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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
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    • 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
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    • Former President of IEEE-HKN Mu Beta Chapter
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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
Responsible AI Development: Bias and Fairness

Responsible AI Development: Bias and Fairness

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Last updated on Jun 1, 2025
← The Future of Mental Health in the Age of LLMs, Agentic AI, and Ethical Design. Jul 1, 2025
AI Is Not Your Therapist: Measuring Trust and Reliability in Mental Health LLMs Jan 1, 2025 →

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