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  • Talks
    • AI for AGITATION: Predicting Behavioural Distress in Dementia Care
    • The Future of Mental Health in the Age of LLMs, Agentic AI, and Ethical Design.
    • Responsible AI Development: Bias and Fairness
    • AI Is Not Your Therapist: Measuring Trust and Reliability in Mental Health LLMs
    • Moderate for a panel discussion in Responsible AI
    • Apache Spark vs Apache Storm: Side-by-Side Comparison
    • Lead without Limits From a woman in STEM
    • Apache Kafka Architecture & Fundamentals Explained
    • Python, Machine learning, and deep learning: A beginner's guide
  • Teaching
    • Instructor @ Guelph University
    • Instructor @ Ontario Tech University
    • Teaching Assistant @ Ontario Tech University
    • Teaching Assistant @ Arab Academy for Science and Technology
  • Awards
    • Connected Minds Postdoctoral Scholarship (CFREF)
    • Ontario Graduate Scholarship (OGS)
    • PhD Entrance Scholarship
    • PhD Best Thesis Award Nomination
    • Canada’s Student Work Placement Program (SWPP) Funding
    • National Prototype Innovation Grant for PortaCare
  • Labs
    • i4Health Research Lab
    • IoT Research Lab
    • IATSL Lab
    • Dr. Frank Rudzicz's Lab
  • Publications
    • Detecting coronavirus from chest X-rays using transfer learning
    • Investigating Multimodal Sensor Features Importance to Detect Agitation in People with Dementia | CCECE 2023
    • A Scoping Review of Algorithmic Equity, Data Diversity, and Inclusive Design in the Transformer Era of Clinical NLP | medRxiv 2025
    • Multimodal Detection of Agitation in People With Dementia in Clinical Settings: Observational Pilot Study | JMIR Aging 2025
    • Not Lost After All: How Cross-Encoder Attribution Challenges Position Bias Assumptions in LLM Summarization | EMNLP 2025
    • When Can We Trust LLMs in Mental Health? Large-scale Benchmarks for Reliable LLM Evaluation
    • Position: Beyond Assistance—Reimagining LLMs as Ethical and Adaptive Co-Creators in Mental Health Care | ICML 2025
    • Combining Video-Based Skeletal and Wearable Physiological Data for Early Detection of Agitation in Dementia Using Deep Learning
    • A Real-Time System for Monitoring and Managing Neuropsychiatric Symptoms in Dementia Patients
    • Leveraging self-training and variational autoencoder for agitation detection in people with dementia using wearable sensors
    • Profile of NPS in Neurocognitive Disorders: Sex Differences, and Identifying Targets for Digital Biometrics
    • Artificial intelligence and features investigating to detect neuropsychiatric symptoms in patients with dementia: A pilot study
    • P171: Identifying pre-agitation biometric signature in dementia patients: A feasibility study
    • S13: Technology enabled care for neuropsychiatric symptoms of dementia: implementation at the point of care
    • 12-lead ECG platform for real-time monitoring and early anomaly detection
    • Energy saving on constrained 12-leads real-time ECG monitoring
    • Xbeats: A real-time electrocardiogram monitoring and analysis system
    • 3D-RadViz: Three Dimensional Radial Visualization for Large-Scale Data Visualization
    • ECG real-time monitoring and heart anomaly detection reimagined
    • Sensor Type, Axis, and Position-Based Fusion and Feature Selection for Multimodal Human Daily Activity Recognition in Wearable Body Sensor Networks
    • Daily activity recognition using wearable sensors via machine learning and feature selection
    • Education development employing latest free space optical research papers for undergraduate communication engineering students in class and examination
    • Multimodal human activity recognition from wearable inertial sensors using machine learning
  • Services & Talks
    • Mentor - Women in AI Hackathon 2025
    • Conference Volunteer
    • Conference and Journal Reviewer
    • Former President of IEEE-HKN Mu Beta Chapter
  • Projects
    • Pandas
    • PyTorch
    • scikit-learn
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    • 👩🏼‍🏫 Teach academic courses
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  • Experience
  • CV
  • AI for AGITATION: Predicting Behavioural Distress in Dementia Care
  • The Future of Mental Health in the Age of LLMs, Agentic AI, and Ethical Design.
  • Responsible AI Development: Bias and Fairness
  • AI Is Not Your Therapist: Measuring Trust and Reliability in Mental Health LLMs
  • Moderate for a panel discussion in Responsible AI
  • Apache Spark vs Apache Storm: Side-by-Side Comparison
  • Lead without Limits From a woman in STEM
  • Apache Kafka Architecture & Fundamentals Explained
  • Python, Machine learning, and deep learning: A beginner's guide
Talks
The Future of Mental Health in the Age of LLMs, Agentic AI, and Ethical Design.

The Future of Mental Health in the Age of LLMs, Agentic AI, and Ethical Design.

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Last updated on Jul 1, 2025
← AI for AGITATION: Predicting Behavioural Distress in Dementia Care Sep 23, 2025
Responsible AI Development: Bias and Fairness Jun 1, 2025 →

© 2025 Me. This work is licensed under CC BY NC ND 4.0

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