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ML Research Engineer Vibe Researching Sunnyvale, CA

Writing & building ML systems that make models work.

ML engineer working across model iteration, machine learning systems, and AI-powered software. Long-running interest in bandits, reinforcement learning, OOD detection, and the practical infrastructure that makes production models tractable.

Research Focus: ML systemsmodel iterationOOD detectionbanditsAI software
01Writing
all writing ->
02Selected publications
google scholar ->
NeurIPS 2023 · main

Characterizing Out-of-Distribution Error via Optimal Transport

Yuzhe Lu, Yilong Qin, Runtian Zhai, Andrew Shen, Ketong Chen, Zhenlin Wang, Soheil Kolouri, Simon Stepputtis, Joseph Campbell, Katia Sycara

ICLR 2023 · workshop

Predicting Out-of-Distribution Error with Confidence Optimal Transport

Yuzhe Lu, Zhenlin Wang, Runtian Zhai, Soheil Kolouri, Joseph Campbell, Katia Sycara

AISTATS 2022 · main

Best Arm Identification with Safety Constraints

Zhenlin Wang, Andrew Wagenmaker, Kevin Jamieson

03Projects
github ->

needle

active

A Deep Learning framework with customized GPU and CPU backend in C++ and Python

c++pythoncuda
read code ★ 0 · 27 commits · ◷ 2y

Researched and developed a classifier-free guidance-based latent diffusion model for autonomous vehicle motion forecasting using UNet and Transformer as backbones

pytorchdiffusionautonomous vehicle
read codereport ★ 0 · 2 commits · ◷ 3y

A small D3.js-powered Satellite Tracking visualization

d3.jsjavascriptreact
read code ★ 0 · 7 commits · ◷ 3y

Travel-Planner

archived

A GPT-powered web application to help users automate travel plan suggestion, generation and archiving

gptgomysql
read codeslides ★ 0 · ◷ 3y