ADA Lab @ UCSD

 

Project Genisys

Overview

Genisys is a new kind of data system that enables ADA applications to easily deploy ML models in environments ranging from the cloud to personal devices to the Internet of Things. Genisys exploits deep learning-based ML models to see, hear, and understand unstructured data and query sources such as speech, images, video, time series, and text. We call this vision of type-agnostic data analytics database perception. Watch this space for more details.

Component Project Webpages

 

SpeakQL
Enabling speech-driven multimodal querying of structured data with regular SQL and more.

 

Vista
Enabling data systems to truly see image and video data for efficient multimodal analytics.

 

Krypton
Enabling fast interactive diagnosis of the internals of visual perception systems.

Publications

  • Incremental and Approximate Inference for Faster Occlusion-based Deep CNN Explanations
    Supun Nakandala, Arun Kumar, and Yannis Papakonstantinou
    ACM SIGMOD 2019 | Paper PDF | TechReport | Code and Data coming soon
    Honorable Mention for Best Paper Award

  • Demonstration of SpeakQL: Speech-driven Multimodal Querying of Structured Data
    Vraj Shah, Side Li, Kevin Yang, Arun Kumar, and Lawrence Saul
    ACM SIGMOD 2019 Demo | Paper PDF | Video

  • Demonstration of Krypton: Optimized CNN Inference for Occlusion-based Deep CNN Explanations
    Allen Ordookhanians, Xin Li, Supun Nakandala, and Arun Kumar
    VLDB 2019 | Paper PDF coming soon | Video

  • Demonstration of Krypton: Incremental and Approximate Inference for Faster Occlusion-based Deep CNN Explanations
    Supun Nakandala, Arun Kumar, and Yannis Papakonstantinou
    SysML 2019 Demo | Paper PDF | Video

  • Hierarchical and Distributed Machine Learning Inference Beyond the Edge
    Anthony Thomas, Yunhui Guo, Yeseong Kim, Baris Aksanli, Arun Kumar and Tajana Rosing
    IEEE ICNSC 2019 | Paper PDF

  • Materialization Trade-offs for Feature Transfer from Deep CNNs for Multimodal Data Analytics
    Supun Nakandala and Arun Kumar
    SysML 2018 (Short paper/poster) | Paper PDF

  • SpeakQL: Towards Speech-driven Multi-modal Querying
    Dharmil Chandarana, Vraj Shah, Arun Kumar, and Lawrence Saul
    ACM SIGMOD 2017 HILDA Workshop | Paper PDF

  • SpeakQL: Towards Speech-driven Multimodal Querying of Structured Data
    Vraj Shah, Side Li, Arun Kumar, and Lawrence Saul
    Under submission | TechReport | Dataset on Drive

  • Materialization Trade-offs for Feature Transfer from Deep CNNs for Multimodal Data Analytics
    Supun Nakandala and Arun Kumar
    Under submission | TechReport | Code and Data