# Rin Ha

> Robotics SW & ML @ Dusty Robotics

Location: San Jose, California, United States
Profile: https://flows.cv/rinha

## Work Experience
### Robotics Software Engineer @ Dusty Robotics
Jan 2024 – Present | Mountain View, California, United States

### Project Team Lead @ Wayfair
Jan 2023 – Jan 2024

### Machine Learning Researcher @ AMISTAD Lab
Jan 2022 – Jan 2024 | Claremont, California, United States
• Collaborating with 5 students to study the vectorization of inductive bias for ML regression algorithms for analysis and comparison of the biases of different algorithms using scikit-learn
• Problem-solving how to represent vectors of continuous search spaces into a discretely-sized vector
• Researching solutions using Kernel Density Estimation, Conditional Density Estimations, and Hashing Tricks

### Software Engineer Intern @ Dusty Robotics
Jan 2023 – Jan 2023

### Intro To CS Grutor @ Harvey Mudd College
Jan 2021 – Jan 2021
- Tutored for Mudd's Intro to CS class and helped students work through problems about Python lists, recursion, iterations, assembly, logic circuits, AI, and finite state machines

### Software Developer @ MuddSub - HMC RoboSub Team
Jan 2020 – Jan 2021
- Implemented and integrated pipeline for Teensy to interact with thrusters and sensors with summer research team
- Wrote documentation on using ROS and instructions for testing the robot for fellow members
- Designed GUI of the 2D simulation of RoboSub for future members to learn robotics programming
- Writing training scripts for multiple neural networks (MobileNet) using COCO dataset to test for potential usage
- Clustering 100 images using unsupervised learning methods of principal component analysis (PCA) and k-Means

### Research Intern @ Massachusetts Institute of Technology
Jan 2019 – Jan 2019 | Boston, Massachusetts, United States
Research Intern at Sinha Lab at MIT
Evaluation of  possible treatment for amblyopia (lazy eye)
 - Collected EEG data on brain activity in response to a flickering light while measuring the highest perceivable flickering frequency based on the subject’s testimonial. 
  - Analyzed EEG data (neural response) with Fast Fourier Transform using MATLAB to see if its peak component was still aligned with flickering frequency beyond perceivable limit.

### Software Intern @ nHansa
Jan 2018 – Jan 2018 | San Jose, California, United States
- Upgraded performance model for software interactions in avionics (electronic systems used on aircraft)
- Automated testing flow for 8 core processor in aircrafts to identify optimal configurations for memory cache in real time OS


## Education
### Bachelor's degree Candidate in Computer Science
Harvey Mudd College

### Lynbrook High School


## Contact & Social
- LinkedIn: https://linkedin.com/in/rin-ha

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Source: https://flows.cv/rinha
JSON Resume: https://flows.cv/rinha/resume.json
Last updated: 2026-03-31