AOSHIMA LABORATORY
Leading the world in new research in statistics
for High-Dimensional Data Analysis
RECENT AWARDS
AWARDS FOR SCIENCE AND TECHNOLOGY 2020 (RESEARCH CATEGORY):
THE COMMENDATION FOR SCIENCE AND TECHNOLOGY BY THE MINISTER OF EDUCATION, CULTURE, SPORTS, SCIENCE AND TECHNOLOGY
Professor Makoto Aoshima
April 7, 2020
"Research on High-Dimensional Statistical Analysis for Understanding High-Dimensional Phenomena"
2022 BEST FACULTY MEMBER AWARD (RESEARCH):
UNIVERSITY OF TSUKUBA
Associate Professor Kazuyoshi Yata
February 20, 2023
2022 OGAWA PRIZE:
JAPAN STATISTICAL SOCIETY
Junior Associate Professor Aki Ishii
September 6, 2022
2021 BEST FACULTY MEMBER AWARD (RESEARCH):
UNIVERSITY OF TSUKUBA
Professor Makoto Aoshima
February 7, 2022
ABRAHAM WALD PRIZE IN SEQUENTIAL ANALYSIS 2019
Professor Makoto Aoshima, Associate Professor Kazuyoshi Yata, Yugo Nakayama
June 19, 2019
TOKYO ACADEMY OF PHYSICS AWARD:
TOKYO UNIVERSITY OF SCIENCE
Professor Makoto Aoshima
June 17, 2019
2017 BEST FACULTY MEMBER AWARD (RESEARCH):
UNIVERSITY OF TSUKUBA
Professor Makoto Aoshima
February 19, 2018
2017 HONORED EVALUATOR AWARD:
JAPAN SOCIETY FOR THE PROMOTION OF SCIENCE
Professor Makoto Aoshima
September 29, 2017
2017 JAPAN STATISTICAL SOCIETY AWARD
Professor Makoto Aoshima
July 25, 2017
2013 HONORED EVALUATOR AWARD:
JAPAN SOCIETY FOR THE PROMOTION OF SCIENCE
Professor Makoto Aoshima
October 31, 2013
2013 YOUNG RESEARCHER AWARD IN UNIVERSITY OF TSUKUBA
Assistant Professor Kazuyoshi Yata
October 24, 2013
2012 BEST FACULTY MEMBER AWARD (RESEARCH):
UNIVERSITY OF TSUKUBA
Professor Makoto Aoshima
March 6, 2013
2012 JAPAN STATISTICAL SOCIETY RESEARCH ACHIEVEMENT AWARD
Professor Makoto Aoshima, Assistant Professor Kazuyoshi Yata
September 10, 2012
ABRAHAM WALD PRIZE IN SEQUENTIAL ANALYSIS 2012
Professor Makoto Aoshima, Assistant Professor Kazuyoshi Yata
June 13, 2012
JAPANESE JOINT STATISTICAL MEETING 2024
OUTSTANDING PRESENTATION AWARD
Tetsuya Umino
September 5, 2024
- Title:
- Sparse estimation of high-dimensional features without regularization parameters
2020 DEAN AWARD, GRADUATE SCHOOL OF PURE AND APPLIED SCIENCES: UNIVERSITY OF TSUKUBA
Yugo Nakayama
March 25, 2020
2020 MEIKEI AWARD: UNIVERSITY OF TSUKUBA
Kento Egashira
March 25, 2020
THE JAPAN STATISTICAL SOCIETY SPRING MEETING
OUTSTANDING POSTER PRESENTATION AWARD
Yugo Nakayama
March 10, 2019
- Title:
- Clustering for high-dimensional data by kernel PCA with the Gaussian kernel
TSUKUBA GLOBAL SCIENCE WEEK 2018
INTERDISCIPLINARY WORKSHOP ON SCIENCE AND PATENTS
IWP MEMORIAL AWARD
Yugo Nakayama
September 21, 2018
- Title:
- Robust classification of imbalanced data in high dimension, low sample size context
THE JAPAN STATISTICAL SOCIETY SPRING MEETING
OUTSTANDING POSTER PRESENTATION AWARD
Yugo Nakayama
March 4, 2018
- Title:
- SVM with Gaussian kernel: Bias correction and tuning parameter for high-dimensional data
2016 MEIKEI AWARD: UNIVERSITY OF TSUKUBA
Yugo Nakayama
March 24, 2017
2016 DEAN AWARD, GRADUATE SCHOOL OF PURE AND APPLIED SCIENCES: UNIVERSITY OF TSUKUBA
Yugo Nakayama
March 24, 2017
THE 15TH JAPANESE JOINT STATISTICAL MEETING
OUTSTANDING PRESENTATION AWARD
Yugo Nakayama
September 6, 2016
- Title:
- Asymptotic Properties and Bias Correction of Support Vector Machine
in High-Dimension, Low-Sample-Size Context
THE JAPAN STATISTICAL SOCIETY SPRING MEETING
OUTSTANDING POSTER PRESENTATION AWARD
Aki Ishii
March 8, 2014
- Title:
- Geometric Representations of High-Dimension, Low Sample Size Data:
Statistical Inference on Eigenvalues, Eigenvectors and Their Contribution Ratio
2013 DEAN AWARD, GRADUATE SCHOOL OF PURE AND APPLIED SCIENCES: UNIVERSITY OF TSUKUBA
Aki Ishii
March 4, 2014
THE JAPAN STATISTICAL SOCIETY SPRING MEETING
OUTSTANDING STUDENT POSTER PRESENTATION AWARD
Kazuyoshi Kurishita
March 4, 2012
- Title:
- Cluster Analysis for High-Dimensional Data by Using the Second Moments
THE JAPAN STATISTICAL SOCIETY SPRING MEETING
OUTSTANDING STUDENT POSTER PRESENTATION AWARD
Yuko Kobayashi
March 6, 2011
- Title:
- Robust and High-Speed Model Selection and Clustering for Contaminated Multivariate Data