ligeng [at] mit (dot) edu
I am a Ph.D student at MIT, fortunately working with Prof. Song
Before coming to freezing Boston, I have lived in Hangzhou and Vancouver, where I was a member of Dual
Degree Program between Zhejiang University and Simon Fraser University.
My research interests focus on automated, scalable and efficient machine learning.
During my undergrade, I worked with Prof. Brian
Funt on colour vision, and Prof. Ping Tan on
If you find any research interests that we might share, feel free to drop me an email. I am always open
to potential collaborations.
/ Google Scholar
Delayed Gradient Averaging is going to appear on NeurIPS 2021.
Welcome to our poster session!
We are going to present IOS - Inter-Operator Scheduler at MLSys
2021. Welcome to stop by!
Distributed Training across the World
Neural Information Processing Systems (NeurIPS) Workshop on Systems for ML (MLSys),
Scale Synchronous SGD across the world, without loss of speed and accuracy!
Talks & Presentations
- [08/2019] AutoML for Efficient Neural Architecture Design (Slides)
@ OpenPower Summit, Polarr Tech
- [08/2019] Scalable and Secure Machine Learning for Edge Devices @ Qualcomm
- [05/2019] Neural Architecture Designs @ UIUC IFP Group (Slides)
- [12/2018] Proxylessly Specialize CNN for Hardware @ IBM-MIT Watson Events (Poster)
- [01/2018] Sparsely Aggregated Convolutional Networks (Slides)
@ UBC Vision Group, Deephi Tech, Sensetime Inc
- [11/2017] Invited lectures about deep learning
@ SFU Computer Vision Course (CMPT-412), ZJU Programming Group
Open-source Projects (Selected)
My life (both academic and daily) is greatly powered by open source projects. To thank their selfless
effort, I embrace open source as much as possible. Please refer to my github for a complete list of projects.
Review papers for:
ICCV 21 / ICML 21 / ACL 21 / NeurIPS 20 / CVPR 20 / AAAI 20 / NeurIPS 19 / ICCV 19 / CVPR 19
T-PAMI / IEEE Micro