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    Saeed Amizadeh

    Machine Learning Scientist at Microsoft

    Saeed Amizadeh is a Senior Machine Learning Researcher at Microsoft's Applied Sciences Group (ASG) in Redmond, Washington.5 He has been working at Microsoft since 2015.3 His research interests primarily focus on neuro-symbolic methods, deep learning, reinforcement learning, and geometric deep learning.35

    Amizadeh holds a Ph.D. from the University of Pittsburgh, which he completed in 2013 under the supervision of Milos Hauskrecht.23 After his Ph.D., he worked as a Research Scientist at Yahoo from 2013 to 2015 before joining Microsoft.3

    Throughout his career, Amizadeh has made significant contributions to the field of machine learning. He has authored numerous publications, with his work being cited over 1,300 times.1 Some of his notable research includes:

    1. Generic and scalable framework for automated time-series anomaly detection (2015)1
    2. Learning to solve circuit-SAT: An unsupervised differentiable approach (2019)1
    3. Neuro-symbolic visual reasoning: Disentangling (2020)1

    Amizadeh's expertise spans various areas of machine learning, including deep learning, neuro-symbolic methods, reinforcement learning, and geometric deep learning.3 His recent work includes research on weakly-supervised audio separation using bi-modal semantic similarity.4

    On LinkedIn, his username is indeed saeed-amizadeh, as mentioned in the query.5

    Highlights

    Milos Hauskrecht's Home Page - University of Pittsburgh
    ‪Saeed Amizadeh‬ - ‪Google Scholar‬
    Jan 1 · openreview.net
    Saeed Amizadeh | OpenReview
    Aug 28 · people.cs.pitt.edu
    [PDF] Saeed Amizadeh: PhD. Thesis - Error: 400

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    Saeed Amizadeh
    Saeed Amizadeh, photo 1
    Saeed Amizadeh, photo 2
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    Location

    Greater Seattle Area