Shaival Parikh

- Developing a robust perception pipeline for the robot application
- Designing fast and efficient mapping and map generation systems using Drone imagery
- Designing safety features for robot mobility in different deployment environments and conditions

Analyzed component lifecycles and failure times for different robot at Intuitive Surgical and designing tools for internal use

- Developed machine learning models to extract tree-level metrics (e.g., height, diameter, species, tree count) from satellite imagery, integrating ground-level sensor data (LiDAR, GPS, etc.) collected across diverse forest types and terrains
- Conducting on-site field visits for data collection, system testing, and validation, directly contributing to product refinement and improved customer sati

Developing a streamlined pipeline for a multi 3D object detection and tracking using only monocular vision for autonomous vehicles to handle different traffic scenarios on the road like traffic signals, intersections, etc.

- Created an interactive client-server network using sockets in Python to stream 3D point cloud data from a RGBD camera and visualizing it on a webpage using Node.js
- Designed an end-to-end calibration pipeline product to complete Eye-to-Hand calibration and calculate the extrinsic parameters and the relative pose of a RGBD camera mounted on a robotic arm with respect to the end effector and base

18-793 Image and Video Processing

• Developing a Reinforcement Learning based framework under Prof. Carlee Joe-Wong to incorporate altruism in an Autonomous Vehicle Fleet in a mixed-autonomy environment to mitigate various problems faced on the road
• Experimenting with different network designs and other techniques to optimize and generalize the performance in mixed-autonomy transportation system and reach an equilibrium state so

• Worked under Professor Howie Choset
• Worked on developing a novel algorithm to solve Multi-Agent Path Finding problem using Deep Learning techniques
• Attempted to implement a learning-based Conflict Based Search (CBS) algorithm using Attention and Reinforcement learning
• Studied development of robust algorithms for path planning for multiple articulated manipulators using Deep Learning techni

• Wrote Python scripts to analyse simulator outputs and automate end-to-end timetable generation for coaching trains for the Indian Railways, resulting in improved train scheduling and reduced downtime by 75%
• Performed data clustering on more than 48,000 freight trains spanning over 6 major Indian Railway routes, to identify train timings and route patterns, thus optimizing resource allocation o

• Designed and back-tested quantitative trading algorithms in Python to maximize profits and cap losses to 10% of buying power
• Interpreted and analyzed large historical financial datasets to identify trading opportunities using statistical analysis and curated comprehensive reports to assist future strategic actions

• Intern for IoT Solutions for Remote Asset Monitoring
• Designed and fabricated temperature calibration circuits using Altium Designer for testing and generated the standard test set for prototype IoT devices
• Created the standard emulator on Raspberry Pi for testing and calibrating sensors for the Jio Vehicle Tracker IoT device

• Developed a 3-axes autonomous quadruped robot capable of following a line, climbing steps and jumping over ropes
• Designed prototypes for different orientations of the actuators in the mechanical structure
• Developed the navigation algorithm for the robot on a Computer Vision based - android application built using MATLAB

• Designed a robot based on the specified dimensions for the Fastest Line Follower Challenge
• Designed a micromouse robot with proper sensor and actuator placement for Maze Solving Competiton

Worked as Technical Team Member at DJS Robocon.

Pursued a Master of Science in Electrical and Computer Engineering, focusing on robotics and computer vision.