Duong Le
ML Researcher at Apple
Seattle, Washington, United States
Summary
👤
Senior🎓
Top SchoolDuong Le is an ML researcher based in Seattle with nine years of experience focused on computer vision, currently contributing to applied research at Apple. He progressed from research internships and academic labs into research roles at VinAI and the Allen Institute for AI, where he bridged predoctoral research and engineering to move models from prototype to production. His background includes geometric computation and high-performance computing, reflecting a blend of theoretical rigor and systems-level optimization. Duong has repeatedly worked in international research environments—from Tokyo and Singapore to Vietnam—indicating strong cross-cultural collaboration and rapid adaptation to new domains. He is comfortable navigating both academic and industry research pipelines, turning complex vision problems into deployable solutions. Less obvious: his trajectory shows a pattern of short, impactful stints that accelerate capability transfer between labs and product teams.
8 years of coding experience
6 years of employment as a software developer
Honors Program Bachelor of Engineering Computer Science, Honors Program Bachelor of Engineering Computer Science at Ho Chi Minh City University of Technology
Github Skills (19)
text-to-image9
convolutional-neural-networks9
mdp9
image-translation8
stochastic8
pipeline7
deep-learning6
diffusion-models6
sdk5
camera5
stable-diffusion4
visualize2
machine-learning2
pytorch2
computer-vision2
Programming languages (4)
Github contributions (5)
lehduong/Job-Scheduling-with-Reinforcement-Learning
May 2020 - Aug 2020
Learning in Noisy MDP (which is governed by stochastic, exogenous input processes) with input-dependent baseline
Contributions:1 release, 163 commits, 6 PRs in 2 months
exogenousstochasticnoisymdp
lehduong/Knowledge-Distillation-by-Replacing-Cheap-Conv
Jan 2020 - Apr 2020
In search of effective and efficient Pipeline for Distillating Knowledge in Convolutional Neural Networks
Contributions:268 commits, 12 PRs, 289 pushes in 2 months
pipelineknowledgedeep-learningeffectiveconvolutional
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