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May 21 - Women in AI Meetup

Event artwork for May 21 - Women in AI Meetup

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About this event

What to expect

Online May 21, 2026: Women in AI Meetup brings three expert talks on AI, ML and computer vision, hosted by Montréal AI, Machine Learning and Computer Vision Meetup. This online event features practical insights from researchers and industry practitioners, with time for discussion and Q&A. Date/time listed on the page: May 21, 2026, 9-11 AM Pacific; Online (registration links provided via Zoom). If you’re curious about how cutting-edge AI research translates to real-world systems, this session is for you.

What to expect:

  • Three 40-minute talks covering real-world AI topics, followed by a Q&A
  • A focus on the intersection of AI, ML and computer vision, with practical takeaways for developers and researchers
  • An online format designed for remote participation with accessible registration
  • Networking-style opportunities through a community of Montréal AI, ML and CV enthusiasts

Speakers and talks (as listed on the event page):

  • Beyond Models: LLM-Guided Reinforcement Learning for Real-World Wireless Systems — Fatemeh Lotfi, Ph.D. researcher focused on integrating large language models and reinforcement learning for adaptive wireless control. The talk explores using LLMs as a reasoning layer that guides RL decision-making with domain logic, scenario interpretation, and adaptive constraints. The architecture provides structured advisory signals from the LLM while preserving the RL policy as the final action authority to avoid hallucination-driven failures. Early experiments suggest improved robustness under distribution shifts and complex constraints where standard RL struggles.
  • Responsible and Ethical AI in Healthcare: Building Trustworthy and Inclusive Intelligent Systems — Jahnavi Kachhia, Global Product Owner, AI & ML at Abbott, leading AI initiatives for the FreeStyle Libre platform. The session covers fairness, transparency, accountability and reliability, practical embeddings of Responsible AI in healthcare datasets, model governance, privacy, and regulatory considerations. Speakers share governance frameworks for data privacy and model monitoring to foster clinician trust and patient safety.
  • AI Applications in Drug Repurposing — Madhurima Mondal, PhD candidate at Texas A&M University. The talk highlights drug–target interaction (DTI) prediction and combining data-independent modeling with data-driven learning to identify plausible repurposing candidates, with emphasis on oncology contexts and mechanisms.

Why you should attend:

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