Summary
Trung Trinh is a doctoral researcher in Probabilistic Machine Learning at Aalto University with 10 years of industry and academic experience focused on making neural networks robust to distribution shifts. Expected to graduate in May 2025, he blends theoretical work—three papers at NeurIPS/ICML/ICLR—with practical engineering using PyTorch, JAX, Sacred, and Weights & Biases to produce scalable, reproducible solutions. His research emphasizes efficient Bayesian approaches and advanced optimization to improve generalization and uncertainty calibration for safety-critical applications like autonomous driving and medical diagnostics. Prior industry work spans end-to-end ML systems for NLP and fraud detection, delivering productionized models with Dockerized deployments and continuous updates. Based in Espoo, Finland, he pairs rigorous academic credentials (MSc 4.93/5, BE 9.09/10) with a record of open-source releases that accelerate adoption of robust deep learning methods.
10 years of coding experience
1 year of employment as a software developer
Doctor of Philosophy - PhD, Machine Learning and Artificial Intelligence, Doctor of Philosophy - PhD, Machine Learning and Artificial Intelligence at Aalto University
Bachelor of Engineering - BE, Computer Science, 9.09/10, Bachelor of Engineering - BE, Computer Science, 9.09/10 at Ho Chi Minh University of Technology