Developing AI and large language model frameworks for mental health, with a focus on responsible, fair, and context-aware recommendations. Funded by the Connected Minds CFREF Scholarship and collaborating with Vector Institute.

Designed and evaluated LLM-based methods to investigate mental health problems. Worked on fair, transparent, and context-aware AI recommendations using Python, Llama 3, AWS, and chain-of-thought prompting.

Built LLM systems to classify and predict youth mental health issues and reduce counselors’ administrative burden. Developed high-performing models that surfaced new insights from counseling conversations using chain-of-thought reasoning.

Led a collaborative project with Ontario Tech University on leveraging AI to detect, predict, and manage neuropsychiatric symptoms in people with dementia. Drove REB approval and deployment of an agitation detection system in a dementia care unit.

Research trainee at KITE Research Institute and IATSL lab on multimodal human activity recognition from wearable inertial sensors. Investigated features and ML models to detect aggressive behavior, achieving performance beyond state-of-the-art baselines.

Engineered NLP pipelines using named entity recognition to extract grocery store data and power a price-tracking product currently used in production. Improved and optimized the BetterCart platform using Python, SQL, supervised learning, and NER models.

Contributed to multiple AI projects including real-time ECG risk prediction with Apache Kafka streaming, real-time video-based traffic analysis, and deep learning models for COVID-19 prediction from X-ray images that outperformed prior work.

Thesis on Leveraging Artificial Intelligence and wearable sensors to predict agitation and aggression in people with dementia.

Thesis on Multimodal Human Activity Recognition from Wearable Sensors using Machine Learning and a Feature Selection Approach. Graduated with GPA 3.96/4.0 (Excellent with Honor).

Graduation project: PortaCare: IoT-Based Portable Intensive Care Unit, a low-cost prototype for a portable ICU. The project received two national funds. Graduated with GPA 3.95/4.0 (Excellent with Honor).