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. 

Recent Publications

• Mitra, Aniket; E.V, Vinu; Optimizing Class Subsumption through Controlled Dynamics of n-Balls in Vector Space, Extended Semantic Web Conference (ESWC), 2024 (CORE’21: A, h5-index: 32, h5-median: 51)

• Mitra, Aniket; E.V, Vinu; Enhancing Region-Based Geometric Embedding for Gene-Disease Associa- tion, International Conference on Data Science and Management of Data (CoDs COMAD 2024) (Short Paper) (h5-index: 20, h5-median: 26)

• D. L. Tosi, Mauro; E.V, Vinu; Theobald, Martin. TensAIR: Real-Time Training of Neural Networks from Data-streams, International Conference on Machine Learning and Soft Computing (ICMLSC), 2024. (h5-index: 12, h5-median: 20). (best paper presentation award)

• Kulkarni, Apurva; Ramanathan, Chandrashekar; E.V, Vinu; Cognitive Retrieve- Empowering Document Retrieval with Semantics and Domain- Specific Knowledge Graph, CIKM (Workshop on Enterprise Knowl- edge Graphs-LLM), 2023. (CORE: A, h5-index: 79, h5-median: 122)

• Kulkarni, Apurva; Ramanathan, Chandrashekar; E.V, Vinu; Semantics-Aware Document Retrieval for Government Administrative Data, International Journal of Semantic Computing (IJSC), Vol. 17 Issue 3, Page 477-491, Sep 2023. DOI: 10.1142/S1793351X23300017 (CiteScore: 1.9, IF: .8, h5-index: 19, h5-median: 21).

• E.V, Vinu; Theobald, Martin; Tassetti, Damien; Chaychi, Samira; Tawakuli, Amal; Targeting Light-Weight and Multi-Channel approach for Asynchronous Stream Data Processing, Journal of Parallel and Distributed Computing, Vol. 167, Page 18-30, April 2022. (CORE: A+, CiteScore: 10.2, IF: 3.8, h5-index: 65, h5-median: 98).

• E.V, Vinu; Theobald, Martin; Chaychi, Samira; Tawakuli, Amal. AIR: A Light-Weight Yet High-Performance Dataflow Engine based on Asynchronous Iterative Routing, Proc. of IEEE 32nd Intern. Symposium on Computer Architecture and High Performance Computing (SBAC-PAD). ISBN: 978-1-7281-9924-5 (h5-index: 13, h5-median: 22, CORE: C) (best paper finalist)

• AI 551 Foundations of AI Term-II Jan-May Since 2024 (co-teaching with Prof. Badrinath)

• CS839 NoSQL Systems Term-II Jan- May Since 2022

• CS876 Streaming Data Systems Term-I Aug-Dec Since 2022

• CS838 Cloud Computing Term-II Dec-2021 - May-2022 (not offering anymore)

• Laboratoire des Sciences du Numérique de Nantes (LS2N) CNRS, France, Prof. Dr. Guillaume RASCHIA and Prof. Jose MARINEZ | StreamSpan: Advancing Stream Data Systems with Spanning Events | Funding agency: CEFIPRA

• Machine Intelligence & Robotics CoE (MINRO), IIITB, India, Prof. G R Sinha | Machine Learning based study of Community Wellness | Funding agency: MINRO, IIITB

• Center for Technology Research and Innovation (CTRI), IIITB, India, Prof. Chandrashekar Ramanathan An AI-Driven Scalable DataLake Framework | Funding agency: Center for E-Governance, IIITB

• Center for Internet of Ethical Things (CIET), IIITB, India, Prof. Chandrashekar Ramanathan | Ethics-aware Framework for Large-Scale IoT Data Processing | Funding agency: Gov. of Karnataka.

• Web Science Lab, IIITB, India, Prof. Srinath Srinivasa & Prof. Sridhir M Karnataka Data Lake | Funding agency: Gov. of Karnataka

• University of Luxembourg and Max-Planck-Institut für Informatik, Germany, Prof. Dr. Gerhard WEIKUM & Prof. Dr. Martin THEOBALD BigText - A Distributed Graph Database for Large-Scale Text Analytics | Funding agency: FNR CORE

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

• Received the Collaborative Scientific Research Grant from Indo-French Centre for the Promotion of Advanced Research (CEFIPRA)

• Our paper: “TensAIR: Real-Time Training of Neural Networks from Data-streams” is a Best Paper Presentation Award at ICMLSC-24

• 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

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

The Scalable Data Science and AI (ScaDS.ai) Lab was established by Prof. Vinu E. Venugopal in 2021 at the International Institute of Information Technology Bangalore (IIITB). Our research team is dedicated to creating scalable solutions for a variety of big data challenges.

Our current research efforts are concentrated on two main areas:

1. Advancing Neuro-Symbolic AI: We are developing robust AI algorithms to enhance reasoning capabilities.

2. Distributed Streaming Data Systems: We are designing architectures to efficiently process spanning events, which are events associated with a time interval rather than a single timestamp.

Lab members:

PhD Students

• Naseela Jehan (full-time, Aug 2023 - Present)

• Vadivelan Balasubramanian (part- time, Jan 2023 - Present)

MS Students

• Prachi Naik (Aug2022-Present)

• AniketMitra (Jan2023-Present)