Arlington, Massachusetts, United States
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About

Serial and occasionally parallel entrepreneur. Founder of three venture-backed startups:…

Articles by Richard

  • Identify and Manage the Honey-Badger Developer

    A few years back I read Rands' blog post about the Free Electron developer archetype: “the single most productive…

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  • Anthropic

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Publications

  • BayesDB: A probabilistic programming system for querying the probable implications of data.

    Is it possible to make statistical inference broadly accessible to non-statisticians without sacrificing mathematical rigor or inference quality? This paper describes BayesDB, a probabilistic programming platform that aims to enable users to query the probable implications of their data as directly as SQL databases enable them to query the data itself. This paper focuses on four aspects of BayesDB: (i) BQL, an SQL-like query language for Bayesian data analysis, that answers queries by averaging…

    Is it possible to make statistical inference broadly accessible to non-statisticians without sacrificing mathematical rigor or inference quality? This paper describes BayesDB, a probabilistic programming platform that aims to enable users to query the probable implications of their data as directly as SQL databases enable them to query the data itself. This paper focuses on four aspects of BayesDB: (i) BQL, an SQL-like query language for Bayesian data analysis, that answers queries by averaging over an implicit space of probabilistic models; (ii) techniques for implementing BQL using a broad class of multivariate probabilistic models; (iii) a semi-parametric Bayesian model-builder that auomatically builds ensembles of factorial mixture models to serve as baselines; and (iv) MML, a "meta-modeling" language for imposing qualitative constraints on the model-builder and combining baseline models with custom algorithmic and statistical models that can be implemented in external software. BayesDB is illustrated using three applications: cleaning and exploring a public database of Earth satellites; assessing the evidence for temporal dependence between macroeconomic indicators; and analyzing a salary survey.

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  • Towards a Streaming SQL Standard

    Proceedings of the VLDB Endowment

    This paper describes a unification of two different SQL extensions for streams and its associated semantics. We use the data models from Oracle and StreamBase as our examples. Oracle uses a time-based execution model while StreamBase uses a tuple-based execution model. Time-based execution provides a way to model simultaneity while tuple-based execution provides a way to react to primitive events as soon as they are seen by the system.

    The result is a new model that gives the user…

    This paper describes a unification of two different SQL extensions for streams and its associated semantics. We use the data models from Oracle and StreamBase as our examples. Oracle uses a time-based execution model while StreamBase uses a tuple-based execution model. Time-based execution provides a way to model simultaneity while tuple-based execution provides a way to react to primitive events as soon as they are seen by the system.

    The result is a new model that gives the user control over the granularity at which one can express simultaneity. Of course, it is possible to ignore simultaneity altogether. The proposed model captures ordering and simultaneity through partial orders on batches of tuples. The batching and the ordering are encapsulated in and can be modified by means of a powerful new operator that we call SPREAD. This paper describes the semantics of SPREAD and gives several examples of its use.

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  • Linear road: a stream data management benchmark

    VLDB '04 Proceedings of the Thirtieth international conference on Very large data bases

    This paper specifies the Linear Road Benchmark for Stream Data Management Systems (SDMS). Stream Data Management Systems process streaming data by executing continuous and historical queries while producing query results in real-time. This benchmark makes it possible to compare the performance characteristics of SDMS' relative to each other and to alternative (e.g., Relational Database) systems. Linear Road has been endorsed as an SDMS benchmark by the developers of both the Aurora [1] (out of…

    This paper specifies the Linear Road Benchmark for Stream Data Management Systems (SDMS). Stream Data Management Systems process streaming data by executing continuous and historical queries while producing query results in real-time. This benchmark makes it possible to compare the performance characteristics of SDMS' relative to each other and to alternative (e.g., Relational Database) systems. Linear Road has been endorsed as an SDMS benchmark by the developers of both the Aurora [1] (out of Brandeis University, Brown University and MIT) and STREAM [8] (out of Stanford University) stream systems.

    Linear Road simulates a toll system for the motor vehicle expressways of a large metropolitan area. The tolling system uses "variable tolling" [6, 11, 9]: an increasingly prevalent tolling technique that uses such dynamic factors as traffic congestion and accident proximity to calculate toll charges. Linear Road specifies a variable tolling system for a fictional urban area including such features as accident detection and alerts, traffic congestion measurements, toll calculations and historical queries. After specifying the benchmark, we describe experimental results involving two implementations: one using a commercially available Relational Database and the other using Aurora. Our results show that a dedicated Stream Data Management System can outperform a Relational Database by at least a factor of 5 on streaming data applications.

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  • Retrospective on Aurora

    VLDB Journal

    Key lessons learned from the Aurora stream processing engine and five prototype implementations on the platform.

    Other authors
    • Hari Balakrishnan
    • Michael Stonebraker
    • Stan Zdonikchern
    • Mitch Cherniack
    • Eddie Galvez
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  • Covert Messaging through TCP Timestamps

    Privacy Enhancing Technologies

    Covert channels exist in most communications systems and allow individuals to communicate truly undectably. However, covert channels are seldom used due to their complexity. A protocol for sending data over a common class of low-bandwidth covert channels has been developed. The protocol is secure against attack by powerful adversaries. The design of a practical system implementing the protocol on a standard platform (Linux) exploiting a channel in a common communications system (TCP timestamps)…

    Covert channels exist in most communications systems and allow individuals to communicate truly undectably. However, covert channels are seldom used due to their complexity. A protocol for sending data over a common class of low-bandwidth covert channels has been developed. The protocol is secure against attack by powerful adversaries. The design of a practical system implementing the protocol on a standard platform (Linux) exploiting a channel in a common communications system (TCP timestamps) is presented. A partial implementation of this system has been accomplished.

    Other authors
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Patents

Honors & Awards

  • MIT 35 Innovators Under 35

    MIT

    http://www2.technologyreview.com/tr35/profile.aspx?trid=963

Languages

  • English

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Organizations

  • Boston CTO Club

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