Daniel J Wu's CV

Summary

Student at Stanford University interested in solving big problems in medicine with machine learning.


Education

Stanford University

BS: CS and Math, 2021


Professional Experience

Jun 2020 to Dec 2020
New York City, New York

Quantitative Research Intern

Built traditional and deep-learning models for the prediction of index futures from large newsfeeds.



Dec 2019 to Present
Stanford, California

Computer Vision Research Fellow

I work on various projects with the Partnership on AI-assisted care. Using pytorch, we build at-home elderly care systems for automated health monitoring. We are also making advances in differential privacy and federated learning.



Sep 2018 to Present
Stanford, California

Machine Learning Research Fellow

Developing LSTMs and CNNs with Keras on TensorFlow, with gait accelerometry. Used to predict demographic information and cardiovascular risk for 50k+ iOS users.



Jun 2019 to Sep 2019
Redwood City, California

Machine Learning Intern

Implemented, trained, and shipped custom deep neural networks for gait identification in Tensorflow, which outperformed previous models by 20%. Developed model ensembling strategies which decreased error by 80%.



Jun 2017 to Sep 2018
Bethesda, Maryland

Research Fellow

Built an agent-based Python model of carcinogenesis, to target emergent processes with adaptive therapy. Model published and used to inform Phase I clinical trials.



Sep 2015 to Jun 2017
Orlando, Florida

Research Intern

Built epidemiological models of Zika spread in Florida in Python, used to inform pest control.



Jun 2016 to Sep 2016
Tampa, Florida

Research Intern

Built MatLab models to optimize adaptive therapy protocols. Models used to determine dosing in a clinical trial on late-stage prostate cancer.




Extracurriculars

Sep 2018 to Present

Organized AI workshops for the Stanford community.



Developed and pitched Pango, a gamified online reviews platform for doctors, to pre-seed VCs. Organized ASES Summit 2018, a week-long bootcamp for international entreprenuers.



Sep 2018 to Sep 2019

Competed in British Parliamentary and Policy, at several national and international tournaments.



Sep 2018 to Present

Awarded Arete Fellowship, organized critical thinking workshops and talks.




Volunteering and Outreach

Jan 2019 to Present

Cotaught CS 106S: Computer Science for Social Good, and CS 21SI: AI for Social Good.




Skills

Domains

Oncology Gait Cardiology Generative Modelling Computer Vision Deep Learning

Languages

Python Javascript Java C++ MatLab

Mobile

Android (Kotlin) React Native

Awards

USA Biology Olympiad, 2017

National Finalist, Silver Medalist

Ranked 6th in the nation of all high schoolers in the field of biology.


Regeneron Science Talent Search, 2018

National Semifinalist

Ranked in the top 300 in the nation's premier high school science research competition.


Japan Sustainable Innovation Hackathon, 2018

Grand Prize

Designed and pitched a ML aggregator for tsunami mitigation and reconstruction.


Stanford Social Impact Hackathon, 2018

3rd Place

Built Android app with Kotlin for crowdsourced reporting of human trafficking in the Bay Area.


Treehacks, 2019

Best Health Data Hack

Built LiveWell, a Firebase enabled React Native app for assisting refugees find clean water. Accepted to Coding it Forward's Build accelerator.


Treehacks, 2020

Most Ethically Engaged Hack, Best Computer Vision for Medical Access Hack

Built Soteria, a privacy-preserving telemedicine platform for refugees


HCL Better Health Hackathon, 2020

Best Medical Treatment Hack

Built Protego, a logistics platform for predictive allocation of medical supplies to nursing homes impacted by coronavirus.



Publications

Wu, Daniel J and Aktipis, Athena and Pepper, John W
Evolution, Medicine, and Public Health , vol. 2019 , no. 1 , pp. 9-16. , 2019. doi: 10.1093/emph/eoz004


Wu, Daniel J and Datta, Avoy and Prabhu, Vinay U
Proceedings of Workshop on Practical Machine Learning for Developing Countries at ICLR . , 2020.


Wu, Daniel J and Yang, Andrew C and Prabhu, Vinay U
Proceedings of Workshop on Practical Machine Learning for Developing Countries at ICLR . , 2020.


Wu, Daniel J and Badamjav, Odgerel and Reddy, Vikrant V and Eisenberg, Michael, and Behr, Barry
Asian Journal of Andrology , vol. 2020 . , 2020. doi: 10.4103/aja.aja_66_20