One year ago, I decided to step back from work and focus on a Master’s degree to pivot my career toward an applied science path. I expected to take a year off, gain the skills I missed from the industry route, and learn what it means to be a scientist. I figured there was something I could learn to help me read and use the latest research techniques in an industry setting. At Georgia Tech, I ended up taking the following classes in order:

  • Artificial Intelligence
  • Artificial Intelligence Techniques for Robotics
  • Research for Thad Starner (Student cheating detection)
  • Introduction to Research
  • Machine Learning
  • Software Development Process
  • Game AI
  • Deep Learning
  • Natural Language Processing

Georgia Tech Metz

  • Computer Vision
  • Machine Learning for Robotics
  • Introduction to Research in Machine Learning, Robotics & Vision

Being back in school a second time, I was able to focus on learning and finish with a 4.0 GPA. This was one of my goals because I didn’t perform as well in my undergraduate degree over 10 years ago, and I wanted to prove to myself that it was because I hadn’t put in the time to focus on my classes. Classes focus on metrics and problem-solving; additional end-to-end skills are required and should be practiced beyond the classes themselves.

The highlight of my degree is studying abroad at Georgia Tech Metz in my final semester. Taking the three classes together allowed me to connect the learning from each other. My final research project involved using the KITTI-360 dataset, which provides stereo camera pairs and LiDAR data across multiple modalities. This meant I applied the knowledge from my CV class to transform LiDAR data into the camera frame, use the stereo pair to generate a disparity map, and then derive the corresponding depth map.

After a quick vacation, the current plan is to either seek a research lab for a PhD or return to industry with my current research skills and see how my newfound knowledge helps.