I am a PhD student in CSAIL at MIT working with Jonathan Ragan-Kelley. My work focuses on domain specific programming and program optimization for image processing tasks. I work at the intersection of machine learning, graphics, compilers, and systems research. I am interested in designing systems that fuse domain specific knowledge in signal processing and high performance computing with machine learning. My goal is to build systems that make generating efficient and high quality signal processing applications for various hardware targets easy and accessible.
Before starting my PhD I completed a Masters in Computer Science at Carnegie Mellon and a year of research with Kayvon Fatahalian. I went to college at Dartmouth where I received a degree in Economics and minors in Computer Science and Chinese language and literature.
Searching for Fast Demosaicking Algorithms
Karima Ma, Michael Gharbi, Andrew Adams, Shoaib Kamil, Tzu-Mao Li, Connelly Barnes, and Jonathan Ragan-Kelley. 2022. Searching for Fast Demosaicking Algorithms. ACM Trans. Graph. Just Accepted (December 2022). DOI:https://doi.org/10.1145/3508461
Learning to optimize halide with tree search and random programs
Andrew Adams, Karima Ma, Luke Anderson, Riyadh Baghdadi, Tzu-Mao Li, Michael Gharbi, Benoit Steiner, Steven Johnson, Kayvon Fatahalian, Fredo Durand, and Jonathan Ragan-Kelley. 2019. Learning to optimize halide with tree search and random programs. ACM Trans. Graph. 38, 4, Article 121 (August 2019), 12 pages. DOI:https://doi.org/10.1145/3306346.3322967
Efficient automatic scheduling of imaging and vision pipelines for the GPU
Luke Anderson, Andrew Adams, Karima Ma, Tzu-Mao Li, Tian Jin, and Jonathan Ragan-Kelley. 2021. Efficient automatic scheduling of imaging and vision pipelines for the GPU. Proc. ACM Program. Lang. 5, OOPSLA, Article 109 (October 2021), 28 pages. DOI:https://doi.org/10.1145/3485486