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Rohan K. AI, Robotics and General Development

My name is Rohan K. and I have over 0 years of experience in the tech industry. I specialize in the following technologies: AI Development, Artificial Intelligence, Computer Vision, YOLO, Autonomous Vehicles, etc.. I hold a degree in Master of Science (MS). Some of the notable projects I've worked on include: Real-Time Multi-Task Perception, Real-time Monocular SLAM for embedded devices, Grid Vision - A lightweight solution to object Perception, Map-less and Map-based navigation of mobile robot (differential drive), Real-Time Stereo Depth Estimation, etc.. I am based in Thane, India. I've successfully completed 7 projects while developing at Softaims.

I possess comprehensive technical expertise across the entire solution lifecycle, from user interfaces and information management to system architecture and deployment pipelines. This end-to-end perspective allows me to build solutions that are harmonious and efficient across all functional layers.

I excel at managing technical health and ensuring that every component of the system adheres to the highest standards of performance and security. Working at Softaims, I ensure that integration is seamless and the overall architecture is sound and well-defined.

My commitment is to taking full ownership of project delivery, moving quickly and decisively to resolve issues and deliver high-quality features that meet or exceed the client's commercial objectives.

Main technologies

  • AI, Robotics and General Development

    0 years

  • AI Development

    1 Year

  • Artificial Intelligence

    1 Year

  • Computer Vision

    1 Year

Additional skills

Direct hire

Potentially possible

Previous Company

MyRide

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Experience Highlights

Real-Time Multi-Task Perception

This project demonstrates super fast inference pipeline for multiple perception modalities including depth estimation, semantic segmentation, and lane detection. This is achieved using multi-threaded

Real-time Monocular SLAM for embedded devices

This project demonstrates real-time monocular SLAM capable of handling fast moving drones on resource constrained hardware (Raspberry Pi 5).

Grid Vision - A lightweight solution to object Perception

This project demonstrates real-time object perception by fusing LiDAR and camera data. A custom YOLOv4 (3l) detector identifies static and dynamic objects. Static object positions are extracted from e

Map-less and Map-based navigation of mobile robot (differential drive)

This project demonstrates successful navigation of mobile robot in two ways - 1. Mapless - Control vectors that guide robot to the goal position. 2. Map - Occupancy grid and A* algorithm.

Real-Time Stereo Depth Estimation

This project demonstrates real-time stereo depth estimation using two approaches: 1. A combination of a disparity calculation algorithm (SGM) with a depth refinement network, and 2. An end-to-end ste

Education

  • Arizona State University

    Master of Science (MS) in Robotics and Autonomous Systems

    2022-01-01-2024-01-01

Languages

  • English (Fluent)