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.
Our interests span quantum complexity theory, barriers to solving P versus NP, theoretical computer science with a focus on probabilistically checkable proofs (PCP), pseudo-randomness, coding theory, and algorithms.
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.
Automatic speech recognition (ASR) has been a grand challenge machine learning problem for decades. Our ongoing research in this area examines the use of deep learning models for distant and noisy recording conditions, multilingual, and low-resource scenarios.
We aim to base a variety of cryptographic primitives on complexity theoretic assumptions. We focus on the assumption that there exist highly structured problems --- admitting so called "zero-knowledge" protocols --- that are nevertheless hard to compute
We study the fundamentals of Bayesian optimization and develop efficient Bayesian optimization methods for global optimization of expensive black-box functions originated from a range of different applications.
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.
We aim to study the impact of computer-supported roleplaying in changing social perspectives of digital media users. Such media could take the form of videogames, VR systems, training software, and other types of interactive narrative technology.
Knitting is the new 3d printing. It has become popular again with the widespread availability of patterns and templates, together with the maker movements. Lower-cost industrial knitting machines are starting to emerge, but we are still missing the corresponding design tools. Our goal is to fill this gap.
Mixed-methods qualitative (interviews and coding) and computational (AI) approach to understanding relationships between social identities, cultural values, and virtual identity technologies (e.g., online profiles and avatars).
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.
ACM, the Association for Computing Machinery announced this week that MIT CSAIL PhD student ‘19 Jiajun Wu was selected for an honorable mention for his dissertation “Learning to See the Physical World.”
This week it was announced that MIT professor and CSAIL principal investigator Tomas Lozano-Perez has been awarded the 2021 IEEE Robotics and Automation Award for his “foundational contributions to robot motion planning and visionary leadership in the field.”
This week it was announced that MIT professor Armando Solar-Lezama has received a prestigious NSF award for junior faculty, to go towards a new project that could impact scientific discovery in domains as diverse as organic chemistry, RNA splicing and cognitive science.