Vinu E Venugopal

My current research at IIITB has a technological focus that includes building systems for high-velocity stream data processing, distributed deep learning and scalable reasoning. I am broadly interested in working in the various facets of Large-scale Information/Data Management (such as distributed query processing, semantic indexing, information extraction and information retrieval), Knowledge Graphs, Neurosymbolic AI and Semantic Web Technologies. 

• Received funding from Gov of Karnataka to support the DataLake project, Jun 2021

• Selected for Leonardo Research Fellowship, Sep 2020

• Our paper: "AIR: A Light-Weight Yet High-Performance Dataflow Engine based on Asynchronous Iterative Routing" is the Best Paper Award finalist at SBAC-PAD-32 2020

• IITM Institute Research Award April 2017

• Our paper: "Improving large scale assessment tests using ontology-based approaches" is a Best Student Paper finalist in FLAIRS-28 2015

International Conferences (Full papers):

1. Xu, Jingjing; Biryukov, Maria; Theobald, Martin; E.V, Vinu;  BigText-QA : Question Answering over a Large-Scale Hybrid Knowledge Graph, EAI BDTA 2023

2. Kulkarni, Apurva; E.V, Vinu; ‪ R, Chandrashekar; Semantics-aware Document Retrieval for Government Administrative Data, ESCRI 2023.

3. Kulkarni, Apurva; R, Chandrashekar; E.V, Vinu; ‪ Ontology Mediated Document Retrieval for Exploratory Big Data Analytics, ICSC 2022.

4.  Kulkarni, Apurva; Bassin, Pooja; Parasa, Niharikasri; Srinivasa, Srinath; E.V, Vinu; ‪ R, Chandrashekar; Ontology Augmented Data Lake System for Policy Support, International Conference on Big Data Analytics 2022.

5. E.V, Vinu; Kumar, P Sreenivasa, Verbalizing but not just Verbatim Translations of Ontology Axioms, BNAIC2021 [link]

6. E.V, Vinu; Theobald, Martin; Chaychi, Samira; Tawakuli, Amal, AIR: A Light-Weight Yet High-Performance Dataflow Engine based on Asynchronous Iterative Routing.  SBAC-PAD 2020  (nominated for best paper award)

7. Wu, Yan; Chen, Jinchuan; Haxihauti, Plarent; E.V, Vinu; Theobald, Martin; GILP: Guided Inductive Logic Programming for Cleaning Knowledge Bases with Iterative User Feedback, GCAI’20. 

8. E.V, Vinu; Kumar, P Sreenivasa, Improving large scale assessment tests using ontology based approaches, In the Proceedings of the Twenty-Eighth International Florida Artificial Intelligence Research Society Conference, FLAIRS 2015, Hollywood, Florida. May 18-20, 2015, Page 457, 2015. [link]  (best student paper finalist)

     Posters/Short Paper:

1. Convergence time analysis of Asynchronous Distributed Artificial Neural Networks, CoDs COMAD 2022, Mauro Dalle Lucca Tosi, Vinu E. Venugopal and Martin Theobald [link]

2. Dalle Lucca Tosi, Mauro;  Theobald, Martin; E.V, Vinu; Online Learning using Distributed Neural Networks. DTU DRIVEN Colloquium 2021. [link] 

3. E.V, Vinu; Theobald, Martin; Effective Stream-data processing using Asynchronous Iterative Routing Protocols. BigData2021  [Poster+shortpaper]

4. E.V, Vinu; Theobald, Martin, Benchmarking Synchronous and Asynchronous Stream Processing Systems, CoDS COMAD 2020: Proceedings of the 7th ACM IKDD CoDS and 25th COMADJanuary 2020 Pages 322–323 [PPT] [PDF]

5. E.V, Vinu; Kumar, P Sreenivasa, Improving Ontology Verbalization using Semantic-level Refinement, In the Proceedings of DL2019, Oslo, Norway.  June 18-21, 2019 [PPT] [Poster]

Journals:

1. E.V, Vinu; Theobald, Martin; Tassetti, Damien; Chaychi, Samira; Tawakuli, Amal. Targeting Light-Weight and Multi-Channel approach for Asynchronous Stream Data Processing, Submitted to the Special Issue on “Computer Architecture and High-Performance Computing”, Journal of Parallel and Distributed Computing (accepted on 25th April, 2022)

2. E.V, Vinu; Kumar, P Sreenivasa, Effective Verbalization of Ontologies using Semantic-Refinement, Journal of Web Semantics. Undergoing revision, Aug 2020. [link]

3. E.V, Vinu; Kumar, P Sreenivasa, Difficulty-level Modeling of Ontology-based Factual Questions, Semantic Web Journal. Accepted, Nov 2018. [link]

4. E.V, Vinu; Kumar, P Sreenivasa, Automated Generation of Assessment Tests from Domain Ontologies, Semantic Web Journal, Volume 6, 1023-1047, July 2017. [link]

5. E.V, Vinu; Kumar, P Sreenivasa, A novel approach to generate MCQs from domain ontology: considering DL semantics and open-world assumption, Journal of Web Semantics: Science, Services and Agents on the World Wide Web, Volume 34 (C), 40-54, May 2015. [link]

CS839 NoSQL Systems Term-II Jan-2023 - May-2022

CS876 Streaming Data Systems Term-I Aug-2022 - Jan-2023

CS838 Cloud Computing Term-II Dec-2021 - May-2022

1. DataLake Project - Gov. of Karnataka

2. AI-DataLake - CTRI-DG

3. Data Anonymization - CIET 

Please refer: https://bda-lab.github.io/projects/ for updated project details.

Scalable Data Science (ScaDS) Lab  (https://scads.iiitb.net/)

The ScaDS team focuses primarily on developing scalable solutions for diverse big data problems. The “Big” here refers to not just the volume of the data but also challenges concerning the variety, veracity, and velocity of the data.

This laboratory is a part of the Big Data Research Center established by Prof. Srinath Srinivasa in 2019 to enable collaboration between IIIT Bangalore, with City University London, as the UK partner, and Siemens Research, India, as the industry partner. In addition to the Royal engineering FCRA grant, the lab is also supported by several other grants and funding. Past projects carried out in the Big Data Research Center can be found on the WSL website.