Tsukasa Nomoto
Business Development Manager at Ishuran
Tokyo, Japan
Summary
🤩
Rockstar🎓
Top SchoolTsukasa Nomoto is a Business Development Manager in Tokyo with 15 years of cross-industry experience spanning healthcare, SaaS, sports, and consulting. At a healthcare IT startup he leads multiple projects to build AI-powered products for cancer patients, combining hands-on engineering and product management experience with market research and patient interviews. He brings technical credibility from meaningful open-source work—contributing loss functions and metrics to Microsoft’s widely used LightGBM and bug fixes/features to projects like Keras and mpv—so he fluently translates ML/engineering constraints into business outcomes. Having launched SaaS products, built customer success workflows, and driven marketing strategies, he excels at turning user feedback into measurable growth. Educated overseas and well-traveled, he leverages a global perspective to work effectively with international partners and diverse patient populations.
15 years of coding experience
5 years of employment as a software developer
Bachelor's degree, Business Administration and Management, General, Bachelor's degree, Business Administration and Management, General at Linnaeus UniversityBusiness Administration and Management, General, Business Administration and Management, General at Portland State UniversityBachelor's degree, English Language and Communication, Bachelor's degree, English Language and Communication at Kansai Gaidai University
Japanese, English
Stackoverflow
51reputation
1kreached
0answers
1question
Github Skills (29)
loss-functions10
package-management10
python10
data-science10
machine-learning10
c1110
ffmpeg10
gradient-boosting10
ruby10
c1710
keras10
regression10
deeplearning-ai10
deep-learning10
tensorflow10
Programming languages (13)
Github contributions (5)
microsoft/LightGBM
Dec 2016 - Apr 2020
A fast, distributed, high performance gradient boosting (GBT, GBDT, GBRT, GBM or MART) framework based on decision tree algorithms, used for ranking, classification and many other machine learning tasks.
Role in this project:
ML Engineer / Data Scientist
ML Engineer / Data ScientistContributions:1 review, 54 commits, 81 PRs in 3 years 4 months
Contributions summary:Tsukasa contributed significantly to the LightGBM project by implementing new loss functions and metrics for regression tasks, including Huber, Fair, and Poisson losses. They also made code modifications and additions to support L1 loss and updated the existing code for the creation of valid sets and the handling of approximate hessians for L1 and Huber losses. The user's work directly enhances the model's capabilities and improves its performance.
kagglepythondata-mininglightgbmmicrosoft
Homebrew/legacy-homebrew
Apr 2012 - Oct 2015
💀 The former home of Homebrew/homebrew (deprecated)
Role in this project:Back-end Developer
Back-end DeveloperContributions:28 commits, 4 PRs, 6 comments in 3 years 7 months
Contributions summary:Tsukasa primarily contributed to the maintenance and enhancement of formula files within the Homebrew ecosystem. They implemented new formula files for packages like `l-smash` and updated existing ones, such as `x264`, to incorporate new versions, dependencies, and configuration options. Their work included updating the `x264` formula to add MP4 support, and modifying homebrew internal files. The user also updated the codebase to accommodate changes in taps and formula directory structures, demonstrating a focus on the overall health and organization of Homebrew's formula system.
macoshomebrew
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