Formerly the Google Self-Driving Car Project

• Developed a workload management/scheduling system for allocating resources, handling up to 65.3% of the company workload

• Implemented the system API gateway using FastAPI and deployed using Nomad, passing stress tests with over 20k requests

• Designed to handle over 40k queries per minute using ElasticSearch, MySQL, Redis and RabbitMQ, and built a web front-end for visualization

• Built a license usage prediction system with an ensemble model of XGBoost regressors and LSTMs with a periodic accuracy monitor, mean absolute error as low as 0.39%; querying/posting data from/to Graphite and ElasticSearch, served using Nomad

10-301/601 Introduction to Machine Learning

• Authored a 44-page write-up on matrix calculus with exercises and full solutions, selected as one of the recommended extra readings for the course

• Participated actively in Piazza Q&A board with 1,309 total contributions; highest among all CMU MLD TAs in history

• Hosted office hours on topics including neural network, reinforcement learning, logistic regression, recommender system and Bayesian network

• Wrote/graded homework and exam questions on reinforcement learning and logistic regression

• Provided starter code and set up Gradescope autograder for programming assignments

Vision & Learning Lab

• Achieved up to a 32.9% recall score improvement in interactive image retrieval by devising a neural network with cycle consistency

• Designed a novel neural network for viewpoint-agnostic change captioning and attained an improvement of up to 15 points in common natural language processing metrics such as CIDEr

• Published papers at AAAI 2021 and ICCV 2021, and gave an hour long lab presentation on recent image retrieval works

• Collaborated with Hyundai Motor Company and completed funded research projects (value of approximately 240k USD)

• Implemented neural networks with PyTorch, and created a dataset for change captioning under viewpoint changes using Blender