Mostafa Karimi
Applied Science Manager at Amazon
Redmond, Washington, United States
Summary
👤
Senior🎓
Top SchoolMostafa Karimi is an Applied Science Manager at Amazon with a decade of experience blending deep learning, Bayesian methods, and optimization to build high-impact solutions across computational biology, speech, NLP, and computer vision. He holds a Ph.D. in Electrical Engineering from Texas A&M and has driven production-focused research at Microsoft (low-latency ASR and low-resource languages) and Amazon, as well as biotech-focused modeling that contributed to a patent submission at a Flagship Pioneering startup. Comfortable moving models from research to product, he has published and presented work at venues like NeurIPS and CVPR workshops and has a track record of applying SSL methods such as wav2vec2 and HuBERT in hybrid ASR systems. Known for pairing rigorous theoretical tools (convex and combinatorial optimization) with practical engineering, he particularly enjoys projects whose societal impact includes advances in cancer-related computational biology.
10 years of coding experience
13 years of employment as a software developer
Doctor of Philosophy (Ph.D.) Electrical Engineering, Doctor of Philosophy (Ph.D.) Electrical Engineering at Texas A&M UniversityBachelor's Degree Computer Science, Bachelor's Degree Computer Science at Sharif University of Technology
English, Persian
Github Skills (15)
attention-mechanism10
prediction10
drug-discovery10
affinity10
compound10
protein-sequences10
autoencoder10
semi-supervised-learning10
hierarchical9
generative9
deep-learning8
embedding7
tensorflow7
graph6
pytorch5
Programming languages (1)
Github contributions (5)
Shen-Lab/Drug-Combo-Generator
Mar 2020 - Aug 2020
Deep Generative Models for Drug Combination (Graph Set) Generation given Hierarchical Disease Network Embedding
Contributions:20 commits, 17 pushes in 4 months
pytorchcombinationdeep-learningnetwork-embeddinghierarchical
Shen-Lab/DeepAffinity
May 2018 - Jan 2021
Protein-compound affinity prediction through unified RNN-CNN
Contributions:21 commits, 20 pushes, 4 comments in 2 years 8 months
autoencoderrnninterpretable-deep-learningpredictiondrug-discovery
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