Ryotaro Kobayashi

Date 05/14/2024

小林涼太郎 / Ryotaro KOBAYASHI                                     

Second-year master’s student,

Department of Systems Innovation,

School of Engineering

Email : b2022rkobayashi@socsim.org

Education

04/2023-present The University of Tokyo, Tokyo, Japan

Master of Engineering,

Department of Systems Innovation, School of Engineering

04/2021-03/2023 The University of Tokyo, Tokyo, Japan

Bachelor of Engineering,

Department of Systems Innovation, Faculty of Engineering

Advisor: Kiyoshi Izumi

Thesis: “Economic Ripple Effect Analysis by Causal-Chain Presentation System Considering Output Diversity”

04/2019-03/2021 The University of Tokyo, Tokyo, Japan

Undergraduate, Natural Sciences I, College of Arts and Sciences

Publications

International Conferences (Refereed)

1.        R. Kobayashi, Y. Murayama and K. Izumi, “Impact Analysis of Social Events on Industries through Narrative Causal Search,” 2023 IEEE International Conference on Big Data (BigData), Sorrento, Italy, Oct 2023.

2.        R. Kobayashi, Y. Murayama and K. Izumi, “Economic Causal Chain Presentation System Considering Output Diversity to Search Economic Ripple Effects,” The 4th Workshop on Knowledge Discovery from Unstructured Data in Financial Services (KDF 2023) in the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2023), Taipei, Taiwan, Jul 2023.

3.        H. Sakaji, R. Kobayashi, K. Izumi, H. Mitsugi and W. Kuramoto, “Summarization of Investment Reports Using Pre-trained Model,” The 13th International Conference on Smart Computing and Artificial Intelligence (SCAI 2023) in the 14th IIAI International Congress on Advanced Applied Informatics (IIAI AAI 2023), Koriyama, Japan, Jul 2023.

Domestic Conferences (Non-refereed)

1.        R. Kobayashi, Y. Murayama and K. Izumi, “A Weakly Supervised Approach Leveraging Causal-sensitive Sentence Embeddings by Contrastive Learning for Discerning Economic Causality,” 2024年度人工知能学会全国大会(第38回), no. 3Q1-IS-2a-02, 浜松, 2024年5月. (口頭発表)

2.        小林涼太郎, 高柳剛弘, 鈴木雅弘, 坂地泰紀, 和泉潔, “経済的因果検索のためのデータセット構築に向けて,” NLP若手の会第18回シンポジウム(YANS2023), 東京, 2023年8月. (ポスター発表)

3.        高柳剛弘, 小林涼太郎, 鈴木雅弘, 坂地泰紀, 和泉潔, “Causal Text Mining in the Era of Large Language Modeling: A Reality Check,” NLP若手の会第18回シンポジウム(YANS2023), 東京, 2023年8月. (ポスター発表)

4.        小林涼太郎, 坂地泰紀, 和泉潔, “経済波及効果発見のための出力の多様性を考慮した因果連鎖提示システムの構築,” 2023年度人工知能学会全国大会(第37回), no. 2L4-GS-3-01, 熊本, 2023年6月. (口頭発表)

5.        小林涼太郎, 坂地泰紀, 和泉潔, “BERTとGATを用いた金融テキストにおける因果関係を含む文の判定,” 言語処理学会第29回年次大会, 沖縄, 2023年3月. (口頭発表)

Awards

1.        2023年度人工知能学会全国大会優秀賞 (2023年7月)

2.        令和4年度 東京大学 工学部長賞 (2023年3月)

3.        令和4年度 東京大学工学部システム創成学科 優秀卒業研究賞 (2023年3月)

Activities

l  Participation in the 2022 UTokyo Global Internship Program (UGIP) Data Hackathon Finals

l  Qualification - Applied Information Technology Engineer Examination, Information-technology Promotion Agency, Japan (06/2021)

Skills

l  Programming - Python, Java

l  Others - Infrastructure(Linux, AWS, Ansible, etc...), Deep Learning, Machine Learning