---
title: "Shubham Parab - Research Assistant in United Kingdom | Tal"
description: "Meet Shubham Parab, Robotics & Computer Vision Engineer | ROS 2 | MoveIt2 | SLAM | Robot Perception | AI | 3+ Years R&D Experience based in United Kingdom. AI stack includes cursor, opencode, and claudecode."
image: "https://tal.club/meet/shubham-parab/share-image"
---

# Shubham Parab on Tal

## Headline

Robotics & Computer Vision Engineer \| ROS 2 \| MoveIt2 \| SLAM \| Robot Perception \| AI \| 3\+ Years R&D Experience

## About

Passionate about transforming the future through computer vision, robotics, and AI\. With a proven track record of designing and implementing intelligent systems, I have successfully led projects leveraging machine learning algorithms and advanced imaging technologies\. My expertise includes developing real\-time image processing solutions that enhance automation and decision\-making processes\. I am dedicated to continuous learning and innovation in the tech landscape, aiming to create intelligent solutions that address real\-world challenges\.

## Location

United Kingdom

## AI stack

cursor

opencode

claudecode

## Work experience

Research Assistant at Buckinghamshire New University, Mar 2026 \- Jun 2026 · 4 mos, High Wycombe, · Developed an innovative approach for 3D underwater scene reconstruction by integrating 3D Gaussian Splatting \(3DGS\) with a lightweight neural network to accurately model underwater light effects\. · Reduced training time by over 90% compared to previous methods, enabling rapid model deployment\. · Increased rendering speed to real\-time performance \(up to 241 FPS\), making the solution ideal for autonomous underwater vehicles \(AUVs\) and real\-time applications\. · Addressed challenges such as light absorption, scattering, and colour distortion, resulting in higher\-quality visual reconstructions\. Applied advanced training techniques, including deferred activation and progressive parameter warm\-up, to ensure stable and efficient learning\. · Utilised Python, PyTorch, deep learning, and computer vision; validated improvements using the SeaThru\-NeRF benchmark dataset\.

Research Intern – AI & Network Planning at Newcastle University, Mar 2026 \- May 2026 · 3 mos, Newcastle Upon Tyne, · Developed an end\-to\-end ML pipeline and interactive Streamlit dashboard for Tofa Ltd to automate LoRaWAN gateway site surveys, reducing manual planner workload by 97\.5%\. · Engineered an asynchronous scraping and geospatial viewpoint generation workflow \(GeoPandas, Playwright\) to automatically extract targeted Street View imagery\. · Implemented a two\-stage computer vision model using SAM3 for zero\-shot object detection/cropping and a fine\-tuned ConvNeXt CNN for suitability classification\. · Achieved 98% accuracy and 99\.2% precision on auto\-approvals across 3,070 validation images\. · Designed and integrated a human\-in\-the\-loop, three\-tier confidence policy \(auto\-approve, manual review, auto\-reject\) to ensure reliable, scalable network planning\.

Machine Learning Intern at Lunaris Medical Ltd, Feb 2026 \- Apr 2026 · 3 mos, Newcastle Upon Tyne, • Automated the large\-scale generation of 3D synthetic data using FLAME, generating 10,000\+ annotated face meshes and drastically reducing manual dataset creation effort\. • Executed mesh\-level geometry processing with Python and NumPy, streamlining data handling\. • Applied preprocessing techniques, including scaling, normalisation, and mesh simplification, to prepare data for model training • Evaluated and contrasted 3D landmark detection approaches to shape dataset design and boost model performance\. • Engineered a scalable pipeline to batch\-process 3D meshes and annotations efficiently\.

System Engineer at Tata Consultancy Services, Jun 2022 \- Aug 2025 · 3 yrs 3 mos, Bengaluru, • Engineered end\-to\-end Computer Vision and Robotic Perception modules using Python and OpenCV for Retail Automation and Industrial Robotics\. • Developed and deployed Object Detection and Anomaly Detection pipelines, enabling autonomous navigation and decision\-making for omnidirectional robots\. • Led the integration of Vision\-ML models with ROS/ROS2 middleware and control systems, ensuring low\-latency communication for real\-time robotic manipulation\. • Optimised data processing pipelines, achieving a 30% reduction in manual intervention and improved system accuracy during client demos\.

Django Developer at Karthi wealth infotech limited, Jun 2021 \- Jul 2021 · 2 mos, Remote, • Architected scalable backend modules using Python and the Django Framework, ensuring high availability for web applications\. • Implemented RESTful APIs and conducted systematic debugging to resolve legacy software issues, improving code maintainability and performance\.

## Education

Msc in Data Science and AI, Artificial Intelligence, Newcastle University

Bachelor of Engineering \- BE, Electrical and Electronics Engineering, Ramrao Adik Institute of Technology

[View the original profile](https://tal.club/meet/shubham-parab)

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