Bansilal Ramnath Agarwal Charitable Trust's

Vishwakarma Institute of Technology,Pune

Faculty Profile
Home | MR. KESHAV GOPINATH TAMBRE

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MR. KESHAV GOPINATH TAMBRE

Designation:

Assistant Professor

Department:

Computer Science and Engineering (Data Science)

Email :

keshav.tambre@vit.edu

Phone :

9325857066

 



Personal

Educational Qualification :

University Degree Year
Dr. Babasaheb Ambedkar Marathwada University ME 2016
Dr. Babasaheb Ambedkar Marathwada University BE 2006


Date of Joining : 18/09/2024


Total Experience : 18 year:1 month


Area of Specialization :

  • Cloud Computing

    • Experience :

    Sr. No Organisation Designation From Date To Date Years of Experience
    1 Jaihind Institute of Technology Lecturer 08-Jan-2008 31-Aug-2011 3
    2 Zeal Dnyanganga college of Engineering and Research Assistant Professor 22-Jun-2011 30-May-2015 3
    3 International Institute of Information Technology Assistant Professor 08-Jun-2015 19-Sep-2024 9
    4 Vishwakarma Institute of Technology Assistant Professor 23-Sep-2024 - 1

    Research of Interest :

    1. Cloud Computing


    Technical Skills :

    1. Cloud Computing


    Professional Contribution :

    1. Class Teacher SEM I and SEM II

    2. Lab Incharge

    3. Infra Structure Management


    Invited Talks :

    Sr. No Name Description Type Role From Date To Date
    1 NEP Orientation FDP Participated 21-Apr-2025 30-Apr-2025

    International Journal:

    1. Real Time AI Based Platform for debate using CRAG and Wave2Vec2 models ,International Conference on Sustainable Innovation with Artificial Intelligence and Machine Learning,125

    International Conference:

    1. Smart Traffic Management: Optimization and Analysis Using YOLOv8 ,Networks and Soft Computing (ICNSoC-2025),125


    Patents :

    1. A method and device for Efficient Workforce Management and HRM using Machine Learning
    2. Low-Latency Interconnects Between High-Performance Computing Nodes and Quantum Devices
    3. Cryogenic-to-HPC Interfacing Systems for Direct QPU–CPU/GPU Communication
    4. Hybrid GPU-HPC Systems for Tensor-Network Simulations of Quantum Systems
    5. Fault-Tolerant HPC Architectures Tailored for Hybrid Quantum Workloads
    6. Energy-efficient scheduling of quantum and HPC workloads across heterogeneous systems
    7. Hybrid HPC-AI Pipeline for Drug Repurposing – Combining HPC-based Docking with Deep Learning Models for Accelerated Screening of FDA-Approved Drugs
    8. Adaptive High-Performance Computing Framework for Scalable Molecular Dynamics Simulations
    9. Cloud-Based High-Performance Computing (HPC) Platforms for Testing Quantum Algorithms Prior to Hardware Deployment



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