Biography

Shunsuke Kitada (北田 俊輔 in Japanese) is a Ph.D student at Major in applied informatics, graduate school of science and engineering, Hosei University under the supervision of Prof. Hitoshi Iyatomi. 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 the 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

  • 🤖 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

Accepted our paper to ACL2020 Student Research Workshop

Our paper: “AraDIC: Arabic Document Classification Using Image-Based Character Embeddings and Class-Balanced Loss” has been accepted to ACL2020 Student Research Workshop.
Last updated on Apr 29, 2020 Paper Accepted

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.
Last updated on Apr 29, 2020 Interview

Got Honorable Mention in YANS 2019

I got an honorable mention in YANS 2019.
Last updated on Apr 29, 2020 Award

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.
Last updated on Apr 29, 2020 Interview

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.
Last updated on Apr 29, 2020 Award
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International Conference

Conversion Prediction Using Multi-task Conditional Attention Networks to Support the Creation of Effective Ad Creative

Proc. of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining. 2019. (Acceptance Rate = 20%)
Preprint PDF Video DOI Code

End-to-End Text Classification via Image-based Embedding using Character-level Networks

Proc. of IEEE Applied Imagery Pattern Recognition (AIPR) 2018 Workshop
Preprint PDF DOI

Skin lesion classification with ensemble of squeeze-and-excitation networks and semi-supervised learning

International Skin Imaging Collaboration 2018.
Preprint

Domestic Conference

北田 俊輔, 彌冨 仁 (2020). 解釈可能な敵対的摂動を用いた頑健な注意機構の学習. NLP 2020.

PDF

青木 匠, 北田 俊輔, 彌冨 仁 (2020). 文字単位の解釈可能な潜在表現のdata augmentation. NLP 2020.

PDF

Mahmoud Daif, Shunsuke Kitada, Hitoshi Iyatomi (2020). Image-based Character Embedding for Arabic Document Classification. NLP 2020.

PDF

長澤 駿太, 北田 俊輔, 彌冨 仁 (2020). Script-aware embedding を用いた文字表現の獲得. NLP 2020.

PDF

北田 俊輔, 彌冨 仁 (2019). 解釈性向上のための注意機構と損失勾配に対する関連損失の導入. YANS 2019.

Mahmoud Daif, Shunsuke Kitada, Hitoshi Iyatomi (2019). Image Based Character Embeddings for Arabic Document Classification. YANS 2019.

Slides

長澤 駿太, 北田 俊輔, 彌冨 仁 (2019). 日本語の文字体系を考慮した文書分類モデルの提案. YANS 2019.

Poster Slides

北田 俊輔, 彌冨 仁 (2019). 頑健な皮膚腫瘍診断支援のための body hair augmentation. IPSJ 2019.

北田 俊輔, 彌冨 仁 (2019). 広告クリエイティブ自動生成にむけたマルチタスク学習と Conditional Attention による CVR 予測. NLP 2019.

PDF

北田 俊輔, 関 喜史, 彌冨 仁 (2018). 広告クリエイティブ自動生成に向けた単語レベルでの評価手法の検討. YANS 2018.

See all publications

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

This talk introduces a case study of research and development internship at Gunosy Inc.
Sep 27, 2019 3:40 PM — 4:00 PM Future Corporation
PDF Slides

ICML/KDD 2019 Pre-conference session

Jun 3, 2019 7:00 PM — 9:30 PM LAPRAS Inc.

Awards & Grants

Got Honorable Mention in YANS 2019

I got an honorable mention in YANS 2019.
Last updated on Apr 29, 2020 Award

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.
Last updated on Apr 29, 2020 Award

Got Student Honorable Mention in IPSJ 2019

I got an student honorable mention in IPSJ 2019
Last updated on Apr 29, 2020 Award

Got 1st prize of hackU Hosei 2018

I got an 1st prize of HackU Hosei 2018 creating ChashBox with Cpaw members
Last updated on Apr 29, 2020 Award

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.
Last updated on Apr 29, 2020 Award

Projects

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All PyTorch Chainer Tool

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-MeanTeachers

Implementation of Mean teachers are better role models in Chainer.

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.

Popular Topics

Award Chainer Computational Advertising Domestic Conference HP Image-based Character Embedding International Conference Interpretability Invited Talk Medical Image Processing Natural Language Processing News Non-refereed Preprint PyTorch Refereed Server Survey Tool