Deepak Kukreja

Deepak Kukreja

Project Assistant

Followers of Deepak Kukreja964 followers
location of Deepak KukrejaPrayagraj, Uttar Pradesh, India

Connect with Deepak Kukreja to Send Message

Connect

Connect with Deepak Kukreja to Send Message

Connect
  • Timeline

  • About me

    Ph.D Scholar at Indian Institute Of Information Technology Allahabad

  • Education

    • Rishikul Vidyapeeth Sonipat

      2009 - 2011
      Non medical Science

      Senior Secondary

    • Indian Institute Of Information Technology Allahabad

      2024 - 2029
      Doctor of Philosophy - PhD Information Technology
    • Kurukshetra University

      2014 - 2016
      Master's degree Electronic Science
    • Sri Aurobindo College

      2011 - 2014
      Bachelor’s Degree Electronics Science (Hons) First

      B.SC. (Hons.) Electronic Science

  • Experience

    • CSIR-CEERI

      Feb 2018 - Jul 2018
      Project Assistant
    • CSIR-CEERI

      Sept 2018 - Mar 2020
      Project Assistant

      Monitoring and management of kubernetes cluster of 5 petaflops (NVIDIA DGX-I) Supercomputing facilities, for prototyping in the fields of Image & Video Analytics, Natural Language Processing and Security etc.

    • Indian Institute Of Information Technology Allahabad

      Jan 2021 - now

      Low resolution face recognition on resource-constrained devices is a project that aims to develop a system capable of recognising faces even when the images are of low resolution and captured on devices with limited processing power and memory.The goal of the project is to overcome the challenges of recognizing faces from low-quality images that are often captured in real-world scenarios, such as security cameras, webcams, or even low-end smartphones. Resource-constrained devices, such as embedded systems and IoT devices, often have limited computational power, storage, and battery life, making it challenging to perform complex tasks such as face recognition.The project would involve developing an algorithm or a model that can accurately identify faces from low-quality images and run efficiently on resource-constrained devices. This would require using techniques such as deep learning, image processing, and computer vision to extract features from the low-resolution images and match them against a pre-trained face database.The project would also require optimizing the algorithm for low-power devices by reducing the computational and memory requirements while maintaining accuracy. This could involve using techniques such as pruning, quantization, and compression to reduce the size and complexity of the model.Overall, the low resolution face recognition on resource-constrained devices project is an exciting and challenging area of research that has significant real-world applications in fields such as security, surveillance, and bio-metrics. Show less

      • Ph.D Scholar

        Jan 2024 - now
      • Junior Research Fellow

        Aug 2023 - now
      • Junior Research Fellow

        Jan 2021 - now
  • Licenses & Certifications