Erik Schmidt

Erik Schmidt Email and Phone Number

Machine Learning at Netflix @ Netflix
los gatos, california, united states
Erik Schmidt's Location
San Francisco Bay Area, United States
About Erik Schmidt

I am a Research Scientist at Netflix focused on machine learning and recommender systems. Before Netflix I worked for Pandora on music recommendation. My work combines both research science and product development.During my Ph.D., I worked on machine learning for music, developing algorithms capable of understanding music content directly from the audio waveform. My thesis focused on music emotion recognition, where I aimed to identify the conveyed emotion in a piece of music as well as how it evolved over time.

Erik Schmidt's Current Company Details
Netflix

Netflix

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Machine Learning at Netflix
los gatos, california, united states
Website:
netflix.com
Employees:
11436
Erik Schmidt Work Experience Details
  • Netflix
    Research Scientist L6
    Netflix Apr 2024 - Present
    Los Gatos, California, United States
  • Netflix
    Senior Research Scientist
    Netflix Jan 2020 - Apr 2024
    Los Gatos, Ca
    Machine learning and recommender systems for personalization. Projects spanning homepage row positioning, billboard selection, category and talent ranking, and explainable recommendations. Driving algo for cross-functional projects spanning ML, design, product, and engineering.
  • Pandora
    Staff Scientist
    Pandora Apr 2017 - Dec 2019
    Oakland, Ca
    Developed machine learning systems for music mood understanding and helped launch a collection of personalized playlists focused on specific moods and activities. Led the algorithmic architectural design for recommendation features in Pandora’s on demand music platform, Pandora Premium. This architecture drives autoplay and the magic wand playlist extension tool.
  • Pandora
    Senior Scientist
    Pandora Aug 2013 - Apr 2017
    Oakland, Ca
    Led the playlist and algorithmic design of Thumbprint Radio, a hyper-personalized radio product that in its first year was used by over 25 million listeners and spun over 7.6 billion tracks. Contributed of numerous playlist recommendation strategies to the Pandora listening experience, both personalized and non-personalized, context and content-based. Developed of machine listening systems to automatically understand the musicological content of audio utilizing the incredible data collection known as the Music Genome Project. Work spanning machine learning, recommender systems, and digital signal processing.
  • Drexel University
    Post-Doctoral Research Associate
    Drexel University Sep 2012 - Aug 2013
    Researcher in the Music and Entertainment Laboratory (MET-lab), a group led by Youngmoo E. Kim, an MIT Media Lab Alum. The MET-lab performs research in digital media technologies, especially in the areas of sound and music. Performed research in music emotion recognition spanning the areas of psychology, signal processing, and machine learning. Mentored Ph.D. students in multiple areas of music informatics: automatic mixing of multi-track audio, content-based prediction of musical influence, content-based modeling of musical expression, and musical robotics. Lead instructor for Drexel University Winter 2013 course on Machine Listening and Music Information Retrieval.
  • Drexel University
    Research Assistant
    Drexel University 2007 - Sep 2012
    Ph.D. student in the Music and Entertainment Laboratory (MET-lab). Developed machine learning techniques for automatic prediction of time-varying musical emotion from audio, spanning Kalman-filtering approaches and conditional random fields. Developed deep learning approaches for extracting acoustic features specifically optimized for musical emotion. Developed and implemented DSP libraries for acoustic feature extraction from audio including loudness, timbre, and harmony.
  • Aviom
    Engineering Intern
    Aviom 2005 - 2007
    Developed DSP algorithms for real-time, multi-rate audio processing for 32 simultaneous channels and assisted in FPGA hardware deployment. Maintained and deployed bug fixes in low-level (assembly) user-interface software. Developed hardware for digital mainboards. Performed SMT component level debug and repair of prototype hardware and system beta testing.

Erik Schmidt Education Details

Frequently Asked Questions about Erik Schmidt

What company does Erik Schmidt work for?

Erik Schmidt works for Netflix

What is Erik Schmidt's role at the current company?

Erik Schmidt's current role is Machine Learning at Netflix.

What schools did Erik Schmidt attend?

Erik Schmidt attended Drexel University, Drexel University, Temple University.

Who are Erik Schmidt's colleagues?

Erik Schmidt's colleagues are John Newhart, Imtiyaj Ansari, Virat Kadaru, Mohammed Homran, Neeraj Meena, Prabhat Kumar Singh, Ims Indominus.

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