Experience

• 

  Akara Robotics

  • Computer Vision Intern

    • May 2024 - Present

• 

  Carnegie Mellon University Robotics Institute

  • Pittsburgh, Pennsylvania, United States

  • Graduate Research Assistant

    • Nov 2023 - Present
    • Pittsburgh, Pennsylvania, United States

    1. Developed 3D Trajectory Extraction in pursuit of learning from demonstrations 2. Implemented various state-of-the-art video object segmentation models for reliable tracking

• 

  ORB Robotics

  • Lead Computer Vision Engineer

    • Sep 2023 - Present

• 

  ANZ

  • Bengaluru, Karnataka, India

  • Graduate Engineer

    • Jun 2022 - Jul 2023
    • Bengaluru, Karnataka, India

    1. Architected and expanded automation framework for end-to-end data onboarding process reducing manual efforts by 80%2. Integrated various modules of test automation framework resulting in increased efficiency of tester by 3X saving 2 million dollars annually

• 

  Aqgromalin

  • Computer Vision Intern

    • Feb 2022 - May 2022

    1. Implemented a weekly supervised learning algorithm (LCFCN) for chicken counting application achieving an MAE of 0.5622. Deployed the LCFCN Model on the cloud with Flask achieving near real-time inference rate

• 

  Indian Institute of Science (IISc)

  • Bengaluru, Karnataka, India

  • Research Intern

    • Dec 2020 - May 2022
    • Bengaluru, Karnataka, India

    1. Created a light-weight and failure-tolerant table organization pipeline for targeted pick and place of known objects to predefined configurations as a part of the Open Cloud Robot Table Organization Challenge, IROS 2020 2. Implemented a custom 3D Object Pose estimation technique leveraging RGB-D camera trained using non-photorealistic synthetic data achieving a 2cm translational error 3. Modified Crazyflie default firmware to accept individual motor PWM commands4. Developed end-to-end reinforcement learning-based controller for drones and demonstrated sim-to-real capabilities

• 

  Agdhi

  • AI Intern

    • Jan 2021 - Sep 2021

    1. Devised a custom Auto-Encoder-based Classification CNN Model for seed variety classification improving systems accuracy from 60% to 97% 2. Participated in Cassava Leaf Disease Classification and reached 10% submissions with an accuracy of 86%

• 

  IEEE Student Branch BMSIT&M

  • India
  • Non-profit Organizations
  • 1 - 100 Employee

  • Chairperson

    • Jul 2020 - Nov 2020

  • Vice Chair

    • Nov 2019 - Jul 2020

  • Joint Secretary

    • Apr 2019 - Nov 2019