Ji Lin
PhD Candidate
Cambridge, England, United Kingdom
Summary
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RockstarJi Lin is a PhD candidate and seasoned machine learning engineer with a decade of experience focused on efficient video understanding and model optimization. Based in Cambridge, UK, Ji has contributed to influential open-source work at MIT’s Han Lab, notably enhancing the ICCV‑2019 Temporal Shift Module with non-local variants, in-place temporal shifts, pretrained models, and an online demo for practical evaluation. Their contributions show a knack for bridging research and production—fixing training issues like weight decay and delivering pretrained assets for Kinetics and Sth‑Sth benchmarks. Ji combines deep academic rigor with hands-on engineering, consistently improving model performance and usability for the broader ML community.
10 years of coding experience
Github Skills (8)
computer-vision10
pytorch10
machine-learning10
video-understanding10
python9
acceleration9
faster-rcnn8
mask-rcnn8
Programming languages (4)
Github contributions (5)
mit-han-lab/temporal-shift-module
Mar 2019 - Aug 2021
[ICCV 2019] TSM: Temporal Shift Module for Efficient Video Understanding
Role in this project:
ML Engineer
ML EngineerContributions:36 commits, 5 PRs, 36 pushes in 2 years 5 months
Contributions summary:Ji contributed to the development and enhancement of the Temporal Shift Module (TSM) for efficient video understanding. They added non-local TSM models trained on Kinetics, an in-place version of the temporal shift, and pretrained models for Kinetics and Sth-Sth datasets. Furthermore, the user fixed weight decay issues and added an online demo for the TSM model. Their work primarily focused on improving model performance and providing practical tools for video analysis.
video-understandingaccelerationlow-latencytemporal-modelingefficient-model
mit-han-lab/tinyml
Mar 2021 - Jun 2022
Contributions:14 commits, 1 PR, 15 pushes in 1 year 2 months
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