Rachit Nigam
Office: 32-G814
CSAIL researchers find even “untrainable” neural nets can learn effectively when guided by another network’s built-in biases using their guidance method.
This new approach could lead to enhanced AI models for drug and materials discovery.
A team of researchers has mapped the challenges of AI in software development, and outlined a research agenda to move the field forward.
Doctoral Thesis Title: Programmable Architectural Support for Diverse Sparse WorkloadsPresenter: Hyun Ryong “Ryan” LeePresenter’s Affiliation (CSAIL, RLE, LIDS, MTL, etc.): CSAILThesis Supervisor(s): Daniel Sanchez Date: 07/25/2025Time: 1PM Location if…
Name:Samuel Tenka Time:Wednesday, June 18, 4pm Room: 4-257 Zoom: https://mit.zoom.us/j/96397133905Password: cohobast Title: Geometric Aspects of Optimization and Representation in Learning Abstract: Machine learning combines methods in optimization, data-representation,…
Thesis Title: Next Generation Operating Systems for the Datacenter Presenter: Josh Fried Presenter’s Affiliation: CSAIL Thesis Supervisor: Adam Belay Date: April 1, 2025 Time: 3PM Location: 32-G882 (Hewlett)…
All promotions and appointments will take effect July 1, 2025.
Associate Professor Julian Shun develops high-performance algorithms and frameworks for large-scale graph processing.
The dedicated teacher and academic leader transformed research in computer architectures, parallel computing, and digital design, enabling faster and more efficient computation.