University of GlasgowのFahim Kawsar教授が当研究室を訪問され，特別講義をしていただきました．
UKグラスゴー大学のFahim Kawsar先生に，慶應グローバルファカルティプログラムの元，政策･メディア研究科の特別教授(国際)として来日していただき，22日(木)には特別講義を行っていただきました．モバイル/ウェアラブルコンピューティングシステムの研究者として活躍され，IEEE Pervasiveの編集長を務めながら，さらにOmniBuds, IchiZeroといった複数のスタートアップを自ら立ち上げfounder, CTO, advisorとして実社会にデプロイしているKawsar先生の，シャープかつバイタリティあるお仕事に，自分としても感銘を受けました．
Fahim Kawsar教授には，慶應義塾大学大学院政策・メディア研究科の特別招聘教授（国際）（Guest Professor (Global)）に就任いただいています．特別講義の情報は以下のとおりです．
Edge AI at Human Scale
Fahim Kawsar（School of Computing Science, University of Glasgow・Graduate School of Media and Governance, Keio University）Abstract:
What if your ears could become a window into your cardiovascular health? What if a child’s first encounter with AI didn’t come from YouTube, but from building and training their own models in the classroom? What if a $10 camera could detect industrial faults in milliseconds—without touching the cloud? This talk explores the reality of Edge AI at human scale: intelligent systems engineered to operate entirely on-device, under real-world constraints. OmniBuds is a clinically driven, ear-worn digital health platform that enables continuous, passive, and context-aware monitoring of hypertension and respiratory health, using multimodal sensing and microcontroller-optimised inference. Bella is a foundational AI education platform that introduces computing and artificial intelligence to children aged 6–12 through interactive, explainable, and offline model training—crafted specifically for safety, engagement, and accessibility in diverse classroom environments. CaaS is an edge-native camera platform for industrial automation, delivering low-latency, task-specific visual intelligence on low-power microcontrollers, without relying on external compute or connectivity. These platforms required targeted innovations in few-shot learning, self-supervised techniques, compiler-level optimisation, and event-driven inference—all while balancing efficiency, interpretability, and real-world resilience. I will conclude by outlining core principles for translating AI research into deployable, trustworthy, and domain-specific systems that scale—advancing the vision of pervasive intelligence across health, education, and industry.
