Yu Naknao
Yu Naknao
Software Engineer
Software Engineer
Email: yu.nakano6 [at] gmail.com
LinkedIn: www.linkedin.com/in/yu-nakano
Yu Nakano is a software engineer in Japan involved in information retrieval systems. He was Ph.D. student majoring in computer science at the University of Tsukuba. His research theme was Information Retrieval & Recommendation, and he was mainly working on algorithms for searching tabular data using keywords and text as queries. He was also working on the application of data mining techniques to academic papers and trajectory data.
Dataset Retrieval for Long Text Queries (DEIM 2021, IPSJ-TOD 2021)
Numerical Cell Retrieval / Alignment (DEIM 2022, DBSJ DDS 2023, DEIM 2023)
Ad-hoc Dataset Retrieval, Ad-hoc (Web) Table Retrieval (NTCIR-16)
Table QA
Data Mining for Scholarly Data
Visualization utilizing Co-citations (DEIM 2016, ICADL 2016)
Tagging Terms in Controlled Vocabulary using Survey Articles (WebDB Forum 2017)
Discovering Novel Classification Papers using Outlier Detection
Turnover Prediction using Taxi Probe Data (34th JSCS Symposium)
Doctoral Programs (Informatics) in Comprehensive Human Sciences, University of Tsukuba
Theme: Fact Checking by Open Data using Data Citation
Supervisor: Assoc. Prof. Makoto P. Kato, Prof. Atsuyuki Morishima
Graduate School of Informatics, Kyoto University
Master's Thesis: Tagging Scholarly Papers Using Taxonomy of Survey Articles
Supervisor: Prof. Masatoshi Yoshikawa
Computer Science Course, School of Informatics and Mathematical Science, Faculty of Engineering, Kyoto University
Thesis: Presentation of Paper-Relation Graph Utilizing Co-Citation Information (in Japanese)
Supervisor: Prof. Masatoshi Yoshikawa
Theme: Development of Data Search Engine for Open Data
Implementations and Evaluations of Unsupervised Search Result Diversification Methods
Developing a library providing high-performance and easy-to-use data analysis tools for Python, C++, JavaScript (TypeScript)
Solving data science problems for business purpose
Time-series forecast using state-space model
Optimizing by deep reinforcement learning
Yu Nakano, Makoto P. Kato. Leveraging Query and Document Fields for Cited Dataset Retrieval (in Japanese). IPSJ Transactions on Databases (IPSJ-TOD), Vol.14(4), pp.49-60, 2021.
Yu Nakano, Toshiyuki Shimizu, Masatoshi Yoshikawa. A Visualization of Relationships Among Papers Using Citation and Co-citation Information. In Proceedings of the 18th International Conference on Asia-Pacific Digital Libraries (ICADL2016), Tsukuba, Japan, December 7-9, 2016. Link
Yu Nakano, Makoto P. Kato. A Dataset for Numerical Cell Alignment for Cited Statistical Dataset (in Japanese). In Proceedings of the 14th Forum on Data Engineering and Information Management (DEIM2022), Online, 2022.
Yu Nakano, Makoto P. Kato. Statistical Dataset Retrieval for Mis-Citation Verification (in Japanese). In Proceedings of the 13th Forum on Data Engineering and Information Management (DEIM2021), Online, 2021.
Yu Nakano, Yuki Fujimoto Kaito Takahashi, Employee Turnover Prediction using Taxi Probe Data (in Japanese). In Proceedings of the 34th Symposium of the Japanese Society of Computational Statistics, Online, 2020.
Yu Nakano, Toshiyuki Shimizu, Masatoshi Yoshikawa. A Study of Tagging Scholarly Papers Using Taxonomy of Survey Articles (in Japanese). In Proceedings of WebDB Forum 2017, Tokyo, Japan, 2017.
Yu Nakano, Toshiyuki Shimizu, Masatoshi Yoshikawa. Presentation of Paper-Relation Graph Utilizing Co-Citation Information (in Japanese). In Proceedings of the 8th Forum on Data Engineering and Information Management (DEIM2016), Fukuoka, Japan, 2016.
Best Interactive Runner-up Award: DEIM 2022, May 2022. (Top 11/127=8.7%)
Student Presentation Award: DEIM 2022, March 2022.
Sponsor Award (NEC Inc. Award): DEIM 2022, March 2022.
Student Presentation Award: DEIM 2021, March 2021.
Best Presentation Runner-up Award: Team MSI-API. In JASMAC Data Analysis Competition 2019, Study Group of Japanese Society of Computational Statistics (JSCS), February 2020.
JST SPRING : Support for Pioneering Research Initiated by the Next Generation
Duration: 1.5 years (2021/10-2023/03)
Theme: Supporting Statements Containing Numerical Information with Statistical Datasets
750,000 yen
Grant Number: JPMJSP2124
Second semester of 2017: Computer Science Laboratory and Exercise 4 (Teaching Assistant)
Course for undergraduate students at Kyoto University.
First semester of 2016: Databases (Teaching Assistant)
Introductory course on database theory and database management systems for undergraduate students at Kyoto University.
Second semester of 2016: Computer Science Laboratory and Exercise 4 (Teaching Assistant)
Course for undergraduate students at Kyoto University.
2017/08: SIGIR 2017 Student Volunteer
ACM
Database Society of Japan
Information Processing Society of Japan
The Association for Natural Language Processing
Tokyo ACM SIGIR Chapter
Programming languages: Python, C, C++, Nim.
OS: MacOS, Linux (esp. Ubuntu, CentOS7)
Natural languages: Japanese (native), English (TOEIC score: 845 (as of 2015)).
I often participate in competitive programming contests, such as AtCoder, TopCoder and Codeforces. I have participated in many on-site finals in Japan (CODE RUNNER 2015, Code Festival 2015-2016, DISCO presents ディスカバリーチャンネル コードコンテスト2016, Code Thanks Festival 2017, (第一回)全国統一プログラミング王, 第4回 RECRUIT 日本橋ハーフマラソン). I was an organizer of Kyoto University Programming Contest in 2016-2017.