Faculty Profile
Home | MRS. PRIYANKA CHETAN KINAGE

Image

MRS. PRIYANKA CHETAN KINAGE

Designation:

Assistant Professor

Department:

Computer Science and Engineering(Artificial Intelligence)

Email :

priyanka.kinage@vit.edu

Phone :

9922508728

Educational Qualification :

University Degree Year
Bharati Vidyapeeth University Mtech 2014


Date of Joining : 30/06/2025


Total Experience : 11 year:7 month

Experience :

Sr. No Organisation Designation From Date To Date Years of Experience
1 Bharati Vidyapeeth Lecturer 03-Aug-2009 30-Dec-2016 7
2 MITWPU Assistant Professor 01-Dec-2017 - 0
3 SmtKashibaiNavaleCOE 07-Sep-2021 30-Jun-2025 3

Invited Talks :

Sr. No Name Description Type Role From Date To Date
1 Integrating ML and AI for Scalable IoT solutiions FDP Participated 13-Apr-2026 17-Apr-2026
2 AI for Sustainable Development Goals Worked as coordinator and organizing team member for 5 days Faculty training program FDP Coordinator 01-Dec-2025 05-Dec-2025
3 AI Powered Education Platform and Tools Training on AI Powered Education Platform and Tools FDP Participated 25-Aug-2025 30-Aug-2025
4 Decentralized AI Decentralized AI FDP Participated 18-Aug-2025 25-Aug-2025
5 Universal Human Values curriculum delivery and evaluation Universal Human Values curriculum delivery and evaluation FDP Participated 11-Aug-2025 11-Aug-2025
6 FDP on DELD Digital Electronics and Logic designs FDP Participated 24-Jul-2025 24-Jul-2025
7 Google AI Essentials Coursera Training course MOOC Participated - -

International Journal:

  1. Leveraging Computer Vision and Data Science for Enhanced Operational Efficiency in Smart Enterprises. ,TANGENCE,125
  2. Leveraging Computer Vision and Data Science for Enhanced Operational Efficiency in Smart Enterprises ,Tangence,125


  1. Best Paper Award

Patents :

  1. ECOCOLLECT BUY SELL and RECYCLE
  2. WorkTrack-AI Productivity Monitoring System
  3. Hybrid Detectiion Segmentation for Ground Penetrating Radar A unifiied Dataset Builder YoloUNet AR
  4. AIEnabled BodyWorn camera for bribery and abuse of power detection
  5. Hybrid DetectionSegmentation for Ground Penetrating Radar A unified dataset Builder YoloUNet archiitecture and radar aware fusion framework for robustsubsurface feature mapping



Copyright © Vishwakarma Institute of Technology,Pune 2026 All rights reserved.

[Best viewed in IE 10+, Firefox, Chrome, Safari, Opera.]

:::| powered by VGESPL |:::