Min Lin
Founding Scientist, Head Of AMI Labs Singapore at AMI - Advanced Machine Intelligence
Singapore
Summary
🤩
Rockstar🎓
Top SchoolMin Lin is a founding scientist and head of AMI Labs Singapore with 13 years of experience building and scaling production-grade machine learning systems across industry and academia. Previously she led research at Sea and conducted postdoctoral research at Mila, bringing a strong blend of applied research and product-focused delivery. Her technical contributions to high-profile open-source projects like Caffe and MXNet include low-level convolutional and symbolic API work, and she added performance and CI/DevOps improvements to RL infrastructure such as EnvPool. Trained with a PhD in Computer Science from NUS and a BS in Biology from Peking University, she combines rigorous theoretical grounding with a biology-informed systems perspective. Min is known for translating research prototypes into deployable platforms and for hands-on engineering that tightens the loop between model design and production performance. Colleagues value her ability to bridge research, engineering, and operational concerns to ship impactful AI systems.
13 years of coding experience
7 years of employment as a software developer
Bachelor of Science - BS, Biology/Biological Sciences, General, Bachelor of Science - BS, Biology/Biological Sciences, General at Peking UniversityDoctor of Philosophy (PhD), Computer Science, Doctor of Philosophy (PhD), Computer Science at National University of Singapore
Github Skills (27)
symbolic-computation10
caffe10
convolutional-neural-networks10
c-language10
python10
api-design10
mxnet10
machine-learning10
deep-q-learning10
reinforcement-learning10
deep-learning10
bazel10
neural-network10
cuda10
computer-vision10
Programming languages (9)
Github contributions (5)
sail-sg/envpool
Nov 2021 - Jul 2022
C++-based high-performance parallel environment execution engine (vectorized env) for general RL environments.
Role in this project:
Back-end Developer & DevOps Engineer
Back-end Developer & DevOps EngineerContributions:36 reviews, 10 commits, 9 PRs in 8 months
Contributions summary:Min contributed to the core functionality of the EnvPool project, a C++-based high-performance parallel environment execution engine for reinforcement learning. They refactored the build process, switching from `pip_parse` to `pip_install` for dependency management. The user moved example code to a separate folder and added dynamic shaped array support. They also added a Dockerfile for building release wheels, demonstrating proficiency in CI/CD and build processes. Additionally, the user implemented XLA CustomCall interface for integration with JAX.
starcraftmahjongbox2dreductiongomoku
apache/mxnet
Jul 2015 - Jun 2016
Lightweight, Portable, Flexible Distributed/Mobile Deep Learning with Dynamic, Mutation-aware Dataflow Dep Scheduler; for Python, R, Julia, Scala, Go, Javascript and more
Role in this project:Back-end Developer
Back-end DeveloperContributions:51 commits, 19 PRs, 12 pushes in 11 months
Contributions summary:Min's contributions primarily focused on modifying the `symbol.h` and related files, suggesting involvement in the core API and structure of the MXNet library. The changes include interface definitions, class structure adjustments, and implementation details for the `Symbol` class and its associated components. The user's work directly impacts the fundamental building blocks of the deep learning framework, particularly its symbolic representation.
pythonschedulerdataflowmutationdata-science
Find and Hire Top DevelopersWe’ve analyzed the programming source code of over 60 million software developers on GitHub and scored them by 50,000 skills. Sign-up on Prog,AI to search for software developers.