Jesse Doan

Biography Picture 

B.S. in Computer Science, Dec 2021
Stanford University

M.S. in Computer Science, June 2022
Stanford University

E-mail: jesseqd [AT] alumni [DOT] stanford [DOT] edu

About me

I graduated from Stanford University in 2022 with a Bachelor's and a Master's in Computer Science with specializations in Theory and Artificial Intelligence, respectively. Currently, I am a Machine Learning Engineer at Nuro on the Machine Learning Research team. My focus is on leveraging technology to support innovative solutions to challenging problems, including K-12 education.

During my time at Stanford, I served as a Section Leader for the introductory Computer Science courses through the Stanford Computer Science Department. In 2018 and 2019, I co-organized Stanford ProCo, a computer programming contest for high school students.

Some of the projects that I have completed at Stanford include a low-level Smart Mirror, AI Agents for Ultimate Tic-Tac-Toe (poster), Learned Hash Index (paper, slides), Student Ability Growth Estimator (SAGE) (website), and Active Tutored Learning Through Adaptive Systems (ATLAS) (paper, slides).

Throughout middle and high school, I founded and organized the Maui Math Challenge, an annual elementary school math contest aimed at teaching problem-solving skills and sparking interest in young minds to excel in math. In addition, I have published two math competition books for beginning mathletes. My ultimate goal is to equip students with the problem-solving skills that are needed to solve the challenges of the 21st Century.

Experience

Nuro

Machine Learning Engineer (Sept 2022 - Present)
Nuro is a leading autonomous vehicle company. Our mission is to better everyday life through robotics and strengthen local communities with our electric, zero-occupant autonomous delivery vehicles.

MITRE

Graduate Machine Learning and Software Engineering Intern (June 2021 - Sept 2021)
MITRE is a not-for-profit organization that manages federally funded research and development centers (FFRDCs) supporting various U.S. government agencies in the aviation, defense, healthcare, homeland security, and cybersecurity fields, among others.

  • Developed a novel and efficient clustering algorithm to identify hotspots of activity from large mobility datasets

  • Implemented algorithm at scale using existing open-source and in-house data analysis libraries, including Google’s S2 Geometry, used to tile the surface of the earth into grid cells

  • Evaluated algorithm’s performance on Microsoft’s GeoLife dataset, containing 17,621 GPS datapoints from 182 users over a span of 3 years, achieving a runtime of 3 minutes

  • Obtained a 20x runtime speedup and improved scores by 30% from baseline DBSCAN algorithm

TeacherPrints

Machine Learning and Software Engineering Intern (May 2021 - July 2021)
TeacherPrints is a free instructional coaching app that utilizes personalized, data-driven visualizations to help teachers bring the reality of their lesson delivery in line with their expectations and goals.

  • Fixed model output data pipeline with Django/Docker

  • Engineered Design/Prototype of Teacher Portfolio

  • Implemented ML application of Speaker Diarization, which tracks unique speakers throughout an audio file

Computational Education Lab

Research Assistant (Mar 2019 - Dec 2019)

  • Work on TinyFeedback, an individually designed project focused on providing quick, incremental feedback for student teachers in introductory computer science courses

  • Design and run an experiment to test out hypotheses based on education research and a prior exploratory study

  • Develop a web development tool to facilitate TinyFeedback

Coursework

Computer Science Depth - Artificial Intelligence

Computer Science Depth - Theory

Computer Science Core + Breadth

Education

Engineering and Math

Publications

  • Doan, Jesse. For The Rising Math Olympians. Createspace Independent Publishing Platform, 2016. Print. (Amazon, website)

  • Doan, Jesse and Steven Doan. Elementary School Math Contests. Createspace Independent Publishing Platform, 2017. Print. (Amazon)

Teaching

Other Links

LinkedIn
Résumé