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hey there

I'm Lauren Zhu.
Always hunting for
my next life adventure.

About

More About Me

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.

My Work Experience.

June 2020 - September 2020

Apple Special Projects Group

Machine Learning Intern

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

Ford Greenfield Labs

Machine Learning Intern

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

University of Edinburgh

AI Researcher (NLP)

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

Qualcomm

Software Engineering Intern

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.

Things that Shape Me

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Stanford Jump Rope Team

I've been performing and competing with the Stanford Jump Rope team since my earliest days at Stanford. We do crazy flips and stunts, dance in double dutch, and jump on our butts!

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Stanford Women in Computer Science

This community has shaped my journey at Stanford both personally and professionally. As the Co-President my junior year, I had the honor of working with hundreds of women in CS that I admired.

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Wilderness photography

When I'm out in wild landscapes, I'm home. When the breeze grazes my cheeks, when the pine needles whistle above, when the water rumbles below. To capture the sublimity of nature is to inspire awe, to preserve the land.

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Recording Covers

During quarantine, I picked up the guitar to sing with and haven't put it down since. If I'm not working or hiking, odds are I'm learning the fingerstyle to a new song. Annie's song. Landslide. Cherry Wine.

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Searing Steaks

I grew up around Chinese food, but spent countless hours soaking up culinary knowledge from The Food Network. I find cooking to be a form of art, and love to apply my creativity to classic dishes and make them my own.

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Piano

While my competition days are behind me, nothing beats the expression that Liszt, Chopin, and Debussy had intended for their music. That these pieces retain their beauty and power for hundreds of years is a marvel.

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Travel

I am forever grateful for the opportunity to travel. To be a part of cultures that are not my own, places that I did not know, beauty I cannot comprehend. These experiences make for insane stories. These are the lessons extend beyond the classroom.

Portfolio

See My Latest Work.

Dive deep into my work, both professional and personal.

Recolorizing B&W Images

Computer Vision

Hinge Loss on CNNs to recolorize black and white landscape images.

AI Travel Itinerary Planning

Ant Colony Optimization

Ongoing project by Peggy and me! :)

Pixel 4 Pixel

Human Computer Interaction

In a collaboration with the Stanford HCI group on a project to build a digital self-tracking took, I implemented a grid detection algorithm using computer vision to extract colors from a hand-drawn grid.

University of Edinburgh

Neural Machine Translation

NLP research conducted at the University of Edinburgh under Professor Rico Sennrich.
Adversarial Training in Zero-Shot Multilingual Neural Machine Translation.

Question and Answering

Deep NLP

Extending Answer Prediction for Deep Bi-directional Transformers.

MAXQ: Autonomous Rockets

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.

Rendering a Scene

Computer Graphics

Testing my abilities as an interior designer and computer graphics engineer,
my partner and I created and rendered this scene using a Ray Tracer and Blender.

AXLES

BMW Collaboration

Senior project capstone, software project with BMW combining micro-gesture recognition and gaze tracking into an interesting use case for an autonomous vehicle. See Github wiki link for more information.

Vlog

Stanford @ Cinque Terre

Music

Coffee with Charlie

Cinematography

Central Coast of California

23

National Parks Visited

1200

Cups of Coffee

110

Projects Completed

570

Hugs Given

Contact

Say Hello!

Let's get in touch.
Just shoot me an email,
or connect with me on LinkedIn.

Location

Stanford University
Stanford, CA 94305

Email

laurenz@stanford.edu
laurenzhu@gmail.com