ligeng [at] mit (dot) edu
I am a Ph.D student at MIT, fortunately working with Prof. Song
Before coming to freezing Boston (not that cold recent days), 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 efficient designs for edge computing.
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
Latest update on Nov 1 2022.
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:
NeurIPS 22 / CVPR 22 / NeurIPS 21 / ICCV 21 / ICML 21 / ACL 21 / NeurIPS 20 / CVPR 20 / AAAI 20 / NeurIPS 19 / ICCV 19 / CVPR 19
T-PAMI / IEEE Micro