Emanuele Coviello

About Emanuele Coviello

Principal ML scientist at Amazon Music, personalized recommendations, foundation models, and large language models- Founded and served as CEO of Keevio, startup focusing on video, audio and music recommendation and monetization technology- Real world and scientific expertise in machine learning, deep learning, foundation models (audio, multimedia) and large language models- Ph.D. degree in Electrical and Computer Engineering from the University of California, San Diego (UCSD), under the supervision of prof. Gert Lanckriet- Track record of 18 technical/scientific publications of original work in machine learning, computer vision, and audio and music analysis and recommendation, published on some of the most prestigious journals and conferences in machine learning (JMLR, PAMI, CVPR, ICML, NeurIPS).

Experience

1. Principal Applied Scientist, Machine Learning

   Amazon Music

   Dec 2015 — Present

Education

• UC San Diego

  PhD, Electrical and Computer Engineering; Electrical and Computer Engineering

  2009 — 2014

• University of California, San Diego

  UC Education Abroad Program, Electrical and Computer Engineering

  2007 — 2008

• G. B. Quadri

  High School, Maturità Scientifica

  1998 — 2003

• Università degli Studi di Padova

  MS, Telecommunication Engineering

  2006 — 2008

• Università degli Studi di Padova

  BS, Information Engineering

  2003 — 2006

Skills

• Machine Learning
• Matlab
• Information Retrieval
• Data Mining
• Latex
• Python
• Signal Processing
• Algorithms
• Artificial Intelligence
• Statistical Modeling
• Mathematical Modeling
• Natural Language Processing
• Pattern Recognition
• Image Processing
• Computer Science
• Computer Vision
• Optimization
• Deep Learning