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Research Projects

3D Shape-Based Retrieval and Analysis

Our goal is to investigate issues in shape-based retrieval and analysis of 3D models. As a first step, we have developed a search engine for 3D polygonal models. The main research issues are to develop effective shape representations and query interfaces.

Research Areas: Graphics / Vision

Applications of data mining and mechanisms in healthcare

Applications of data mining and mechanisms in healthcare

Faculty and Graduate Students: Mark Braverman
Research Areas: Theory

Big data: anonymity, privacy, ethics

Big data: anonymity, privacy, ethics

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

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

Bitcoin and Cryptocurrencies

Bitcoin and Cryptocurrencies

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

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 / Networks

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

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
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

Computational universality vs. noise

Computational universality vs. noise

Faculty and Graduate Students: Mark Braverman
Research Areas: Theory

DecoBrush: Drawing Structured Decorative Patterns by Example

Structured decorative patterns are common ornamentations in a variety of media like books, web pages, greeting cards and interior design. Creating such art from scratch using conventional software is time consuming for experts and daunting for novices. We introduce DecoBrush, a data-driven drawing system that generalizes the conventional digital ``painting' concept beyond the scope of natural media to allow synthesis of structured decorative patterns following user-sketched paths. The user simply selects an example library and draws the overall shape of a pattern. DecoBrush then synthesizes a shape in the style of the exemplars but roughly matching the overall shape. If the designer wishes to alter the result, DecoBrush also supports user-guided refinement via simple drawing and erasing tools. For a variety of example styles, we demonstrate high-quality user-constrained synthesized patterns that visually resemble the exemplars while exhibiting plausible structural variations.

Faculty and Graduate Students: Adam Finkelstein
Research Areas: Graphics / Vision

Enterprise and data-center networks

Enterprise and data-center networks

Faculty and Graduate Students: Jennifer Rexford
Research Areas: Systems / Networks

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

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

Frenetic

Programming language for software-defined networks

Faculty and Graduate Students: Michael Freedman

Geo-replicated cloud storage

Scalable causal consistency for wide-area data replication

Faculty and Graduate Students: Michael Freedman
Research Areas: Systems / Networks

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

Interactive coding theory

Interactive coding theory

Faculty and Graduate Students: Mark Braverman
Research Areas: Theory

Internet architecture

Internet architecture

Faculty and Graduate Students: Jennifer Rexford
Research Areas: Systems / Networks

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