Daniel Jiang

PhD Student at the University of Washington

Google Scholar, LinkedIn


University of California, Berkeley
B.A., Computer Science with Honors, Concentration in Math


Industry Experience

Machine Learning Engineer, Amazon Search, Berkeley, CA

Worked on the science and infrastructure of machine learning methods for search that work on Amazon-scale.

Machine Learning Intern, Amazon Search, Palo Alto, CA

Investigated the use of latent space embedding methods to improve classifier performance for Amazon search. Also, investigated uses of kernel canonical correlation analysis (kCCA) to improve embeddings.

Software Intern, Cruise Automation, San Francisco, CA

Development of image segmentation models for self-driving car maps.

Software Intern, NASA, Greenbelt, MD

Development of a web app for space weather analysis and anomaly detection.

Research Experience

Undergrad Research Assistant, RISELab, UC Berkeley

Worked with PhD student Tijana Zrnic (co-advised by Michael Jordan and Moritz Hardt).
Research on algorithms for hypothesis testing with false discovery rate control.

Undergrad Research Assistant, Redwood Center for Theoretical Neuroscience, UC Berkeley

Worked with PhD student Brian Cheung (advised by Bruno Olshausen).
Research on biologically plausible algorithms for backprop-like credit assignment in artificial neural networks, sparse neural architecture search, and learning supervised embedding representations from unsupervised datasets.

Undergrad Research Assistant, ICSI Multimedia Group, UC Berkeley

Worked with PhD student Jaeyoung Choi (advised by Martha Larson) and Adjunct Professor Gerald Friedland.
Research on using word embedding distributions to detect bias in image datasets via learned image-text joint representations.

Posters and Presentations