Junichiro NIIMI Research Information

Website for Junichiro NIIMI from Graduate School of Economics, Nagoya University


1. Current Affiliation

  • Doctoral Student in Graduate School of Economics, Nagoya University
  • Student in PhD Professional Program

2. Society

  • Japan Institute of Marketing Science; JIMS
  • Japanese Society of Artificial Intelligence; JSAI

3. Background

2015 - 2018
Grad. School of Econ. Nagoya Univ.
D.Econ. (Expected)
2013 - 2015
Grad. School of Econ. Nagoya Univ.
2009 - 2013
Grad. School of Econ. Nagoya Univ.
2006 - 2009
Yokosuka Highschool

Fields of Interest  

1. Marketing Science

We analyze real datasets offered from various firms by statistical methods to predict customer's behaviors in the future or in the competing firms. These information can't be obtained in the ordinary corporate activities so that the development of novel approaches of prediction surely contributes to the society.

We are good at considering multiple datasets (e.g. web access history in E-Commerce; visit and purchase history in the real store; operation history in mobile apps;) at the same time in the model.

2. Statistical Modeling including Machine Learning

In the big data era, the techniques of Neural Network especially Deep Learning thrive in the various fields of industry. Companies have the various needs of handling their data.
(1) Large-Scalability
(2) Real-time Learning
(3) Multifarious variables
We have developed the prominent models with the frexible scalability, online-learning ability and universal use for any datasets.

Research Works  

1. Published Papers

Prediction of consumer behaviors in the competing firms with their heterogeneity of the browing
Junichiro NIIMI & Takahiro HOSHINO (2015). Predicting the Consumers Behavior with Using the Variety of User Access Patterns, Japanese Journal of Applied Statistics, 44(3), 121-143. [Referred]
J-STAGE ResearchGate
Junichiro NIIMI & Takahiro HOSHINO (2017). Predicting Purchases with Using the Variety of Customer Behaviors -Analysis of the purchase history and the browsing history by Deep Learning-, Transactions of the Japanese Society for Artificial Intelligence, 32(2), B-G63_1. [Referred]
J-STAGE ResearchGate

2. Conference

新美潤一郎, & 星野崇宏. (2014). ユーザ別アクセス・パターン情報を用いた,競合サイトでの閲覧・購買行動の予測, 日本マーケティング・サイエンス学会 第95回研究大会, 関西学院大学
J-STAGE ResearchGate
新美潤一郎, & 星野崇宏. (2017). Deep Boltzmann Machine を用いたデータ融合手法の提案 - Data Fusion Method with Deep Boltzmann Machine, 2017年度 人工知能学会全国大会(第31回), ウインクあいち

3. Others

Junichiro NIIMI, Takahiro HOSHINO. (2015). How Often Do Your Customers Purchase From Your Competitors? -Analysis of Users’ Online Browsing History-, PhD Professional Toryumon NC Ambition Camp, North Carolina State University. [Poster session]

Joint Study  

Practical analysis cooperated with the firms and other university

We understand the needs of practicality in order to develop marketing models. We have cooperated with many companies in various fields and other university.

We have ever experienced to be in charge of the evaluation of marketing theory in the in-service training program.


1. Statistical Analysis

I have the experience of the implementations of marketing analysis and the developments of statistical models.

2. Programming

I can use the programming languages especially Python and statistical softwares such as SAS, MATLAB, R.
In addition, I have development experience of E-Commerce websites.

3. Language

IELTS Overall: Score 6.5
I had studied in the English language school in Malaysia and in the classes at the North Carolina State University. I established some joint projects in some Asian contries with local students.


1. Leading Graduate School Program

Not only the research but I take part in many activities in the Program for Leading Graduate Schools "PhD Professional: Gateway to Success in Frontier Asia". As a proper member of this, I have been to the Asian countries such as Mongolia, Cambodia, Kyrgiz and Malaysia, and finally to the United States and attend lectures about practical business, entrepreneurship and self-development.

In addition, as a representative of the university, I was invited to the study tour offered by IBM Japan and visit IBM New York and Watson Research Center.

I am featured in Toyo-Keizai (physical magazine and online article).

2. Science Communication

We have held the small conference at the cafe as the science communication. We have the seminar about recent Big Data, Artificial Intelligence and Machine Learning fields to the non-academic people.


Please use following address for the contact.

1. E-mail

2. Address in the university

Room 319, Bldg. C, School of Science, Nagoya University
Furou-cho, Chikusa-ku, Nagoya, 464-8601 JAPAN
Junichiro NIIMI

3. SNS

You can send messages with SNS.

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