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IJCAI in Canada: 90-second pitches from the next generation of AI researchers
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为即将于2025年8月在蒙特利尔举行的第34届国际人工智能联合会议(IJCAI 2025),当地组委会发起活动,通过90秒视频系列展示加拿大下一代AI研究者。视频介绍了多位学生及其AI研究,涵盖牙科AI辅助设计、AI生成音乐、大型语言模型安全、AI化学应用、AI模型可解释性、药物发现及AI普及等领域,展现加拿大AI研究的多元创新。

🔬 Imane Chafi博士研究AI辅助牙科修复设计,通过AI模型提升牙冠制备的效率和精度,为牙科诊疗提供智能化支持。

🎶 Liliane-Caroline Demers运用神经符号方法结合机器学习与约束规划,研究AI生成音乐,创造出风格与结构兼具的音乐作品。

🛡️ Sophia Jit博士致力于将伦理规范转化为可测试要求,通过约束条件提升大型语言模型的安全性和可信度,保障AI伦理。

🧪 Marta Skreta博士将AI应用于化学领域,设计兼具物理真实性和特定功能的分子,推动AI在材料科学中的应用。

🧐 Vitória Barin Pacela博士研究数据中隐藏因素的解耦与识别,提升AI模型的可解释性和鲁棒性,增强模型透明度。

🧬 David Saikali结合机器学习与约束规划优化序列模型,通过推理时结构规则约束提升药物发现的效率,无需重新训练。

👩‍🏫 Aidan Taha推动AI安全知识普及,致力于让先进AI概念更易于公众理解,促进AI知识的广泛传播。

🌐 Aidan Taha推动AI安全知识普及,致力于让先进AI概念更易于公众理解,促进AI知识的广泛传播。

Ahead of the 34th International Joint Conference on Artificial Intelligence (IJCAI 2025), which will take place in Montréal, Canada, from 16 to 22 August 2025, the Local Arrangements Committee has launched a campaign to showcase the next generation of AI researchers in Canada.

Through a series of 90-second videos, we meet students based in Canada and find out a bit about their work. You can watch the videos below:


Imane Chafi, PhD candidate at the Polytechnique Montréal, uses AI models to support dentists in designing dental preparations for dental crowns more efficiently and accurately.


Liliane-Caroline Demers, Student Communication Coordinator for IJCAI 2025 Local Arrangement Committee and a recent master’s graduate from Polytechnique Montréal, researches AI-generated music. Using a neurosymbolic approach that combines machine learning with constraint programming at inference time, she creates music that is both stylistically authentic and structurally coherent.


Sophia Jit, PhD candidate at the University of Toronto and Polytechnique Montréal, translates ethical and social norms into testable requirements to make large language models safer and more trustworthy.


Marta Skreta, PhD candidate at the University of Toronto and Vector Institute (incoming post-doc at the University of Montreal and Mila) applies AI to Chemistry, designing molecules that are both physically accurate and tailored to specific functions.


Vitória Barin Pacela, PhD candidate at the University of Montreal and Mila – Quebec Artificial Intelligence Institute, studies how to disentangle and identify hidden factors in data to make AI models more interpretable and robust.


David Saikali, a graduate of the Polytechnique Montréal, combines machine learning with constraint programming to improve sequence models by enforcing structural rules at inference time—particularly in drug discovery—enabling constraint enforcement without the need for retraining.


Aidan Taha, a pre-university student from Jean-de-Brébeuf College, is driven by a passion for AI safety and works to make advanced AI concepts more accessible to the broader public.


You can find out more about this video series here.

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