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Research Projects

Bioinformatics & Functional Genomics

The new era of large-scale experimental methods in molecular biology has transformed it into an information-based science, making bioinformatics an integral part of genomic research. The research focus of the Laboratory of Bioinformatics and Functional Genomics is the development of integrated computational and experimental technologies for the study of gene function and regulation in biological systems through analysis, modeling, and visualization of heterogeneous biological data. The is is a joint laboratory with the Department of Computer Science and the Lewis-Sigler Institute for Integrative Genomics.

Faculty and Graduate Students: Olga Troyanskaya
Research Areas: Computational Biology

CASS: Content-Aware Search System

This project investigates how to build an efficient, high-quality content-based similarity search engine for feature-rich (non-text) data, which has dominated the increasing volume of digital information. The research topics include sketch construction, indexing for similarity search, distance functions for different feature-rich data types, integration with attribute-based search tools, content-addressable and searchable storage system, and Memex systems. The current toolkit is used to construct search systems for four data types including audio recordings, digital photos, 3D shapes, and genomic micro-array data.

Faculty and Graduate Students: Moses Charikar, Perry Cook, Kai Li, Olga Troyanskaya
Research Areas: Systems

CertiCoq: Principled Optimizing Compilation of Dependently Typed Programs

The CertiCoq project aims to build a proven-correct compiler for dependently-typed, functional languages, such as Gallina—the core language of the Coq proof assistant. A proved-correct compiler consists of a high-level functional specification, machine-verified proofs of important properties, such as safety and correctness, and a mechanism to transport those proofs to the generated machine code. The project exposes both engineering challenges and foundational questions about compilers for dependently-typed languages.

Faculty and Graduate Students: Andrew Appel, Olivier Savary Belanger, Zoe Paraskevopoulou

Computational Molecular Biology

My group develops algorithms for a diverse set of problems in computational molecular biology. We are particularly interested in predicting specificity in protein interactions and uncovering how molecular interactions and functions vary across context, organisms and individuals. We leverage high-throughput biological datasets in order to develop data-driven algorithms for predicting protein interactions and specificity; for analyzing biological networks in order to uncover cellular organization, functioning, and pathways; for uncovering protein functions via sequences and structures; and for analyzing proteomics and sequencing data. An appreciation of protein structure guides much of our research.

Faculty and Graduate Students: Mona Singh, Dario Ghersi, Borislav Hristov, Shilpa Nadimpalli Kobren, Pawel Przytycki, Joshua Wetzel
Research Areas: Computational Biology

Computational Neuroscience

The Seung Lab uses techniques from machine learning and social computing to extract brain structure from light and electron microscopic images.

Faculty and Graduate Students: Sebastian Seung
Research Areas: Machine Learning

Cryptocurrencies and blockchains

Cryptocurrencies and blockchains

Faculty and Graduate Students: Arvind Narayanan

Enterprise and data-center networks

Enterprise and data-center networks

Faculty and Graduate Students: Jennifer Rexford
Research Areas: Systems

Epigenome-wide association studies

We are currently developing methods for performing epigenome-wide scans for association of methylation status with phenotypes of interest.

Faculty and Graduate Students: Barbara Engelhardt
Research Areas: Computational Biology

Eyewire

EyeWire is a game to map the brain from Seung Lab at MIT. Anyone can play and you need no scientific background. Over 130,000 people from 145 countries already do. Together we are mapping the 3D structure of neurons; advancing our quest to understand ourselves.

Faculty and Graduate Students: Sebastian Seung
Research Areas: Computational Biology

Fairness and ethics in computing

Fairness and ethics in computing

Faculty and Graduate Students: Arvind Narayanan
Research Areas: Policy, Security & Privacy

FCMA: Full Correlation Matrix Analysis of Human Brains

FCMA: Full Correlation Matrix Analysis of Human Brains

Faculty and Graduate Students: Kai Li
Research Areas: Computational Biology

Geo-replicated cloud storage

Scalable causal consistency for wide-area data replication

Faculty and Graduate Students: Michael Freedman
Research Areas: Systems

ImageNet

ImageNet is an image database organized according to the WordNet hierarchy (currently only the nouns), in which each node of the hierarchy is depicted by hundreds and thousands of images. Currently we have an average of over five hundred images per node. We hope ImageNet will become a useful resource for researchers, educators, students and all of you who share our passion for pictures.

Faculty and Graduate Students: Kai Li

Internet architecture

Internet architecture

Faculty and Graduate Students: Jennifer Rexford
Research Areas: Systems

Internet policy

Internet policy

Faculty and Graduate Students: Jennifer Rexford
Research Areas: Systems

Least-privilege web services

Inferring and Enforcing Security Policies in Web Applications

Faculty and Graduate Students: Michael Freedman
Research Areas: Security & Privacy

Liberty Research

The Liberty Computer Architecture Research Group exploits unique opportunities exposed by considering the interaction of compilers and architectures to increase performance, to improve reliability, to reduce cost, to lower power, and to shorten the time to market of microprocessor systems. This objective is accomplished by providing critical computer architecture and compiler research, expertise, and prototypes to the community.

Faculty and Graduate Students: David August
Research Areas: Computer Architecture

Natural Algorithms

For much of my professional life, designing algorithms had been my thing. Then, one day, I watched a majestic flock of geese fly over Carnegie Lake and it dawned upon me that it had been their thing, too. Having been at it for 100 million years, even longer than I had, naturally their algorithmic genius surpassed mine. Undaunted, I resolved to catch up. The premise of my current research is that interpreting biological or social self-organized systems as "natural algorithms" brings upon them a fresh, new perspective ripe for inquiry. I believe that only the algorithm has the expressive power to model complex self-adaptive systems at the right levels of abstraction. Algorithms are the differential equations of the 21st century. Beyond its trite catchiness, this line serves to remind us that mankind's grasp of PDEs vastly exceeds its mastery of algorithms. The first order of business, therefore, is to build new analytical tools for natural algorithms.

Faculty and Graduate Students: Bernard Chazelle
Research Areas: Theory

Network Programming and Verification

The Network Programming Initiative supports research on languages, algorithms, and tools for network programming, and facilitates closer interactions with partners in industry and government.

Faculty and Graduate Students: Aarti Gupta, Jennifer Rexford, David Walker

Painting with Triangles

Although vector graphics offer a number of benefits, conventional vector painting programs offer only limited support for the traditional painting metaphor. We propose a new algorithm that translates a user’s mouse motion into a triangle mesh representation. This triangle mesh can then be composited onto a canvas containing an existing mesh representation of earlier strokes. This representation allows the algorithm to render solid colors and linear gradients. It also enables painting at any resolution. This paradigm allows artists to create complex, multi-scale drawings with gradients and sharp features while avoiding pixel sampling artifacts.

Faculty and Graduate Students: Adam Finkelstein

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