Reza ZadehFounder & CEO at Matroid Adjunct Professor at Stanford At Stanford, I focus on Machine Learning, Distributed Computing, and Discrete Applied Mathematics. I am CEO of Matroid and previously served on the Technical Advisory Board of Databricks. Press | Publications | Teaching | Students | Talks | Conferences | BioNewsCreated CME 323: Distributed Algorithms and Optimization [2015] [2016] [2017] [2018] [2020] [2022] [2024] Teaching CME 305: Discrete Mathematics and Algorithms [2014] [2015] [2016] [2017] Won Best Paper Award runner-up at KDD 2016 Built the Scaled Machine Learning Conference News in Bloomberg, Wall Street Journal, MIT Technology Review, TechCrunch, and many others Interview: On the Evolution of Machine Learning, from Linear Models to Neural Networks [oreilly report] Matroid was covered in The Wall Street Journal. Selected PublicationsDeep Learning for Glaucoma Detection and Identification of Novel Diagnostic Areas in Diverse Real-World Datasets [pubmed], TVST 2022 Detecting Glaucoma Using 3D Convolutional Neural Network of Raw SD-OCT Optic Nerve Scans [pdf], AAO 2019 FusionNet: 3D Object Classification Using Multiple Data Representations [pdf] [blog], NIPS 2016 Matrix Computations and Optimization in Apache Spark [pdf], KDD 2016 MLlib: Machine Learning in Apache Spark [arxiv], JMLR 2015 Dimension Independent Similarity Computation [pdf] [extension] [slides] [poster] [code] [press], JMLR 2014 Estimate of Shaking Intensity by Combining Earthquake Characteristics with Tweets [pdf] [slides] [video] [demo] [full], NCEE 2014 On the Precision of Social and Information Networks [pdf] [slides], COSN 2013 WTF: The Who to Follow Service at Twitter [pdf], WWW 2013 A Uniqueness Theorem for Clustering [pdf] [slides], UAI 2009
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