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Robin Lin



ECE/CS Student @ Cornell University | SDE @ Amazon Robotics



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Résumé

About Me

👋 Hey, I'm Robin! I recently graduated Magna Cum Laude from Cornell University with a B.S in Electrical and Computer Engineering (ECE).


I am currently a Software Development Engineer at Amazon Robotics. My focus is embedded firmware for robotic sensor technologies.


I am always excited to make an impact on society and work on novel problems in the field of machine learning, robotics, and embedded systems engineering. If you have any interesting work opportunities, please feel free to email me at zl755@cornell.edu or contact me here!


🦿 Software Development Engineer • Amazon Robotics • Full-time

🦾 Embedded Software Development Engineer (SDE) Co-op • Amazon Robotics • Fall 2021

📱 Software Engineering Intern • Apple • Summer 2021

🚗 Research Intern • Cornell University Autonomous Systems Lab • Spring 2021

💻 Systems Engineering Intern • Uber Advanced Technologies Group • Summer 2020



Skills

Robotics: Motion Planning (rapidly-exploring random tree, potential field methods, visibility graph path planning) • Forward/Inverse Kinematics • State Estimation (dead reckoning, kalman filtering/linear quadratic estimation, extended kalman filtering, particle filtering) • Mapping (occupancy grid mapping)


Software Development: C/C++ • Python • Swift • Java • JavaScript • HTML • CSS • React • Node.js • Flask • SwiftUI • AWS • Firebase • Postman • AWS


Machine Learning: Tensorflow • Keras • PyTorch • Scikit-learn

Experience

Amazon Robotics

Embedded SDE I

  • Working within the Sensor Firmware Team.

Space Systems Design Studio

Research Intern

  • Developing flight software for Alpha CubeSat, a rapidly developed, low-cost 1U CubeSat mission to verify the performance of a highly retroreflective material for light-sail propulsion.
  • To learn more about this project, please visit Alpha CubeSat.

Amazon Robotics

Embedded Firmware Co-op

  • Developing calibration, visualization, and sensor capture scripts for key drive unit sensor technologies including GMSL-based stereo cameras, LiDAR, and radar sensors using Python, C, and Bash.
  • Developing new features for device applications and drivers in an embedded Linux environment using C.
  • Leading an effort to improve testing and QA across Brazil-build enabled codebase, integrating Pytest for unit/regression testing for internal linear algebra library and Amazon S3 datastore functionality.

Apple

Software Engineering Intern

  • Developed a Deep Reinforcement Learning based game application on Apple’s hardware using Swift.
  • Implemented an experimental feature for Automatic Differentiation in the Swift Compiler.

Cornell University Autonomous Systems Lab (ASL)

Research Intern

  • Trained and benchmarked Pyramid Stereo Matching Network on Argoverse tracking datasets.
  • Developed pre-processing scripts for stereo camera disparity regression and point cloud to disparity transformations.
  • Developed a novel shared encoder neural network architecture for Joint Translation-Stereo Learning using PyTorch.

Uber Advanced Technologies Group

Perception Development Test Engineering Intern

  • Developed SDV Data Collection Analysis automation tooling.
  • Utilized GraphQL to extract metadata from mission specialists during road data collection.
  • Implemented Google Sheets API for automated spreadsheet reporting of metadata occurrences.
  • Reduced data analysis time from 4 hours to 10 minutes.
  • Tools/Technologies: Python, GraphQL, Google Sheets API.

Department of Electrical and Computer Engineering - UofT

Research Intern

  • Photonics researcher working on a numerical solver for four-wave mixing, a third-order nonlinear effect in nonlinear fibre optics.
  • Supervised by Professor Helmy in the Department of ECE at UofT.
  • The source code for the project can be accessed here.
  • My report for this project can be downloaded here.
  • To learn more about the work done at my lab, please visit Photonics @ University of Toronto.

Department of Physics - NUS

Research Intern

  • Photonics and optics researcher studying the effects of "quenching" on the fluorescence lifetimes of nanodiamonds.
  • Developed a time-resolved photoluminescence spectroscopy (TRPL) system based on time-correlated single photon counting.
  • My presentation at the annual UofT engineering research event can be accessed here.

Sherman Health Science Research Centre – York University

Research Intern

  • Developed an Arduino-based foot-mounted inertial navigation device for localization without the use of GPS.
  • Developed sensor acquisition and fusion algorithm for dead reckoning and state estimation.
  • Designed schematics of onboard circuitry for Bluetooth, magnetometer, accelerometer, and gyroscope modules.

Education

Cornell University

August 2019 - May 2022

B.S in Electrical and Computer Engineering (ECE), Minor in Computer Science

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