Biography

Shunsuke Kitada (北田 俊輔 in Japanese) is a Ph.D student at the Intelligent information processing laboratory (Iyatomi Lab) in Hosei University. His research interests include deep learning-based natural language processing, computer vision, medical image processing, and computational advertising.

His personality traits can be summarized as follows:

  • Love research and development. I am enjoying research life, and I am currently conducting three research topics simultaneously, e.g., natural language processing, medical image based computer vision, computational advertising.
  • Every day read and implement the cutting-edge deep learning models from research paper. I have released many re-implementations of models using mainly Chainer and PyTorch. Therefore, based on state-of-the-art cases, I can advise on deep learning base product design.
  • High technical communicativity. Summarize what I made and what I studied, and spread such information. This shows that I can input and output regularly.

Interests

  • Deep Learning
  • Natural Language Processing
  • Computer Vision
  • Medical Image Processing
  • Computational Advertising

Education

  • PhD in Engineering, Current

    Graduate School of Science and Engineering, Hosei University

  • MSc in Engineering, 2020

    Graduate School of Science and Engineering, Hosei University

  • BSc in Engineering, 2018

    Hosei University

News

Interviewed by Nikkan Kogyo Shimbun, Ltd.

I was interviewed by 日刊工業新聞社 about my research conducted with my co-author.

Got Honorable Mention in YANS 2019

I got an honorable mention in YANS 2019.

Interviewed about my research internship in Gunosy Inc.

I was interviewed about my research internship in Gunosy. The content of the interview is written in this article.

Got CEO special award in the second half of FY2019 at Gunosy

I got a CEO special award at Gunosy. The details if written in this article in Japanese.

Accepted our paper to KDD2019

Our paper: “Conversion Prediction Using Multi-task Conditional Attention Networks to Support the Creation of Effective Ad Creative” has been accepted to KDD2019.

Experience

 
 
 
 
 

Research Assistant

Hosei University

Apr 2020 – Present
 
 
 
 
 

Internship

M3, Inc.

Jun 2019 – Jul 2019
Quantified and visualized doctors’ interest from browsing history. Based on these analyses, I built a system for recommending articles for doctors from scratch.
 
 
 
 
 

Research Internship

Gunosy Inc.

Aug 2018 – Present
Conducted fundamental research to generate advertisement automatically. I have written a paper and prepared for a presentation for an international conference based on the results during my internship.
 
 
 
 
 

Deep Learning Advisor

Piascore, Inc.

Jun 2018 – Aug 2018
I have advised how to solve practical problems of existing services that use machine learning algorithms and deep learning models. Additionally I have shown examples of the kind of problems recent deep learning models are capable of solving.
 
 
 
 
 

Teaching Assistant

Hosei University

Apr 2018 – Present
Assisted in several classes at Hosei University:

  • Image Processing
  • Information Theory
  • Operating System
  • Programming Language C/C++
  • Programming Language JAVA
 
 
 
 
 

Internship

Faber Company Inc.

Mar 2018 – Mar 2018
Engineer internship 3days / ¥100,000. I implemented machine learning models that accurately capture semantic features of a document in a document similarity.
 
 
 
 
 

Part-time job

Gunosy Inc.

Mar 2017 – Jul 2018
I have worked on improving the user experience and participated in improving the logic of the article distribution. Also visualized multiple KPIs and contributed to service growth through data analysis.
 
 
 
 
 

Part-time job

VALEUNEX Japan Inc.

Feb 2016 – Jun 2018
Dealt with large-scale nonstructural patent information in various forms, e.g., pre-processing, crawling, scraping, and analyzing these data.
 
 
 
 
 

Teaching Assistant for Deep Learning Hands-On Training Lab

NVIDIA Japan

Jan 2016 – Jan 2017
Assisted in several workshops in Tokyo relating to deep learning and CUDA:

  • GTC Japan 2016 DLI
  • NVIDIA Deep Learning Institute 2017 in Takada-no-baba
  • NVIDIA Deep Learning Institute 2017 in Tokyo Midtown
  • GTC Japan 2017 DLI
 
 
 
 
 

Internship

Works Applications Co., Ltd.

Aug 2015 – Aug 2015
Planned and implemented enterprise resource planning (ERP) packages.

Recent & Upcoming Talks

Text Analytics Symposium 2019

ICML/KDD 2019 Pre-conference session

Awards & Grants

Got Honorable Mention in YANS 2019

I got an honorable mention in YANS 2019.

Got CEO special award in the second half of FY2019 at Gunosy

I got a CEO special award at Gunosy. The details if written in this article in Japanese.

Got Student Honorable Mention in IPSJ 2019

I got an student honorable mention in IPSJ 2019

Got 1st prize of hackU Hosei 2018

I got an 1st prize of HackU Hosei 2018 creating ChashBox with Cpaw members

Got Student Award at FR FRONTIER

I got student award at FR FRONTIER: Classification of FR FRONTIER: Classification of color of clothes in fashion images sponsored by opt DSL DeepAnalysis.

Projects

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Paper Survey

📚Survey of previous research and related works on machine learning (especially Deep Learning) in Japanese.

Hosei University Soft Tennis Club Hp

🎾 Hosei University Soft Tennis Club’s home page repository.

chainer-FocalLoss

Implementation of Focal loss in Chainer.

chainer-RICAP

Implementation of RICAP in Chainer.

LSUV.pytorch

Implementation of LSUV (Layer-sequential unit-variance) in PyTorch.

libtorch-gin-api-server

High-speed Deep learning API Server with Libtorch (C++) and Gin (Golang)

nvhtop

A tool for enriching the output of nvidia-smi forked from peci1/nvidia-htop.

chainer-PyramidNet

Implementation of PyramidNet in Chainer.

chainer-InceptionResNetV2

Implementation of InceptionResNetV2 in Chainer.

chainer-IMSAT

Implementation of IMSAT in Chainer.

chainer-center-loss

Implementation of Center Loss in Chainer.