I'm a recent Stanford Grad and am currently pursuing my MS in Computer Science. I'm all about building impactful Artificial Intelligence, empowering women in tech, wilderness photography, singing and guitar, world travel, entrepreneurship, and fashion.
June 2020 - September 2020
Deep Learning—data sampling to improve performance on state-of-the-art stack. Collaborated with core engineering team on several PRs. Refactored and improved evaluation pipelines to increase compute and dev efficiency.
June 2019 - September 2019
Worked on autonomous vehicles, building an LSTM system using vehicle sensor data for an enhanced driving experience. As a bonus, my team won the company hackathon with a road quality monitoring/mapping system.
June 2018 - August 2018
Worked on Zero-Shot Multilingual Neural Machine Translation under Professor Rico Sennrich, and designed a neural network discriminator that used an adversarial objective function to universalize language representations during training.
June 2017 - September 2017
Computer vision and deep learning for object detection on a mobile platform. Using Caffe, trained deep learning frameworks from scratch to build gun detection capabilities on mobile. Achieved high accuracy on both gun and VOC classes in the same model.
Dive deep into my work, both professional and personal.
Reinforcement Learning
This paper aims to solve both a hierarchical reinforcement learning task and a collision avoidance problem for an autonomous rocket in a field of asteroids. This problem is modeled as a Markov decision process and uses the MAXQ decomposition and MAXQ-0 learning algorithm which are compared against Flat Q-learning.
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Stanford University
Stanford, CA 94305
laurenz@stanford.edu
laurenzhu@gmail.com