To Prospective Students
Last update: 11/2024
I want to be a great advisor and believe that this can only happen if and only if:
- there is significant overlap between what you and I are excited about. So please take a look at my research group page, and think about what you feel passionate and highly motivated to work on. Your interests should align, or better yet, expand mine: one of the best things about being in graduate school is that you get to teach others knowledge that, before you, have never been discovered, and I am eager to learn from you things that I've never heard/thought of before.
- we actually like each other as well as what we are doing. To figure this out, we should communicate, and hopefully work together, before you fully join my group. The best way to do this is to start some informal collaboration before you apply/join. This can be taking on a small project of mutual interests or discussing papers you've been reading.
What We Do
Ultimately, our research mission is to 1) discover new sciences so we understand things that we previously don't, 2) build new engineering systems to do things that we previously couldn't, and 3) express art and comprehend art history through computational approaches.
Concretely, we do research at the intersection of imaging (optics + image sensors), cognition/perception (psychophysics and computational modeling), and computer systems (computer architecture and programming model). A common tool underlying many of our explorations is deep learning.
Below is a partial list of things that we are currently exploring:
- Computational art: expressing visual arts, comprehending art history, and exploring aesthetics (if you find some of these papers interesting and/or aren't completely convinved by this paper, let me know! if you are an artist and/or have worked in an art studio, definitely reach out!!)
- Understanding and modeling human visual system to build efficient Augmented and Virtual Reality devices (e.g., color perception-driven display and memory compression, foveated neural rendering).
- Deep learning-inspired neuroscience and neuroscience-inspired deep learning.
- Computer systems for robotics and Embodied AI (see our prior work on robotic computing systems).
- Tools/frameworks for automating computer architecture design and exploration (e.g., automatically inserting buffers in image processing accelerators, synthesizing robotic localization accelerators, accelerator design space exploration for neighbor search and Web applications).
- Assistive technologies (e.g., AR/VR-based) to augment human (visual) perception (e.g., computational treatment of color vision deficiency).
- Efficient and environment-friendly image sensing systems (see our modeling tool and a bespoke eye-tracking sensor architecture and algorithm).
- Optical computing stack for brain-scale simulation and computing.
Send an Email
If you've made this far, feel free to send me an email telling us why your interests align with ours and how you can contribute. Ideally, you will have read one of our recent papers and tell us what you think, e.g., insights you learn from the paper, things that you are not convinced, how you would have done things differently, etc.