Lecture on June 7, 2023(Wed) at Muroran Institute of Technology

Schedule
June 7, 2023(Wed), 16:30-18:30
Venue
R205, Education & Research Building No. 8, Muroran Institute of Technology, Hokkaido, Japan.
Speaker
Kazuo Yamada (President and CEO, softusing Co.,Ltd.)
Title
Human Resource Strategy and Dynamic Capability Development of IT with AI in the DX Era
Abstract
This talk provides insights and a system development viewpoint into acquiring human resource strategy and dynamic capability development for Small and Medium-Sized Software Companies of IT Industry in DX era. Realizing the demand for talent in the IT industry is increasing year after year. To capture the potential market opportunities of “high demand for IT human resource development” that suits individual abilities, we have adopted an improved recruitment strategy by developing a learning management system (LMS). The system developed of AI learning system specialized in programming and reduced the time needed to train personnel to become ready to work.
Contact person
Mianxiong Dong (Muroran Institute of Technology)

(日本語) 講演会のご案内(2023/2/22(Wed) 10:00-12:00 @北海道大学)

講演会のご案内(2023/2/22(Wed) 10:00-12:00 @北海道大学)

下記の通り講演会が開催されますのでご案内いたします．皆様のご参加をお待ちしております．

日時
2023年2月22日(水) 10:00-12:00
場所
北海道大学 情報科学研究院11F 会議室
講師
米山 拓応 氏(セイコーエプソン)
演題
プロジェクタ関連技術の最新動向
概要
近年、プロジェクタを目にする機会は一昔前と比較して一段と増えてきた。ビジネスシーンにおけるプレゼンテーションや家庭でのホームシネマの他にも、家庭用TVの置き換えやサイネージ、デジタルアートといった用途の広がりを見せ、それに伴い顧客ニーズも変化してきている。今回はプロジェクタの種類や構造を光学的な視点で基本原理から解説し、最新の技術動向を交えて紹介する。
世話人
北海道大学情報科学研究院メディア創生学研究室 助教 姜 錫 kssrh[atマーク]ist.hokudai.ac.jp

Lecture on Jan 27, 2023(Fri) at Muroran Institute of Technology

Schedule
Jan 27, 2023(Fri), 16:15-17:45
Venue
R205, Education & Research Building No. 8, Muroran Institute of Technology, Hokkaido, Japan.
Speaker
Prof. Xin Zhu (The University of Aizu)
Title
AI medicine: history, present and future
Abstract
Recent progress in deep learning has seen the implementation of AI in medicine. In this presentation, the history, present and future of AI medicine will be introduced and explained, especially in the analysis of medical images, signals and information. Some pitfalls of AI medicine will also be introduced and should be avoided in future research. Some hot topics like attention, explainable AI, edging computing and federal learning will be mentioned in the end.
Contact person
Prof. Mianxiong Dong (Muroran Institute of Technology)