Ryan Liem

Course Assistant ECE 385 at Illini EV Concept

Champaign, Illinois, United States
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Summary

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Rockstar
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Top School
Ryan Fu is a research scholar and MS/PhD candidate at UIUC specializing in energy-efficient, memory-centric mixed-signal VLSI accelerators that aim to overcome the von Neumann bottleneck for next-generation AI and communication workloads. With nine years of experience across research and engineering roles, he contributes to both academic projects (JUMP2.0/CUbiC PENDA, massive MIMO in-memory computing) and open-source ML tooling, improving ONNX export and refactoring cores in the widely used MMDetection codebase. A recipient of UIUC’s highest undergraduate honors and the CUbiC Undergraduate Research Excellence Award, he joined Professor Naresh Shanbhag’s group as an undergraduate and continued into graduate research. Born in Florida and raised in Xi’an and Shanghai, he brings a multicultural perspective to collaborative hardware-software co-design. Outside research he has competed at a national level in contract bridge, a background that hints at strategic thinking and disciplined teamwork.
code9 years of coding experience
bookHigh School Diploma, High School Diploma at SMAK 6 BPK PENABUR Jakarta
bookBachelor's degree in Computer Engineering, Semiconductor Engineering Minor, 4.0, Bachelor's degree in Computer Engineering, Semiconductor Engineering Minor, 4.0 at University of Illinois Urbana-Champaign
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Github Skills (8)

object-detection10
computer-vision10
pytorch10
onnx10
python10
sd-mmc10
faster-rcnn7
retinanet6

Programming languages (3)

JavaScriptJupyter NotebookPython

Github contributions (5)

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open-mmlab/mmdetection

Sep 2020 - Nov 2020

OpenMMLab Detection Toolbox and Benchmark
Role in this project:
userML Engineer
Contributions:13 reviews, 20 commits, 11 PRs in 2 months
Contributions summary:Ryan's contributions focused on refactoring and improving the codebase related to the integration of MMCV, addressing deprecated functions, and enhancing ONNX export functionality. They made changes to various files, including those related to model heads, testing, and core components of the framework. The user's work involved modifying existing code and adding functions to support the conversion of models into the ONNX format.
openmmlabobject-detectioninstance-segmentationfast-rcnnfaster-rcnn
RyanXLi/RyanXLi.github.io

Nov 2019 - Jun 2026

Xiang Li's personal website
Contributions:2 PRs, 67 pushes, 3 branches in 6 years 8 months
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