Talks and Presentations
I regularly share my work at conferences, symposia, and academic workshops focused on AI in medicine, neuroscience, and higher education. My talks emphasize both the technical and pedagogical dimensions of AI—how new computational tools can expand understanding, enhance transparency, and make learning more reflective and inclusive.
2025
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Society for Teaching and Learning in Higher Education (STLHE) Annual Conference
Saskatoon, SK, Canada — June 2025
Title: Leveraging AI for Automated Short-Answer Grading: An Educational Theory-Guided Approach in Medical Education
Presented on integrating large-language-model assessment systems with educational theory to improve validity, reliability, and feedback design in medical education. -
Frontiers in NeuroAI — Kempner Institute Symposium
Boston, MA, USA — June 2025
Poster: Ken Utilization Layer: Hebbian Replay Within a Student’s Ken for Adaptive Knowledge Tracing
Highlighted biologically inspired memory architectures for modeling learning progression and cognitive replay in knowledge-tracing systems. -
Curriculum Fellows Program Workshop — Harvard Medical School
Boston, MA, USA — March 2025
Title: Scientific Writing and Literature Reviews with LLMs
Led a workshop on how large language models can support structured academic writing, research synthesis, and critical evaluation while maintaining scholarly integrity.
2024
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Medical Education Day — Harvard Medical School
Boston, MA, USA — October 2024
Poster: Development of a Generative Artificial Intelligence Grading and Learning Tool
Presented a generative feedback platform for formative assessment, designed to improve feedback quality and efficiency in graduate-level courses. -
International Workshop on Breast Imaging (IWBI 2024)
Chicago, IL, USA — June 2024
Poster: Accurate Estimation of Density and Background Parenchymal Enhancement in Breast MRI Using Deep Regression and Transformers
Introduced transformer-based regression methods for quantitative breast MRI analysis to improve reproducibility and interpretability in imaging biomarkers.
2023
- Imaging Network of Ontario (ImNO) Annual Meeting
London, ON, Canada — February 2023
Poster: Background Parenchymal Enhancement Estimation on DCE Breast MRI Using a Siamese Network
Presented a deep learning framework leveraging paired contrast and non-contrast MRI to improve background parenchymal enhancement estimation.
2021
- Machine Learning in Medical Imaging Consortium (MaLMIC) — Breast Cancer
Ontario, Canada — November 2021
Presentation: Tissue Features in Breast Magnetic Resonance Imaging and Risk of Breast Cancer
Discussed texture and morphometric biomarkers in MRI for breast cancer risk assessment.
2020
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ISMRM & SMRT Virtual Conference and Exhibition
Sydney, Australia — August 2020
Presentation: Data Augmentation with Conditional Generative Adversarial Networks for Improved Medical Image Segmentation
Showcased how GAN-based augmentation improves segmentation performance under limited data conditions. -
International Workshop on Breast Imaging (IWBI 2020)
Leuven, Belgium — July 2020
Presentation: Domain Adapted Breast Tissue Segmentation in Magnetic Resonance Imaging
Presented methods for domain adaptation to harmonize models across multi-site MRI datasets.
2019
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AMMCS 2019 International Conference
Kitchener-Waterloo, Canada — August 2019
Presentation: Breast Cancer Risk Prediction Using Magnetic Resonance Imaging in High-Risk Women -
Imaging Network of Ontario (ImNO) Annual Meeting
London, ON, Canada — March 2019
Presentation: Tissue Segmentation in Multi-Weighted Breast MRI Using Deep Learning U-Net
2018
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ISMRM Workshop on Breast MRI
Las Vegas, NV, USA — September 2018
Presentation: Tissue Segmentation in Multi-Weighted Breast MRI Using Deep Learning U-Net -
CAIMS Annual Conference
Toronto, ON, Canada — May 2018
Presentation: Segmentation of Multiple Sclerosis Lesions Using Dictionary Learning in Feature Space -
Imaging Network of Ontario (ImNO) Conference
Toronto, ON, Canada — March 2018
Poster: Segmentation of Multiple Sclerosis Lesions Using Dictionary Learning in Feature Space -
James Lepock Memorial Symposium
Toronto, ON, Canada — February 2018
Poster: Segmentation of Multiple Sclerosis Lesions Using Dictionary Learning in Feature Space
2017
- TEDxUofT Salon: Connect and Converge
Toronto, ON, Canada — September 2017
Presentation: Detecting Multiple Sclerosis Using Machine Learning
Watch the talk on YouTube · Event page
💬 Across these venues, my goal has been to translate technical research in AI and medical imaging into conversations about learning, transparency, and responsible innovation in education and healthcare.