Computer Science & Applied Math
Columbia University, School of Engineering ’23.
Email: [neil].[nie] at columbia.edu
Thanks for visiting my homepage. My name is Neil, a third-year undergraduate student studying computer science and applied math at Columbia University, School of Engineering. My background and interests are in computer vision, deep learning, robotics, and software engineering.
Returned to Apple as a software & algorithms intern on the CoreMotion fitness team.
Researcher at Columbia Artificial Intelligence & Robotics Lab, advised by Prof. Shuran Song, working on articulated object manipulation, computer vision, & embodied AI.
Teaching assistant for Computational Aspects of Robotics (COMS 4733) since the spring 2021. Teaching assistant for Artificial Intelligence (COMS 4701) spring 2022.
Returned to Apple as a software & algorithms intern on the CoreMotion fitness team. Invented a new multi-sensing fitness tracking algorithm.
Served as President and Software Engineering Lead for the Columbia University Robotics Club, leading the MATE ROV project and the autonomous vehicles project.
Worked at Apple as a software engineer & algorithms intern on the CoreMotion team. Invented a new multi-sensing algorithm (patent pending).
TEDxDeerfield Executive Committee member and TEDx speaker.
Here are a few of my passion projects. I documented the work and progress, and shared the open-source code on Github. You can visit my blog for more details.
Self-Driving Golf Cart
From 2017-2019, I have been developing a self-driving golf cart. From the drive-by-wire system to the autonomous navigation stack, every component was developed from the ground up to learn as much as possible about robotics, electrical engineering, software engineering, and machine learning. I also developed, trained, and deployed deep neural networks for behavioral cloning and semantic segmentation.
Robotic Arm Gripping System
The project focused on using deep learning, semantic segmentation, ICP, and RRT algorithms to build a complete robotic arm gripping system. The arm uses image segmentation to detect the objects in the bins, uses ICP for pose estimation, and plans paths around obstacles using RRT. (credit: COMS4733 @columbia. not open sourced)
I built a quadcopter and programmed a flight controller from the ground up. The biggest challenge was programming a PID controller for the Arduino with an IMU. Eventually, it was able to fly around and self-balance in the air.
Talks & Presentations
In the spring of 2017, I gave a TEDx talk about A.I. at Deerfield Academy. You can find my talk here on YouTube. I also served as an executive board member and event coordinator for TEDxDeerfield from 2017-2019.