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Current Seminar Series

CSAIL Forum
Dertouzos Distinguished Lecture
Hot Topics in Computing
Algorithms and Complexity (A&C) 2024 - 2025
Algorithms and Complexity (A&C) 2025 - 2026
Bioinformatics Seminar Series 2025
Biomedical Imaging and Analysis 2024 - 2025
Boston IEEE/ACM 2024 -2025
Brains, Minds and Machines 2024 - 2025
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Cryptography and Information Security (CIS) 2025 - 2026
CSAIL Security Seminar 2024 - 2025
EECS Special Seminar
Embodied Intelligence 2024-2025
ML Tea
Theory of Computation (ToC) 2025 - 2026
Thesis Defense
Previous Seminar Series

July 20, 2025

No events scheduled

July 25, 2025

Thesis Defense: Programmable Architectural Support for Diverse Sparse Workloads - Ryan Lee

Part Of

Thesis Defense
1:00P
- 2:00P

Location

36-428
Add to Calendar 2025-07-25 13:00:00 2025-07-25 14:00:00 America/New_York Thesis Defense: Programmable Architectural Support for Diverse Sparse Workloads - Ryan Lee Defense Title: Programmable Architectural Support for Diverse Sparse WorkloadsSparsity is abundant in many workload domains, but presents challenges that results in under- utilization of the available resources in existing hardware. Sparse workloads exhibit irregular control-flow and long-latency memory accesses, starving the core of useful work, and perform fine-grained accesses leading to inefficient use of the available memory bandwidth.Prior work has proposed several software and hardware mechanisms to accelerate sparse workloads, but there has been a lack of a general technique that is applicable to the diverse set of applications in this domain. In particular, existing solutions have had limited support for workloads that concurrently read and update the underlying sparse data structure, such as dynamic graph applications and databases. Prior proposals have instead limited various dimensions of the applications they target in this space, such as restricting the formats they support (e.g., only hash tables) or constraining the types of concurrent operations (e.g., read- only), thereby limiting their applicability. In addition, prior work has insufficiently addressed the inefficient data transfer between compute and memory, instead opting to put expensive compute elements near memory or only supporting restricted forms of fine-grained accesses.This thesis shows that it is possible to design a general and programmable architecture that supports a wide range of sparse workloads. To this end, this thesis presents two hardware accelerators. First, Terminus adds a small hardware unit near each core that accelerate a wide range of data structures types and concurrent reads and updates to these structures, achieving a gmean of 7.4× speedup over a CPU baseline. Second, Gist enhances each DRAM chip with a flexible hardware unit that autonomously performs fine-grained scatter/gather operations for sparse workloads. This allows Gist to more efficiently use the memory bus by returning a compact stream of data, and achieves a gmean of 1.6× speedup over state-of-the-art support for sparse workloads.https://mit.zoom.us/j/8203717891Advisor: Professor Daniel Sanchez TBD

July 28, 2025

Bespoke Threat Models: Achieving Realistic Privacy Guarantees for Deployed Protocols

Kyle Hogan
MIT CSAIL
1:00P
- 3:00P

Location

32-G882
Hybrid
Add to Calendar 2025-07-28 13:00:00 2025-07-28 15:00:00 America/New_York Bespoke Threat Models: Achieving Realistic Privacy Guarantees for Deployed Protocols This thesis focuses on the question of what degree of privacy is achievable in the real world for long running applications. We explore this question in two main settings: anonymous communication and private advertising. In doing so we consider constraints each application may have in practice and what adversarial model is realistic for the context in which the application will be deployed.In the space of private advertising, we propose a novel protocol, Adveil, that eliminates leakage of user data beyond that revealed by the input/output of the ads ecosystem as a whole. We also provide a minimal modeling of the functionality of digital advertising which we use to prove that, even for systems like Adveil with minimal leakage, the advertising metrics released at the end of the protocol are sufficient to leak information about end users to advertisers when combined with their audience targeting criteria. TBD

September 23, 2025

Explicit Lossless Vertex Expanders

Rachel Zhang
CSAIL, EECS

Part Of

Theory of Computation (ToC) 2025 - 2026
4:15P
- 5:15P

Location

32-G449
Refreshments at 4:00 PM
Add to Calendar 2025-09-23 16:15:00 2025-09-23 17:15:00 America/New_York Explicit Lossless Vertex Expanders We give the first explicit construction of lossless vertex expanders. These are d-regular graphs where every small set S of vertices has (1-eps)d|S| distinct neighbors. Previously, the strongest known explicit vertex expanders were those given by Ramanujan graphs, whose spectral properties imply that every small set S of vertices has 0.5d|S| distinct neighbors.Based on joint work with Jun-Ting Hsieh, Ting-Chun Lin, Alex Lubotzky, Sidhanth Mohanty, Ryan O'Donnell, and Assaf Reiner. TBD
  • CSAIL Forum
  • Dertouzos Distinguished Lecture
  • Hot Topics in Computing
  • Algorithms and Complexity (A&C) 2024 - 2025
  • Biomedical Imaging and Analysis 2024 - 2025
  • Boston IEEE/ACM 2024 -2025
  • Brains, Minds and Machines 2024 - 2025
  • CIS Seminar 2024 - 2025
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  • ML Tea
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  • Thesis Defense
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