{"id":32969,"date":"2025-12-02T19:17:15","date_gmt":"2025-12-02T10:17:15","guid":{"rendered":"https:\/\/www.waseda.jp\/fsci\/gips\/?p=32969"},"modified":"2025-12-02T19:20:11","modified_gmt":"2025-12-02T10:20:11","slug":"welcome-to-kameoka-lab-2-2-2-2-3-2-2-2-2-2-2-2-2-4-2-2-2-2-2","status":"publish","type":"post","link":"https:\/\/www.waseda.jp\/fsci\/gips\/news-en\/2025\/12\/02\/32969\/","title":{"rendered":"Furuzuki Lab"},"content":{"rendered":"

Welcome to Furuzuki Lab!<\/h1>\n

Name: QIAO, Li<\/strong>
Program & Year : Doctoral program, 1st-year<\/strong><\/p>\n


\n\u2713\u65e5\u672c\u8a9e\u7248\u306f\u3053\u3061\u3089\/Click here for the Japanese version<\/a>
\n<\/strong><\/p>\n

Laboratory Introduction<\/h3>\n

Artificial intelligence is rapidly permeating all areas of society, demonstrating great potential in fields such as sports, industry, culture, and even art creation. In line with this trend, the Furuzuki Laboratory has long been devoted to the study of core algorithms in AI, focusing on advancing machine learning theory, optimizing deep models, and exploring intelligent systems in various applications. In recent years, with the rapid development of large-scale pre-trained models, especially large language models (LLMs), the laboratory has further expanded its research directions.<\/p>\n

Current studies actively explore fine-tuning methods, knowledge transfer mechanisms, and the internal principles of representation learning, aiming to improve performance and promote innovative applications in multimodal understanding, reasoning, and generation.<\/p>\n

The main research areas of the Furuzuki Laboratory include reinforcement learning, kernel machines, bioinformatics, generative models, and fine-tuning and representation learning of pre-trained models. The lab is committed to combining theoretical research with practical applications to enhance the real-world impact of AI technologies in industry and society.<\/p>\n

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Weekly Seminar<\/p><\/div>\n

Research Environment and Facilities<\/h3>\n

The laboratory is equipped with more than ten high-performance CPU and GPU servers, providing each member with sufficient computational resources and research equipment. These facilities support a wide range of studies, including deep learning, reinforcement learning, large language model fine-tuning, and large-scale data analysis.<\/p>\n

Research Life<\/h3>\n

Weekly seminars are held every Wednesday. Members are divided into four groups that take turns presenting and discussing, allowing each member to receive individual guidance from Professor Furuzuki at least once a month. Seminar topics cover research progress, paper sharing, and open discussions. The lab maintains an active and open atmosphere where everyone\u2019s ideas and opinions are respected. Professor Furuzuki also cares deeply about students\u2019 well-being, values individual development, and encourages a healthy balance between study and personal life.<\/p>\n

The Furuzuki Laboratory warmly welcomes researchers and students passionate about machine learning, deep learning, and pre-trained models to join us in shaping the new era of Artificial intelligence.<\/p>\n

\"Laboratory

Laboratory Members<\/p><\/div>\n

 <\/p>\n

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Diner Party<\/p><\/div>\n

 <\/p>\n","protected":false},"excerpt":{"rendered":"

Welcome to Furuzuki Lab! Name: QIAO, LiProgram & Year : Doctoral program, 1st-year \u2713\u65e5\u672c\u8a9e\u7248\u306f\u3053\u3061\u3089\/Click here fo […]<\/p>\n","protected":false},"author":4,"featured_media":32961,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":""},"categories":[95],"tags":[94,76],"class_list":["post-32969","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-news-en","tag-general-en","tag-outreach-en"],"acf":[],"_links":{"self":[{"href":"https:\/\/www.waseda.jp\/fsci\/gips\/wp-json\/wp\/v2\/posts\/32969","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.waseda.jp\/fsci\/gips\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.waseda.jp\/fsci\/gips\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.waseda.jp\/fsci\/gips\/wp-json\/wp\/v2\/users\/4"}],"replies":[{"embeddable":true,"href":"https:\/\/www.waseda.jp\/fsci\/gips\/wp-json\/wp\/v2\/comments?post=32969"}],"version-history":[{"count":2,"href":"https:\/\/www.waseda.jp\/fsci\/gips\/wp-json\/wp\/v2\/posts\/32969\/revisions"}],"predecessor-version":[{"id":32976,"href":"https:\/\/www.waseda.jp\/fsci\/gips\/wp-json\/wp\/v2\/posts\/32969\/revisions\/32976"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.waseda.jp\/fsci\/gips\/wp-json\/wp\/v2\/media\/32961"}],"wp:attachment":[{"href":"https:\/\/www.waseda.jp\/fsci\/gips\/wp-json\/wp\/v2\/media?parent=32969"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.waseda.jp\/fsci\/gips\/wp-json\/wp\/v2\/categories?post=32969"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.waseda.jp\/fsci\/gips\/wp-json\/wp\/v2\/tags?post=32969"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}