2019September
Present
- Implementing DESIRE trajectory prediction deep neural network in PyTorch to provide lab baseline accuracy metric
- Preprocessing data using NumPy, programming RNN encoder-decoder, CVAE, CNN, and feature-pooling modules, training neural network, and tuning hyperparameters to improve trajectory prediction performance
- Developed Jenkins integration test framework to run autonomous vehicle perception and control software in simulation using Docker
2020May
2020August
- Converted existing CMake build framework to Bazel for autonomous vehicle platform code, improving modularity and decreasing build times for downstream customers
- Wrote Bazel packaging rules and integrated them into CI/CD pipeline, automating packaging and enabling code delivery
2020January
2020February
- Automated building and Docker containerization of Windows to Linux application translation tool
- Integrated automatic tool into downstream CI/CD pipelines, eliminating manual upkeep requirement, improving developer efficiency, and increasing build reliability for customer-facing applications
2019June
2019August
- Trained CNN-based trajectory maneuver classification system for autonomous vehicles using Keras/TensorFlow
- Developed Airflow workflow pipeline in Python to automate company's data generation and customer delivery process
- Overhauled company software testing framework and constructed new Jenkins regression test system
2018October
2019May
- Designed software that enabled quadcopter to perform precision landing in GPS-denied environments
- Programmed Python flight stack capable of control, visual odometry, and sensor processing
2019January
2019February
- Implementing DESIRE trajectory prediction deep neural network in PyTorch to provide lab baseline accuracy metric