscopic tools (trocars) and a camera, with visible 3D-printed organs inside. The goal is to develop a training module that integrates virtual anatomical models with real-world views using HoloLens 2 augmented reality glasses. These models will assist trainees by overlaying relevant anatomical structures or other virtual models useful for training.

Implementing image-based SSL methods for laparoscopic surgical video data

The proposed MITACS GRA project is part of the Human Surgeome Project at the German Cancer Center, which uses advanced machine learning and deep learning technologies to improve surgical practices. By analyzing large amounts of surgical video data, the project aims to enhance surgical training, skill assessment, and workflow. It will develop systems that provide real-time feedback to surgeons, helping to improve efficiency, safety, and decision-making during surgeries. Ultimately, this project seeks to make surgery safer and more standardized, reduce complications, and improve patient outcomes, making healthcare more efficient and evidence-based.

Gamifying Shakespeare: Theorizing and Designing Game-based Digital Media for Stratford Festival Audience Engagement

The aims of the partner organization are to: bolster audience engagement, i.e., to enhance the experience of those already attending the Stratford Festival; bolster audience attendance, i.e., to draw new crowds to the Stratford Festival; and establish the Festival as a leading digital media creator in the field of professional theatre. With the intern’s focus on enhancing player/audience engagement, the creation of a digital game based upon the partner organizations staged productions (beginning with one in the 2015 season) will allow audiences new ways to connect emotionally and empathically with the partner organization and their work.

ESROP-NUS-Measurement of magnetic field vector by a compact diamond quantum sensor

Measurement of magnetic field vector by a compact diamond quantum sensor

Measuring magnetic field is important for material and device characterization. Although various methods have been developed, challenges persist in accurately measuring local magnetic field vectors. Our lab has been developing a compact diamond quantum sensor to overcome the challenge. The diamond sensor uses nitrogen vacancy centres which have unique spin properties enabling room-temperature optical read-out of spin states. By measuring the magnetic resonances of the spin states, we can extract precise magnetic vector information. Students in this project will learn about the optically detected magnetic resonance (ODMR) system and gain hands-on experience in characterizing and benchmarking the quantum sensor.

Investigating neurescence in dopaminergic neurons of PrknR275W mice

Parkinson’s disease (PD) is a devastating brain disorder accompained by the death of dopamine-producing neurons. Aging is the main risk factor for PD, but early-onset forms also exist and are often linked to mutations in PRKN gene, which encodes for a cellular protein called Parkin. Evidence suggests that these mutations may perturb dopamine neuron function and increase brain inflammation, although the exact mechanisms behind the neuronal death remain unclear. Recent discoveries suggest that “neuronal senescence,” a form of cellular aging, may contribute to age-related brain diseases including PD, but its role in triggering neuronal death is not fully understood. This work aims to study senescence markers in dopamine-containing neurons of a new preclinical mouse model of juvenile parkinsonism that harbors a mutation in PRKN gene. Neuronal senescence could serve as a potential therapeutic target since it can be modulated by senolytic drugs, that have already been developed for other diseases. The findings of this research may lead to new neuroprotective treatments for PD.

Innovative Use of Sidoarjo Mud as Aggregate Replacement in Self-Compacting Geopolymer

The proposed project aims to develop a new, eco-friendly construction material by combining fly ash and Sidoarjo mud to create a self-compacting geopolymer mix. This innovative material will replace traditional aggregates, making it more sustainable and reducing environmental impact. The project leverages the international collaboration to address waste management issues and promote sustainable construction practices. Participating institutions will benefit from this project by advancing research in sustainable construction and gaining access to new, cost-effective materials that can be used in building infrastructure.

Understanding the chemistry of cancer with a smart paper chip

The purpose of the project is to design a paper-based device for the co-detection of nitric oxide (NO) and glucose in a tumor angiogenesis model. By combining paper technologies to electrochemical sensing, we envision that an easy-to-use, smart tumor model can be built. The devices will be tested on co-cultured endothelial and tumor cells, to track the levels of glucose and NO in this model of tumor communication. Pharmacological alterations will be tested as a proof of concept.

AI-Powered Financial Document Intelligence: Transforming SMB & Enterprise Data Management

WizeWerks is developing a cutting-edge AI-powered platform to help businesses streamline financial document processing. Designed for SMBs and enterprises in transportation, logistics, and finance, the platform automates the extraction and organization of key financial data from unstructured documents like invoices and rate confirmations. Using a state-of-the-art Large Language Model (LLM)-agent, it enables users to interact with their data through natural language queries, making insights more accessible without requiring technical expertise. The solution incorporates advanced machine learning, full-stack development, and CI/CD deployment for seamless integration. By reducing manual intervention, minimizing errors, and providing interactive visualizations, this platform enhances operational efficiency and data-driven decision-making. Ultimately, it offers businesses a competitive advantage in managing financial information more effectively.

Exploring Data-Driven Strategies for Enhancing Digital Presence and Market Expansion for Retailers Specializing in Gourmet Gifts and Specialty Foods

Dolce & Gourmando is a distinguished Canadian retailer based in Toronto, celebrated for its premium specialty foods, creative gift baskets, and tailored corporate gifting solutions. Despite a robust market reputation and high-quality product offerings, the company struggles with a digital presence that fails to represent its brand identity and engages potential customers effectively. The current website suffers from an outdated design, poor navigation, low online visibility and reduced customer engagement. Moreover, there is no structured process in place for analyzing market trends or understanding customer preferences, which hinders the company’s ability to make data-driven strategic decisions.
This digital shortfall goes well beyond day-to-day operational issues; it directly impacts Dolce & Gourmando’s growth potential and competitive positioning in a rapidly evolving digital marketplace. To address these challenges, the company will collaborate with the Wearable, Interactive, and Mobile Technologies Access Centre in Health (WIMTACH) to launch a comprehensive digital transformation initiative. This project is designed to revitalize the website through modern design and improved functionality and establish a robust framework for continuous market research and business analysis.
Central to this initiative is a Business Analyst intern, who will be embedded at Dolce & Gourmando’s office to represent the company’s strategic interests. The intern will conduct in-depth primary research through structured interviews and questionnaires with the business owner and employees, and secondary research, including competitor analysis frameworks like SWOT analysis and PESTEL analysis. Dolce & Gourmando is a distinguished Canadian retailer based in Toronto, celebrated for its premium specialty foods, creative gift baskets, and tailored corporate gifting solutions.
Success in this endeavor requires expertise in business analysis, digital marketing, market research, and data analytics. The ideal intern will adeptly apply analytical frameworks and research methodologies to generate robust, data-driven insights that serve as the foundation for strategic

Developing Curricula for Organic Farming Courses

To reflect changing external pressures on organic farmers due to erratic and extreme weather patterns, Organic Alberta is seeing a need to shift our extension work from encouraging farmers to adopt best management practices to creating a strong foundation in systems-based problem solving. Our intern will be creating innovative course structures to provide Albertan farmers with foundational knowledge in science-based systems thinking approaches to solving complex on-farm challenges.

Sensory Perception in Mixed Reality

This research explores the creation and study of a prototype controller with integrated thermal feedback (hot/cold tactile output). This type of device has not previously been explored or understood deeply in academic Human-Computer Interaction or Games User Research Literature. The controller with integrated thermal feedback will be evaluated in a simple 3D game and compared with a conventional controller, key metrics will include the ability of the controller to create an improved player experience, including an increased sence of presence and immersion with the game.