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SEAM Lab
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The lab works on accounting information science, service engineering, and data science.

AboutAbout the lab
Our era is ours to create!
SEAM Lab specializes in accounting information science, service engineering, and social data science.
Its research philosophy is to open up a new knowledge frontier: Service Engineering, Accounting, and Marketing (SEAM).
Its educational philosophy is "nurturing next-generation service innovators," and it aims to train STEM-trained service innovators who can talk about money.
In recent years, its papers have covered machine learning on accounting and management data, emotion estimation from biosignals, and the effects of voice in customer service in virtual space.
Key terms
- Service engineering
- A field that designs and improves services using engineering approaches and data analysis
- Journal entry data
- Accounting data that records each transaction by dividing account titles and amounts into debits and credits
- Data collaboration
- A method in which multiple organizations bring together their data in processed form, without sharing it as is, and analyze it jointly
NewsLab news
View More ↗ResearchResearch themes
SEAM Lab, centered on accounting information science and service engineering, studies the analysis of accounting and management data, measurement using biosignals, and the effects of voice in customer service. Its papers in recent years have covered machine learning on journal entry data, methods for analyzing distributed data without sharing it, prediction of the financial condition of small and medium-sized enterprises, and emotion estimation.
*Illustrative imageMachine learning on accounting journal entry data
Using double-entry bookkeeping journal entry data, the lab works on anomaly detection, cash flow prediction, and synthetic data generation. For prediction, it uses machine learning methods such as LSTMs and graph neural networks.
*Illustrative imageAnalyzing data without sharing it
As joint research, the lab works on data collaboration methods that analyze confidential data split across multiple organizations without sharing it as is. Using medical data as an example, it also works on estimating treatment effects.
*Illustrative imagePredicting financial deterioration in small and medium-sized enterprises
The lab studies a framework for predicting whether a small or medium-sized enterprise will fall into financial distress. It is testing methods that handle the uncertainty of predictions, as well as methods that explain a prediction through counterfactuals, that is, how the outcome would change under different conditions.
*Illustrative imageEmotion estimation and voice-based customer service
The lab studies a system that estimates emotions from multiple biosignals measured contactlessly, assuming medical consultation settings. It also examines the effect of making the voice resemble the other person's in customer service in virtual space.
MembersFaculty
- ProfessorYukihiko Okada
VoicesStudent voices
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Report an errorAbout the images
The top and research theme images are illustrative and were not taken at the lab. They are cropped from Wikimedia Commons images. Cropped CC BY-SA images are provided under the same CC BY-SA license as the original (version shown on each line).
- Top image: “Grounds & facilities - data analysis office, UNIVAC 1106” U.S. Army Natick Soldier Systems Center / CC BY 4.0 (cropped)
- Machine learning on accounting journal entry data: “Ledger” RaphaelQS / CC0 (cropped)
- Analyzing data without sharing it: “Hospital Room at Shriners Hospital - DPLA - 39410747f69ec94aa7e3a3dcc574c5dc” Norton and Peel / Public domain (cropped)
- Predicting financial deterioration in small and medium-sized enterprises: “Corner shop, Burley Street, Elland - geograph.org.uk - 1840842” Humphrey Bolton / CC BY-SA 2.0 (cropped)
- Emotion estimation and voice-based customer service: “Customer Service counter, Platform 2, Dutton Park Railway Station P1013918” John Robert McPherson / CC0 (cropped)
- Related lab (志田研究室): “Crowds On Wynyard Crossing Bridge” Ingolfson / CC0 (cropped)
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(髙橋 裕紀) ): “Customer Service counter, Pimpama Railway Station, Old Pacific Highway, Gold Coast P1130327” John Robert McPherson / CC0 (cropped) - Related lab (宇宙測地・
空間情報研究室): “Laquila differential interferogram by TerraSAR-X” DLR / CC BY 3.0 (cropped) - Related lab (繁野研究室): “Flight departure board at Canberra Airport, November 2022” Kgbo / CC BY-SA 4.0 (cropped)
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