D-Index & Metrics Best Publications

D-Index & Metrics

Discipline name D-index D-index (Discipline H-index) only includes papers and citation values for an examined discipline in contrast to General H-index which accounts for publications across all disciplines. Citations Publications World Ranking National Ranking
Computer Science D-index 79 Citations 30,715 176 World Ranking 481 National Ranking 290

Research.com Recognitions

Awards & Achievements

2019 - Member of the National Academy of Engineering For contributions to the design of advanced compiler and analysis systems for high-performance computers.

2007 - ACM Fellow For contributions to compilers and program analysis.

Overview

What is she best known for?

The fields of study she is best known for:

  • Operating system
  • Programming language
  • The Internet

Monica S. Lam mainly focuses on Compiler, Programming language, Parallel computing, Operating system and Software. The study incorporates disciplines such as Algorithm, Computer architecture, Computer hardware and Loop scheduling in addition to Compiler. Her Parallel computing research incorporates elements of Synchronization and Address space.

Monica S. Lam focuses mostly in the field of Operating system, narrowing it down to topics relating to Embedded system and, in certain cases, Server, Hash function, Unix operating system and Collaborative software. Her Software research incorporates themes from Guard, Buffer overflow, Heap overflow, Bounds checking and Testbed. Monica S. Lam has included themes like Multiprocessor performance, Automatic parallelization, Face and Benchmark in her Compiler construction study.

Her most cited work include:

  • A data locality optimizing algorithm (1213 citations)
  • Software pipelining: an effective scheduling technique for VLIW machines (929 citations)
  • The Stanford Dash multiprocessor (909 citations)

What are the main themes of her work throughout her whole career to date?

Monica S. Lam mostly deals with Parallel computing, Programming language, Compiler, Operating system and World Wide Web. Parallel computing is closely attributed to Systolic array in her work. In her study, which falls under the umbrella issue of Programming language, Algorithm is strongly linked to Theoretical computer science.

Monica S. Lam interconnects Software and Benchmark in the investigation of issues within Compiler. Monica S. Lam has researched Benchmark in several fields, including Multiprocessor performance and Face. Her study looks at the relationship between Operating system and fields such as Embedded system, as well as how they intersect with chemical problems.

She most often published in these fields:

  • Parallel computing (29.74%)
  • Programming language (26.67%)
  • Compiler (25.64%)

What were the highlights of her more recent work (between 2015-2021)?

  • Natural language (5.13%)
  • Artificial intelligence (5.13%)
  • Parsing (4.62%)

In recent papers she was focusing on the following fields of study:

Monica S. Lam spends much of her time researching Natural language, Artificial intelligence, Parsing, Set and Database schema. Her research in Natural language intersects with topics in Remote assistance, Human–computer interaction, Access control, World Wide Web and Task. Her biological study spans a wide range of topics, including Domain, Machine learning and Natural language processing.

Her study on Parsing is covered under Programming language. Her research is interdisciplinary, bridging the disciplines of Code and Programming language. Her study looks at the relationship between Set and topics such as Question answering, which overlap with Machine translation.

Between 2015 and 2021, her most popular works were:

  • Almond: The Architecture of an Open, Crowdsourced, Privacy-Preserving, Programmable Virtual Assistant (51 citations)
  • Genie: a generator of natural language semantic parsers for virtual assistant commands (26 citations)
  • Controlling Fine-Grain Sharing in Natural Language with a Virtual Assistant (10 citations)

In her most recent research, the most cited papers focused on:

  • Operating system
  • Programming language
  • The Internet

Her primary areas of investigation include Natural language, World Wide Web, Artificial intelligence, Training set and State. Her work deals with themes such as Parsing, Access control, Interface, Usability and Interoperability, which intersect with Natural language. To a larger extent, Monica S. Lam studies Programming language with the aim of understanding Parsing.

In the subject of general World Wide Web, her work in Crowdsourcing is often linked to Phone, Medical literature and Natural language programming, thereby combining diverse domains of study. In general Artificial intelligence, her work in Ontology, Tracking and Transfer of learning is often linked to Zero linking many areas of study. Her studies in Training set integrate themes in fields like Paraphrase, Machine learning and Shot.

This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.

Best Publications

A data locality optimizing algorithm

Michael E. Wolf;Monica S. Lam.
programming language design and implementation (1991)

1908 Citations

Software pipelining: an effective scheduling technique for VLIW machines

Monica S. Lam.
programming language design and implementation (1988)

1478 Citations

The Stanford Dash multiprocessor

D. Lenoski;J. Laudon;K. Gharachorloo;W.-D. Weber.
IEEE Computer (1992)

1397 Citations

Design and evaluation of a compiler algorithm for prefetching

Todd C. Mowry;Monica S. Lam;Anoop Gupta.
architectural support for programming languages and operating systems (1992)

988 Citations

Tracking down software bugs using automatic anomaly detection

Sudheendra Hangal;Monica S. Lam.
international conference on software engineering (2002)

928 Citations

A loop transformation theory and an algorithm to maximize parallelism

M.E. Wolf;M.S. Lam.
IEEE Transactions on Parallel and Distributed Systems (1991)

901 Citations

Automated processor generation system for designing a configurable processor and method for the same

Earl A. Killian;Ricardo E. Gonzalez;Ashish B. Dixit;Monica Lam.
(2001)

844 Citations

Efficient, context-sensitive pointer analysis for C programs

Robert P. Wilson;Monica S. Lam.
(1997)

821 Citations

Maximizing multiprocessor performance with the SUIF compiler

Mary W. Hall;Jennifer-Ann M. Anderson;Saman P. Amarasinghe;Brian R. Murphy.
IEEE Computer (1996)

779 Citations

SUIF: an infrastructure for research on parallelizing and optimizing compilers

Robert P. Wilson;Robert S. French;Christopher S. Wilson;Saman P. Amarasinghe.
Sigplan Notices (1994)

737 Citations

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Best Scientists Citing Monica S. Lam

Mahmut Kandemir

Mahmut Kandemir

Pennsylvania State University

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J. Ramanujam

J. Ramanujam

Louisiana State University

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Jingling Xue

Jingling Xue

UNSW Sydney

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Guang R. Gao

Guang R. Gao

University of Delaware

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James Michael Ferris

James Michael Ferris

Red Hat (United States)

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Martin Rinard

Martin Rinard

MIT

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P. Sadayappan

P. Sadayappan

University of Utah

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Wen-mei W. Hwu

Wen-mei W. Hwu

University of Illinois at Urbana-Champaign

Publications: 55

Alok Choudhary

Alok Choudhary

Northwestern University

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Albert Cohen

Albert Cohen

Google (United States)

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David Padua

David Padua

University of Illinois at Urbana-Champaign

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Mateo Valero

Mateo Valero

Barcelona Supercomputing Center

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Jason Nieh

Jason Nieh

Columbia University

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Atanas Rountev

Atanas Rountev

The Ohio State University

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Josep Torrellas

Josep Torrellas

University of Illinois at Urbana-Champaign

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Eduard Ayguadé

Eduard Ayguadé

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