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. 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.

Active Component Projects

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

Panorama Enabling unbounded vocabulary querying over video.

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.

Publications

• Panorama: A Data System for Unbounded Vocabulary Querying over Video
  Yuhao Zhang and Arun Kumar
  VLDB 2020 | Paper PDF and BibTeX| TechReport | Talk slides | Talk videos: Youtube Bilibili | Blog post | Source code on GitHub

• Query Optimization for Faster Deep CNN Explanations
  Supun Nakandala, Arun Kumar, and Yannis Papakonstantinou
  ACM SIGMOD Record 2020 | Paper PDF and BibTeX
  ACM SIGMOD Research Highlights Award

• Incremental and Approximate Computations for Accelerating Deep CNN Inference
  Supun Nakandala, Kabir Nagrecha, Arun Kumar, and Yannis Papakonstantinou
  ACM TODS 2020 | Paper PDF and BibTeX
  Invited Paper

• Vista: Optimized System for Declarative Feature Transfer from Deep CNNs at Scale
  Supun Nakandala and Arun Kumar
  ACM SIGMOD 2020 | Paper PDF and BibTeX | TechReport | Blog post | Talk Video | Code

• SpeakQL: Towards Speech-driven Multimodal Querying of Structured Data
  Vraj Shah, Side Li, Arun Kumar, and Lawrence Saul
  ACM SIGMOD 2020 | Paper PDF and BibTeX| TechReport | Blog post | Dataset on Drive

• Incremental and Approximate Inference for Faster Occlusion-based Deep CNN Explanations
  Supun Nakandala, Arun Kumar, and Yannis Papakonstantinou
  ACM SIGMOD 2019 | Paper PDF and BibTeX | TechReport | Blog post | Talk Video
  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 and BibTeX| 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 and BibTeX | 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

• 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 and BibTeX