Nikolaos Dimitriadis is a Machine Learning researcher and Doctoral Assistant at EPFL with nine years of experience and a PhD focused on how knowledge is encoded and transferred in the weight space of foundation models. His work spans Pareto front parametrization for multi-task learning (PaMaL, PaLoRA) and practical model-merging techniques that localize task-specific information and mitigate forgetting (Tall-Masks, LiNeS, MEMOIR). He completed two DeepMind internships tackling visual text rendering in diffusion models and multi-task post-training for large language models, scaling experiments up to 27B parameters. Nikolaos combines rigorous theoretical contributions with scalable, low-rank and post-training methods that improve downstream performance of large pre-trained models, and his research often uncovers compact, task-local structures within merged weights.
9 years of coding experience
1 year of employment as a software developer
Doctor of Philosophy - PhD, Computer Science, Doctor of Philosophy - PhD, Computer Science at EPFL
Master of Engineering - MEng, Electrical and Computer Engineering, Master of Engineering - MEng, Electrical and Computer Engineering at National Technical University of Athens
Contributions:2 pushes, 2 comments, 1 issue in 1 year 7 months
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.