Utkarsh Singh

Utkarsh Singh

Electrical & Control Engineer

Followers of Utkarsh Singh513 followers
location of Utkarsh SinghBengaluru, Karnataka, India

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  • Timeline

  • About me

    Senior Software Engineer | Wipro | R&D | Lab 45

  • Education

    • Manipal Institute of Technology

      2016 - 2020
      BE - Bachelor of Engineering Electrical and Electronics Engineering
    • National Institute of Technology, Kurukshetra, Haryana

      2020 - 2022
      Master of Engineering - MEng Electrical Engineering
  • Experience

    • SolarMobil Manipal

      Mar 2017 - Mar 2019
      Electrical & Control Engineer
    • BHEL Hyderabad

      Dec 2018 - Jan 2019
      Former Trainee
    • C-DAC

      Jul 2021 - Jan 2022
      Project Intern

      -Developed a desktop app for image processing using Wxpython and Deep Learning.-Implemented Navier-Stokes equation using explicit Crank Nicolson method with Python.

    • Wipro

      Sept 2022 - now

      - Led research on AGI tools and Generative AI, showcasing proficiency in LangChain and Autogen.- Implemented Retrieval-Augmented Generation (RAG) framework to enhance information retrieval in enterprise systems, enabling efficient response generation based on user queries. Integrated retrieval-based methods with generative models to fetch accurate and contextually relevant results from large, domain-specific datasets. Improved the precision of query responses, leading to enhanced decision-making and productivity within the organization.- Developed a video-understanding pipeline that combined both visual and audio data to generate meaningful video summaries. Utilized VLMs for object detection and scene analysis, along with audio processing methods like speech-to-text and audio event recognition. This multimodal approach enabled the extraction of key insights from both visual content and spoken information, improving the accuracy and relevance of automated video summaries- Designed and implemented a multi-modal Retrieval-Augmented Generation (RAG) framework to fetch relevant information from both textual and visual modalities. The system integrated NLP-based retrieval mechanisms with computer vision techniques to handle multi-modal inputs, allowing the model to generate more accurate and contextually relevant results by cross-referencing both text and image/video data. Enhanced the model's capability to retrieve and generate responses by leveraging pre-trained vision-language models (e.g., Qwen 2 VL) and combining them with generative models (e.g., GPT, LLama 3, Qwen) for multi-modal question answering and information retrieval tasks Show less

      • Senior Software Engineer (Data Science)

        Oct 2023 - now
      • Software Engineer (Data Science)

        Sept 2022 - Oct 2023
  • Licenses & Certifications

    • Programming, Data Structures and Algorithms using Python

      NPTEL
      Apr 2022
    • The Arduino Platform and C Programming

      Coursera
      Mar 2018
      View certificate certificate
    • Deep Learning Specialization

      DeepLearning.AI
      Nov 2023
      View certificate certificate
    • AI Agents in LangGraph

      DeepLearning.AI
      Jul 2025
      View certificate certificate
    • AWS Certified Machine Learning Engineer- Associate

      Amazon Web Services (AWS)
      Jul 2025
      View certificate certificate
    • AWS Certified Cloud Practitioner

      Amazon Web Services (AWS)
      May 2025
      View certificate certificate
    • Neural Networks and Deep Learning

      DeepLearning.AI
      Mar 2022
      View certificate certificate
    • Python for Data Science and Machine Learning Bootcamp

      Udemy
      Jan 2022
      View certificate certificate