Agustinus Kristiadi
Assistant Professor at Vector Institute
Ontario, Canada
Summary
🤩
Rockstar🎓
Top SchoolAgustinus Kristiadi is an assistant professor and probabilistic machine learning researcher with 13 years of experience spanning industry software engineering and academic research. Currently a tenure-track faculty at Western University and a Faculty Affiliate of the Vector Institute, he focuses on probabilistic ML, decision-making, and AI4Science, building on a PhD from the University of Tübingen and an MSc from Bonn. He bridges rigorous research and practical engineering—contributing ML code to popular generative-models repos (adding CVAE/CGAN and VAE loss improvements) and shipping software during earlier industry roles. Based in Ontario, Canada, he combines deep technical expertise with teaching and mentorship, and often brings Neovim-driven developer tooling habits to his workflow. Unknown to many, his background includes both formal doctoral work and hands-on contributions that improve reproducibility and visualization in generative modeling.
13 years of coding experience
4 years of employment as a software developer
Doctor of Philosophy - PhD, Computer Science, Doctor of Philosophy - PhD, Computer Science at University of TübingenMaster of Science (M.Sc.), Computer Science, Master of Science (M.Sc.), Computer Science at The University of BonnBachelor of Engineering, Computer Science, Bachelor of Engineering, Computer Science at Universitas Atma Jaya Yogyakarta
Stackoverflow
163reputation
30kreached
6answers
2questions
Github Skills (15)
keras10
generative-model10
pytorch10
machine-learning10
deep-learning10
tensorflow10
python-multiprocessing6
scrapy6
php6
sqlite6
reactor6
laravel6
eloquent6
web-crawler6
python6
Programming languages (7)
Github contributions (5)
wiseodd/generative-models
Dec 2016 - Aug 2018
Collection of generative models, e.g. GAN, VAE in Pytorch and Tensorflow.
Role in this project:
ML Engineer
ML EngineerContributions:102 commits, 8 PRs, 85 pushes in 1 year 8 months
Contributions summary:Agustinus contributed significantly to the development of generative models within the repository. They updated the loss function in a variational autoencoder (VAE) implementation to use cross-entropy. The user also added code for a conditional VAE (CVAE) model, including the necessary layers, model compilation, and training steps, as well as code for latent space and reconstruction visualizations. Furthermore, they added a conditional GAN (CGAN) implementation.
pytorchautoencodere-modelsdeep-learninggenerative-adversarial-network
wiseodd/controlled-text-generation
Dec 2017 - Jul 2018
Reproducing Hu, et. al., ICML 2017's "Toward Controlled Generation of Text"
Contributions:32 commits, 2 PRs, 15 pushes in 7 months
nlpcontrollednatural-language-generationicmlnatural-language-processing
Find and Hire Top DevelopersWe’ve analyzed the programming source code of over 60 million software developers on GitHub and scored them by 50,000 skills. Sign-up on Prog,AI to search for software developers.