We develop algorithms, systems and software architectures for automating reconstruction of accurate representations of neural tissue structures, such as nanometer-scale neurons' morphology and synaptic connections in the mammalian cortex.
The challenge that motivates the ANA group is to foster a healthy future for the Internet. The interplay of private sector investment, public sector regulation and public interest advocacy, as well as the global diversity in drivers and aspirations, makes for an uncertain future.
This CoR brings together researchers at CSAIL working across a broad swath of application domains. Within these lie novel and challenging machine learning problems serving science, social science and computer science.
This CoR aims to develop AI technology that synthesizes symbolic reasoning, probabilistic reasoning for dealing with uncertainty in the world, and statistical methods for extracting and exploiting regularities in the world, into an integrated picture of intelligence that is informed by computational insights and by cognitive science.
This community is interested in understanding and affecting the interaction between computing systems and society through engineering, computer science and public policy research, education, and public engagement.
We develop techniques for designing, implementing, and reasoning about multiprocessor algorithms, in particular concurrent data structures for multicore machines and the mathematical foundations of the computation models that govern their behavior.
We build new protocols and architectures to improve the robustness and performance of computer networks. We develop practical solutions in wireless networks, network security, traffic engineering, congestion control, and routing.
(This project is no longer active.) The T-1000, a prototype system of a thousand realistic processors embedded throughout an ensemble of interconnected FPGAs, seeks to demonstrate the scalability of timestamp-based cache coherence protocols on distributed shared memory systems.
Our goal is to develop an adaptive storage manager for analytical database workloads in a distributed setting. It works by partitioning datasets across a cluster and incrementally refining data partitioning as queries are run.
Self-driving cars are likely to be safer, on average, than human-driven cars. But they may fail in new and catastrophic ways that a human driver could prevent. This project is designing a new architecture for a highly dependable self-driving car.
In order to be able to design synthetic organs that function autonomously, we will need to engineer artificial tissue homeostasis. To control the size of these artificial tissues, two major mechanisms will have to be engineered.
We propose a novel aspect-augmented adversarial network for cross-aspect and cross-domain adaptation tasks. The effectiveness of our approach suggests the potential application of adversarial networks to a broader range of NLP tasks for improved representation learning, such as machine translation and language generation.
BlueDBM is an architecture of computer clusters consisting of fast distributed flash storage and in-storage accelerators, which often outperforms larger and more expensive clusters in applications such as graph analytics.
As part of Data Civilizer we are designing abstractions and building tools and systems to help people with their data-related tasks, from discovering, to cleaning, to transforming it. The aim is to shape the data in a way that is easy to analyzer---for example to fit a model or fill in a report.
We aim to better understand the features of network protocols that facilitate denial of service attacks, in order to design more robust protocols and architectures in the future and evaluate existing designs more accurately.
MIT’s Amar Gupta and his wife Poonam were on a trip to Los Angeles in 2016 when she fell and broke both wrists. She was whisked by ambulance to a reputable hospital. But staff informed the couple that they couldn’t treat her there, nor could they find another local hospital that would do so. In the end, the couple was forced to take the hospital’s stunning advice: return to Boston for treatment.
Last week CSAIL principal investigator Shafi Goldwasser spoke about cryptography and privacy as part of the annual congressional briefing of the American Mathematical Society (AMS) and the Mathematical Sciences Research Institute (MSRI).
Anyone who’s downloaded an update to a computer program or phone app knows that most commercial software has bugs and security holes that require regular “patching.” Often, those bugs are simple oversights. For example, the program tries to read data that have already been deleted. The patches, too, are often simple — such as a single line of code that verifies that a data object still exists.