Alex Black
Game Developer at Self-employed
Melbourne, Victoria, Australia
Summary
🤩
Rockstar🎓
Top SchoolAlex Black is a Melbourne-based game developer with 11 years of hands-on experience creating mostly private games since 2012, specializing in Unreal Engine and a broad creative toolset including MotionBuilder, VRoid Studio, and Adobe suite tools. He blends game production skills with backend and ML engineering experience, contributing performance and feature improvements to the well-known Deeplearning4j project—work that touched CNN testing, loss functions, and BERT-related data handling. Comfortable across art, animation, audio, and tooling, Alex brings practical multidisciplinary fluency rather than narrow specialization. Currently self-employed and studying Cert IV in Cyber Security, he pairs creative development with emerging security knowledge that strengthens his end-to-end approach to game projects. Colleagues would describe him as a steady maintainer who quietly improves stability and performance behind the scenes.
10 years of coding experience
Year 12, Year 12 at St Helena Secondary CollegeCert IV, Cyber Security, Cert IV, Cyber Security at Melbourne Polytechnic
Github Skills (12)
neural-network10
javas10
machine-learning10
deeplearning4j10
artificial-intelligence10
loss-functions10
deep-learning10
java10
testing10
spark9
recurrent-neural-networks9
tensorflow4
Programming languages (5)
Github contributions (5)
deeplearning4j/deeplearning4j-examples
Sep 2015 - May 2020
Deeplearning4j Examples (DL4J, DL4J Spark, DataVec)
Role in this project:
Back-end Developer
Back-end DeveloperContributions:658 commits, 279 PRs, 427 pushes in 4 years 9 months
Contributions summary:Alex primarily contributed to the Deeplearning4j examples repository, making small fixes, updating links, and addressing API changes. Their work involved modifying example scripts for deep learning models, specifically within the dl4j-spark component, to incorporate the beta6 and beta7 versions. Additionally, the user corrected code within the SameDiff and RL4J examples. The user's modifications reflect ongoing maintenance and updates to the project's core functionalities.
deeplearning4jpythonzeppelin-notebookdeep-learningmachine-learning
deeplearning4j/deeplearning4j
Jul 2015 - Jun 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:Backend Developer & ML Engineer
Backend Developer & ML EngineerContributions:7357 commits, 2216 PRs, 2709 pushes in 5 years
Contributions summary:Alex's commits primarily focus on improving the runtime performance and testing of deep learning models. This involves optimizations to tests for Convolutional Neural Networks and the implementation of a new loss function (SparseMCXENT). The contributions also include support for features such as the time-distributed wrapper layer, sentence-pair handling within the BERT iterator, and the integration of other neural network features, indicating a focus on refining DL4J's functionality and improving its testing framework, particularly in areas relevant to Recurrent Neural Networks.
deeplearning4jpythonautomatic-differentiationneural-netskeras-tensorflow
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