I am a third year undergraduate student at MIT currently studying Computer Science and Mathematics. I currently work in the Programming Systems Group (PSG) led by Michael Carbin, and I am supervised by Alex Renda. At PSG I have led both a project on Transformers that are invariant to variable renamings and an empirical investigation of the effect data dimensionality has on neural network prunability. I also work as a research scientist intern at MosaicML, where I am investigating efficient methods for LLM pretraining and inference.
In general I am interested in a variety of topics and happy to chat about anything ML related at all so reach out. I am currently focussing on the effect of pretraining data on models and also on systems speedups for ML.
You can find my resume here.
Zachary Ankner*, Rishab Parthasarathy*, Aniruddha Nrusimha, Christopher Rinard, Jonathan Ragan-Kelly, and William Brandon
Preprint
William Brandon, Aniruddha Nrusimha, Kevin Qian, Zachary Ankner, Tian Jin, Zhiye Song, and Jonathan Ragan-Kelly
Preprint
Zachary Ankner*, Naomi Saphra, Davis Blalock, Jonathan Frankle, Matthew L Leavitt
EACL 2024, Poster
J.Ryan Shue*, Eric Ryan Chan*, Ryan Po*, Zachary Ankner*, Jiajun Wu, and Gordon Wetzstein
CVPR 2023, Poster
Zachary Ankner*, Alex Renda, Gintare Karolina Dziugaite, Jonathan Frankle, and Tian Jin
NeurIPS 2022, ICBINB Workshop
Zachary Ankner*, Purvaja Balaji, Ye Zhu, Chun Keat Hiew, Patrick Wang, and Amar Gupta
International Journal of Pattern Recognition and Artificial Intelligence