Athanasios Nikolakopoulos
Senior Applied Scientist, Amazon Special Projects
Seattle, Washington, United States
Summary
👤
Senior🎓
Top SchoolAthanasios Nikolakopoulos is a Senior Applied Scientist at Amazon Special Projects who blends deep academic rigor with product-focused ML engineering across Large Language Models, Graph ML, and computational biology. With a PhD and postdoctoral work in AI and over nine years of experience, he has architected production Generative AI systems—like SAGE—that now supply attribute values for millions of catalog items and have delivered measurable revenue and customer experience gains. His research record (35+ publications, multiple Best Paper awards, and NSF-funded work) underpins practical inventions such as diversified sampling, zero-shot graph expansion, and adaptive batching that dramatically cut labeling and inference costs. At Amazon he now leads pretraining of large-scale GenAI models for biology, highlighting a rare crossover from recommender systems and graph methods into life-science model pretraining. Known for turning novel graph-based and sampling ideas into scalable production wins, he routinely operates at the intersection of foundational research and high-impact engineering.
9 years of coding experience
10 years of employment as a software developer
Post Doc Artificial Intelligence, Post Doc Artificial Intelligence at University of MinnesotaDoctor of Philosophy (Ph.D.) Computer Science and Engineering, Doctor of Philosophy (Ph.D.) Computer Science and Engineering at University of Patras
Greek, English
Stackoverflow
1reputation
0reached
0answers
0questions
Github Skills (40)
pytorch9
amd9
inference9
gpt9
cuda9
transformer8
compression8
slim8
collaborative-filtering8
mlops8
matrix-factorization8
llama8
llm8
tpu8
recommendation-engine8
Programming languages (3)
Github contributions (5)
KarypisLab/SLIM
Aug 2019 - Sep 2020
High-performance implementation of SLIM-based approaches for Top-N recommendation
Contributions:16 commits, 2 PRs, 19 pushes in 1 year
recommendationcollaborative-filteringmachine-learningmatrix-factorizationperformance
nikolakopoulos/Adaptive-Diffusions-for-SSL
Dec 2018 - Feb 2019
Methods for semi-supervised learning on graphs
Contributions:13 commits, 12 pushes in 2 months
supervised-learningsupervisedsemisemi-supervised-learningmachine-learning
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