Tarique Siddiqui

PhD Student
Department of Computer Science
University of Illinois at Urbana Champaign(UIUC)
   SC 1121, 201 N Goodwin Avenue, Urbana, IL 61801

I am a second year Ph.D. student in the Databases and Information Systems Research Group (DAIS) at UIUC, advised by Prof. Aditya Parameswaran.

My research interests lie at the intersection of database systems, data mining, and human-computer interaction. Currently, I am building systems and algorithms for interactive data analytics for extracting insights and patterns from large and complex datasets.

Previously, I have worked on heterogeneous network based text mining problems for identifying and ranking interesting concepts in large scale datasets such as scientific corpora. I have also worked at Goldman Sachs on complex event processing, and large scale distributed systems for identifying correlations among events, trending, telemetry, and predictive analytics.

I received my B.Tech in Computer science from National Institute of Technology India in 2011. I am a recipient of Siebel Scholars Award, 2015 and Indian National Talent Search (NTS) Scholar award, 2005.
  • Sep 2, 2017: Presented our paper on zenvisage at VLDB 2017.
  • Jan 8, 2017: Open-source release of zenvisage (v0).
  • Oct 15, 2016: Our full paper on zenvisage has been accepted at VLDB 2017. Pre-camera ready version here.
  • Oct 11, 2016: Our demo paper on zenvisage has been accepted at CIDR 2017. Pre-camera ready version here.
  • July 17, 2016: Our full paper on FacetGist: Collective Extraction of Document Facets in Large Technical Corpora, has been accepted at CIKM 2017. Paper here.
  • May 13, 2016: We gave a talk on zenvisage at the multi-institution reading group on Visualization for Data Exploration and Analysis. Slides here.
  • May 1, 2016: Release of a new preprint on zenvisage. Paper here.
  • October 26, 2015, We presented our workshop paper on visualization recommendatiom systems at DSIA, VIS 2015 Chicago. Slides from Prof. Aditya Parameswaran.
  • September 2015, Our paper on "Towards Visualization Recommendation Systems" got accepted at the workshop on Data Systems for Interactive Analysis(DSIA), VIS 2015 Chicago
  • September 2015, Thrilled to be receiving the Siebel Scholars Award for the class of 2016. Announcements: 1, 2.
  • August 2014, Excited to be starting my MS under Prof. Aditya Parameswaran at the Department of Computer Science, UIUC
Selected Projects

Zenvisage is a visual analytics system for ad-hoc, interactive, visual exploration of data. It enables users directly specify insights, i.e., trends, patterns, or anomalies of interest through a novel query language- ZQL and a set of interactive visual interfaces. The system efficiently identifies the right visualization that meets user specifications.


Given a collection of scientific documents, FacetGist automatically labels each document with a set of concepts on different key aspects that people are interested in (e.g., application, technique, and dataset). We propose a novel graph-based framework for paper profiling. It considers not only local sentence-level features, such as string suffix and surrounding relation phrase, but also global context information, including document topics and section structures, to model the aspect of a concept mentioned in a document. This task has many interesting applications in scientific domain, including document summarization, literature search, patentability study and business intelligence.


Traditional database systems operate in an all-or-nothing manner, taking as long as it takes to return the entire set of results, however large the result set may be. However, analysts performing data exploration often browse, i.e., pose a query, examine a few of the resulting records and then repeatedly issue new queries. To this end, I am contributing to the development of an alternative database query interaction paradigm called browsing. The aim is to make efficient use of bitmap indices and design fast sampling algorithms for rapid retrieval of a small number of query result records.

Fabric: A Complex Event Processing System

I contributed to the design and development of Fabric, an agent based distributed complex event processing framework for alerting, trending and predictive analytics, for discovering dependencies among the firm’s applications and systems for risk, impact and root cause analysis.

I assisted and helped in designing the following data management and system related courses at UIUC:
  • Human in Loop Data Mananagement
    Fall 2015 with Prof. Aditya Parameswaran
  • Advanced Data Management
    Spring 2015 with Prof. Aditya Parameswaran
  • Systems Programming
    Fall 2014 with Dr. Lawrence Angrave

When I have spare time, I enjoy arts, traveling, listening to urdu poetry and watching cricket.