Research Expo

Thank you all for helping to make Saint Mary’s University’s annual Research Expo such a success! We appreciated you sharing your teams work through booth displays, posters or presentations. This year we had over 200 people attend, making it one of the largest Research Expo events yet. As a community, Expo is a wonderful opportunity to showcase the wide variety of research happening at Saint Mary’s.

Below are some pictures from this years event.

President and Geology studentsTribe Network
Meredith and RazdanCrowd Shot A
Crowd Shot BYigit Aydede Presenting
Jason RhinelanderDavid Chiasson

Springboard Atlantic

A special thanks to Springboard Atlantic for their involvement and contribution towards helping make Research Expo happen! Saint Mary's University is a member of Springboard Atlantic, which is a regional network of offices at most university's and colleges in Atlantic Canada that support researchers interested in collaborating with external partners to mobilize knowledge and protect results where possible.

Here is a copy of the 2024 Final Research Expo Program


Dr. Michael Zhang, Department of Finance, Information Systems and Management Science

Presenter Photo for Michael Zhang

Dr. Michael Zhang is an Associate Professor in the Department of Finance, Information Systems and Management Science at the Sobey School of Business. He is also the Director of the Master of Business Analytics Program.

Dr. Zhang’s research is in Data Analytics in Healthcare Services and Supply Chain Management. He was the Principal Investigator on multi-year project supporting youth with mental health conditions using machine learning and analytics. Additionally, Dr. Zhang has led a project on enhancing Canadian vaccination strategies using machine learning and business analytics. His presentation will cover recent projects involving health data analytics.

Adaptiiv Medical Technologies is a Nova Scotia based healthcare technology company specializing in software that helps clinicians improve radiation treatment accuracy and patient care. Adaptiiv’s software integrates with clinician treatment planning systems and allows for the 3D printing of personalized accessories for external beam radiotherapy or high dose-rate brachytherapy. Adaptiiv solutions improve the quality, efficiency and patient experience during radiation therapy.

Dr. Pawan Lingras, Department of Mathematics and Computing Science

Presenter Photo for Pawan Lingras

Dr. Pawan Lingras is a Professor in the Department of Mathematics and Computing Science. He is also the Director of the Master of Computing and Data Analytics Program. Dr. Lingras is an expert on mining and manipulating data. His areas of interest include Artificial Intelligence, machine learning, big data, wearable technology, image processing, intelligent transportation systems, and optimization using evolutionary algorithms.

Recently, he has been collaborating on a machine learning app that will help family physicians better manage referrals to the pediatric cardiologist. In another collaboration he has partnered with Nova Scotia Health to create a dashboard that helps hospitals better manage their resources. In his presentation, Dr. Lingras will provide an overview of how his expertise have benefited health-based organizations.

Aruna Revolution Health Inc., is a Canadian start-up revolutionising the way menstruators manage menstrual health by creating compostable menstrual products that are made of natural fibres from plant by-products. Aruna aims to reduce menstruators' environmental footprint by replacing existing disposable products and improve user satisfaction by providing an affordable substitute for reusable menstrual items. Aruna provides a cheaper alternative for farmers and food manufacturers to dispose of their waste, diverting it from the landfill, and instead putting it into their proprietary process to sustainably turn into fully compostable menstrual pads

Dr. Majid Taghavi, Department of Finance, Information Systems and Management Science

Presenter Photo for Majid Taghavi

Dr. Majid Taghavi is a Professor in the Department of Finance, information Systems and Management Science. His research areas of interest include healthcare operations and business analytics. Below is an outline of his presentation.

Delayed hospital discharge is a known phenomenon for healthcare providers, especially in countries with an aging population. In Canada, delayed discharge is caused by Alternative Level of Care (ALC) patients. ALC patients are patients who no longer require acute care but cannot be discharged mainly due to a lack of capacity in other healthcare providers such as long-term care facilities. Delayed discharge can cause hospital overcrowding, cancellation of surgeries, access blocks, and many more issues. In his teams research, they use several healthcare databases and machine learning approaches to predict if a patient will end up becoming ALC after admission and to predict their length of hospital stay. They also investigate the risk of readmission for ALC patients and find early predictors of readmission. The results help hospital managers to be more proactive regarding the delayed discharge issue.

Parados Cerebral Solutions Inc.

High-quality physical evaluations typically take thousands of dollars, hours of time, a dedicated space, time-consuming and complicated to set up multi-million-dollar equipment with cameras/sensors/markers, and several subjective specialists. There is currently a serious accessibility issue for clients and movement specialists in the performance, health and education sectors. This leads to trillions of dollars in preventable injuries and issues every year in pro sports teams, blue collar/white collar jobs, older populations, and more.

Parados’s B2B SaaS movement intelligence platform turns any mobile device with a camera into a motion capture device to help large organizations reduce the cost of injuries. It’s quick, simple, remote; anyone can record a video, upload it and in a few seconds our computer vision AI returns both users and specialists with data needed to measure, track, and compare things like mobility, balance, symmetry and explosiveness over time. 

Dr. Yigit Aydede, Department of Economics

Presenter Photo on Yigit Aydede

Dr. Yigit Aydede a professor in Economics. He works on nonparametric methods, machine learning and causal AI.  His presentation will cover some of his recent work in health.

Dr. Aydede was selected to join the NS Covid 19 Research Coalition and has published the teams’ findings on the spread of viral spread in Nova Scotia in Nature/Scientific Reports. Currently, he is collaborating with the NS Microbiology Department to study Lyme disease in the region.  Additionally, he is the co-founder of the Machine Learning Research Portal on Health Care, a platform dedicated to researching healthcare related local challenges such as Cancer, Asthma, 811 Triage using AI applications in partnership with scientists from Saint Mary’s University, Dalhousie University, and other local institutions.  Alongside these engagements with Nova Scotia Health Authority and NHW, his recent research also explores fertility behaviours in Canada and their health implications.

3DBioFibR Inc. produces collagen fibers using their patented dry-spinning technology to recapitulate the biomechanical and biochemical properties of natural collagen structures. With a fully automated manufacturing system, they are the first to produce collagen fibers at commercial scales for a variety of tissue engineering applications, including additives for 3D bioprinting and hydrogels, and cellular scaffolds for 2D and 3D cell and tissue culture.

Dr. Jason Rhinelander, Division of Engineering

Presenter photo for Jason Rhinelander

Dr. Jason Rhinelander is a Professor in the Division of Engineering. An expert in Artificial Intelligence, he focuses his research on applying machine learning and optimization to embedded, real-time development. Below is a brief outline of the topic he will cover in his presentation.

Retrieval-Augmented Generation (RAG) enhances Large Language Models (LLMs) like ChatGPT by integrating domain-specific knowledge from external databases, offering a cost-effective way to customize LLMs. Recent LLMs can handle multi-modal inputs like text, imagery, and audio. These multi-modal LLMs can leverage healthcare data for various applications such as clinical decision support, electronic health record enhancement, medical research assistance, automated client interactions, and health outcome prediction. His research involves applying AI to computer vision, timeseries forecasting, image segmentation, and LLM applications with RAG, which are all highly applicable to healthcare applications.

Emagix is developing AI for preserving vision. Emagix's AI aims to help eye-care specialists determine which patients require vision-preserving treatment.