Robert Altena
Private Investor
Saitama Prefecture, Japan
Summary
🤩
Rockstar🎓
Top SchoolRobert Altena is a private investor and former institutional trader who applies over two decades of hands-on market experience to trading Japanese equities and crypto spot markets with founder-level rigor. He founded and ran an AI-driven research firm for seven years, building tools that turned large language models into institutional market intelligence and a proprietary "Chart AI" that matched historical price patterns to probabilistic forward scenarios. Earlier roles include 13 years executing and advising on Japanese equities at JP Morgan and a hybrid engineering/trading role at Daiwa, where he built execution systems and bridged front-office needs with backend analytics. A practical technologist, he has contributed to the Deeplearning4j ecosystem—improving core numerical APIs and example workflows—demonstrating deep familiarity with ML tooling and JVM-based deep learning. Based in Saitama, Japan, he blends quant discipline, product-driven engineering, and market intuition, and deliberately closed his advisory business after achieving strong personal returns. Notably, he asks for advance engagement fees for recruiting inquiries to ensure mutual commitment and respect for time.
11 years of coding experience
29 years of employment as a software developer
Murmellius Gymnasium
Github Skills (12)
javas10
machine-learning10
deeplearning4j10
deep-learning10
linear-algebra10
java10
api-design9
serialization9
back-end-development9
data-serialization9
neural7
neural-network7
Programming languages (6)
Github contributions (5)
deeplearning4j/deeplearning4j-examples
Jul 2016 - Apr 2020
Deeplearning4j Examples (DL4J, DL4J Spark, DataVec)
Role in this project:
ML Engineer
ML EngineerContributions:117 commits, 71 PRs, 25 pushes in 3 years 9 months
Contributions summary:Robert primarily contributed to examples related to DeepLearning4j, specifically focusing on improving and adding examples. They addressed compiler warnings in existing examples, added a serialization example, and updated existing examples. The user's work involved code related to INDArrays, serialization formats (binary, numpy, csv), and example implementations of deep learning models.
deeplearning4jdl4jsparkjavafxintellij
deeplearning4j/deeplearning4j
Aug 2016 - Jan 2020
Suite of tools for deploying and training deep learning models using the JVM. Highlights include model import for keras, tensorflow, and onnx/pytorch, a modular and tiny c++ library for running math code and a java based math library on top of the core c++ library. Also includes samediff: a pytorch/tensorflow like library for running deep learn...
Role in this project:Back-end Developer
Back-end DeveloperContributions:45 commits, 24 PRs, 57 comments in 3 years 5 months
Contributions summary:Robert primarily contributed to the `nd4j` module, specifically focusing on the `nd4j-backends` component and related API changes. Their work involved modifying core transformation functions, introducing new functionalities like the `dot` product, and refactoring existing code to remove redundancies. They also improved the project's documentation through javadoc updates. This suggests a focus on enhancing the core mathematical functionalities and API of the deep learning framework.
cppdeep-learningjavajvmkeras
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