We can also purchase your own GPU workstation if needed. Before (as well as after) joining our lab, you can negotiate to purchase your own GPU workstation. NUS and NUS CS have shared GPU clusters, but it is convenient to have your own GPU workstation depending on your research style. We will try our best to avoid the situation where the computational resource is the bottleneck of our research, by accommodating the needs for computational resources as much as possible.
Our lab will aim to publish impactful works in top conferences in deep learning (NeurIPS, ICLR, ICML, CVPR, AAAI, etc,) as well as top journals in computational physics and applied mathematics. Funding will be available for travel to conferences.
To advance deep learning and the understanding of intelligence, our lab collaborates with researches at MIT, Harvard University, Brown University, Stanford University, Google, and other top institutes around the world.
I am open to co-advising PhD students at NUS.
Lab members can also expect...
Sponsorship to attend international conferences (NeurIPS, ICLR, ICML, etc.)
Flexibility in choosing research themes and topics.
Assistance with obtaining internships, postdoc positions and faculty positions.