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bhatiasiddharth/README.md

👋 Hi, I am Siddharth Bhatia

I am building TurboML, a machine learning platform reinvented for real-time so that you can manage the complete production ML lifecycle while leveraging real-time data.

Previously, I completed my PhD in Streaming Anomaly Detection from National University of Singapore (NUS) advised by Bryan Hooi and bachelors at BITS Pilani. My research was supported by the Presidents Graduate Fellowship and I was recognized as a Young Researcher by the ACM Heidelberg Laureate Forum.

During my PhD, I spent wonderful summers interning at Amazon Web Services, and Google Research. I also co-organized the Outlier Detection and Description workshop at KDD which brings together academic and industry researchers, and practitioners to discuss and reflect on outlier mining challenges.

I am best reached via email and am always open to interesting conversations and collaboration.

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  1. Stream-AD/MIDAS Stream-AD/MIDAS Public

    Anomaly Detection on Dynamic (time-evolving) Graphs in Real-time and Streaming manner. Detecting intrusions (DoS and DDoS attacks), frauds, fake rating anomalies.

    C++ 762 93

  2. Stream-AD/ExGAN Stream-AD/ExGAN Public

    Adversarial Generation of Extreme Samples

    Python 75 16

  3. Stream-AD/MStream Stream-AD/MStream Public

    Anomaly Detection on Time-Evolving Streams in Real-time. Detecting intrusions (DoS and DDoS attacks), frauds, fake rating anomalies.

    C++ 113 20

  4. Stream-AD/AnoGraph Stream-AD/AnoGraph Public

    Sketch-Based Anomaly Detection in Streaming Graphs

    C++ 78 11

  5. Stream-AD/MemStream Stream-AD/MemStream Public

    MemStream: Memory-Based Streaming Anomaly Detection

    Python 83 18