{"id":15198,"date":"2022-09-15T14:58:19","date_gmt":"2022-09-15T05:58:19","guid":{"rendered":"https:\/\/www.waseda.jp\/fire\/sils\/?p=15198"},"modified":"2025-07-02T12:36:33","modified_gmt":"2025-07-02T03:36:33","slug":"introduction-of-new-faculty-member-qi-xin-assistant-professor-without-tenure","status":"publish","type":"post","link":"https:\/\/www.waseda.jp\/fire\/sils\/news\/2022\/09\/15\/15198\/","title":{"rendered":"[Introduction of New Faculty Member] Qi Xin, Assistant Professor"},"content":{"rendered":"

\"\"<\/p>\n

Self-Introduction<\/h3>\n

Hello there, this is Xin QI from SILS. My field of study is Ubiquitous Networking, Artificial Intelligence, and Blockchain. My current lectures are in Intelligence Informatics. My courses include \u201cintroduction to artificial intelligence,\u201d \u201cdata structure and algorithms,\u201d \u201ccomputerized society,\u201d \u201chuman-technology interface,\u201d and various seminars. My goal is to create a friendly learning experience in the world of Intelligence Informatics.<\/p>\n

In my childhood, I was already curious about things around me and was eager to find out how the machinery worked and what the world looked like inside a CRT monitor. I am sure that in such an information explosion age, many people have the same idea. During my college years, I chose computer science as my major and kept network engineering as a personal interest. Eight years ago, I came to Japan and entered Waseda as an international student. I had a meaningful period of time utilizing Waseda as a platform to communicate with the world.<\/p>\n

A student learns, and a graduate explores. I am always happy to have discussions with students and exchange thoughts in my classes.<\/p>\n

\"\"

Figure 1, small-size camera node for the outdoor experiment.<\/em><\/p><\/div>\n

Recent Research Interest<\/h3>\n

My general research interests include next-generation communication systems, A.I., IoT, and Blockchain. I\u2019m currently working on two research topics: person trajectory forecasting and outdoor GPS spoofing detection. Trajectory forecasting needs first to capture and create a person\u2019s location information from a camera. Trajectory data can then be recorded, and machine-learning-based trajectory learning and forecasting can take place. On the other hand, GPS spoofing data learning and analysis need to record large-scale data outdoors and mix it with emulated spoofing data. The target eventually is to let machines tell the difference between real and fake more efficiently than us. In my field of research, there is always a way to solve a problem. What methods are being used depends on the depth and breadth of knowledge one has.<\/p>\n

\"\"

Figure 2, Raspberry-PI-based data collection device and Bluetooth beacons.<\/em><\/p><\/div>\n

 <\/p>\n

Profile<\/h3>\n

XIN QI received his B.E. degree in Computer Science and Technology from Hangzhou Dianzi University, China, in 2013. He then received M.E. and Ph.D. degrees from Waseda University, Japan. in 2016 and 2019, respectively. He was a Research Associate and a Junior Researcher at Waseda University from 2019 to 2021 and from 2021 to August 2022, respectively. Since September 2022, he has been an Assistant Professor with the School of International Liberal Studies, Waseda University.<\/p>\n

His research interests include ICN\/CCN\/3N for next-generation communication systems, A.I., IoT, and Blockchain.<\/p>\n

Researcher data\u00a0 (on WASEDA researchers database)<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"

Self-Introduction Hello there, this is Xin QI from SILS. My field of study is Ubiquitous Networking, Artificia […]<\/p>\n","protected":false},"author":3,"featured_media":15201,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":""},"categories":[95,1],"tags":[115,179,76,93,63,47,110,178],"class_list":["post-15198","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-news-en","category-news","tag-faculty-report-en","tag-facultyintroduction-en","tag-outreach-en","tag-student-en","tag-outreach","tag-student","tag-faculty-report","tag-facultyintroduction"],"acf":[],"_links":{"self":[{"href":"https:\/\/www.waseda.jp\/fire\/sils\/wp-json\/wp\/v2\/posts\/15198","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.waseda.jp\/fire\/sils\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.waseda.jp\/fire\/sils\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.waseda.jp\/fire\/sils\/wp-json\/wp\/v2\/users\/3"}],"replies":[{"embeddable":true,"href":"https:\/\/www.waseda.jp\/fire\/sils\/wp-json\/wp\/v2\/comments?post=15198"}],"version-history":[{"count":2,"href":"https:\/\/www.waseda.jp\/fire\/sils\/wp-json\/wp\/v2\/posts\/15198\/revisions"}],"predecessor-version":[{"id":22940,"href":"https:\/\/www.waseda.jp\/fire\/sils\/wp-json\/wp\/v2\/posts\/15198\/revisions\/22940"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.waseda.jp\/fire\/sils\/wp-json\/wp\/v2\/media\/15201"}],"wp:attachment":[{"href":"https:\/\/www.waseda.jp\/fire\/sils\/wp-json\/wp\/v2\/media?parent=15198"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.waseda.jp\/fire\/sils\/wp-json\/wp\/v2\/categories?post=15198"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.waseda.jp\/fire\/sils\/wp-json\/wp\/v2\/tags?post=15198"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}