World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
87
Citations
34255
World Ranking
715
National Ranking
376

Research.com Recognitions

  • 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

Monica S. Lam is affiliated with Stanford University in the United States and has contributed extensively to the field of Computer Science. Their research primarily focuses on subfields such as Artificial Intelligence, Computer Vision and Pattern Recognition, Communication, Computer Networks and Communications, and Information Systems.

The main topics covered in their work include:

  • Topic Modeling
  • Natural Language Processing Techniques
  • Speech and dialogue systems
  • Multimodal Machine Learning Applications
  • Wikis in Education and Collaboration
  • Multi-Agent Systems and Negotiation
  • Corporate Social Responsibility Reporting

Their recent publications demonstrate a breadth of interests ranging from virtual reality to corporate social responsibility. Notable papers include:

  • "HybridTrak: Adding Full-Body Tracking to VR Using an Off-the-Shelf Webcam" (2022), published in CHI Conference on Human Factors in Computing Systems
  • "An Empirical Study of the Relationship Between Digital Transformation, Corporate Social Responsibility and Financial Performance" (2024), published in Business Ethics and Leadership
  • "Schema2QA: High-Quality and Low-Cost Q&A Agents for the Structured Web" (2020), published on arXiv (Cornell University)
  • "Assisting in Writing Wikipedia-like Articles From Scratch with Large Language Models" (2024), published on arXiv (Cornell University)
  • "Mediating Effects of Stakeholders and Supervision on Corporate Social Responsibility" (2020), published in Business Ethics and Leadership

They have collaborated frequently with several co-authors, including:

  • Sina J. Semnani
  • Giovanni Campagna
  • Silei Xu
  • Mehrad Moradshahi
  • Shicheng Liu

Their publications appear predominantly in venues such as arXiv (Cornell University), Business Ethics and Leadership, CHI Conference on Human Factors in Computing Systems, Journal of Autism and Developmental Disorders, and Modern Pathology. The highest concentration of their work is found in arXiv, where they have published 23 papers.

Monica S. Lam has received several recognitions in their career:

  • Member of the National Academy of Engineering (2019) for contributions to the design of advanced compiler and analysis systems for high-performance computers
  • ACM Fellow (2007) for contributions to compilers and program analysis

Best Publications

  • A data locality optimizing algorithm

    Michael E. Wolf;Monica S. Lam

  • The Stanford Dash multiprocessor

    D. Lenoski;J. Laudon;K. Gharachorloo;W.-D. Weber

  • Software pipelining: an effective scheduling technique for VLIW machines

    Monica S. Lam

  • Design and evaluation of a compiler algorithm for prefetching

    Todd C. Mowry;Monica S. Lam;Anoop Gupta

  • A loop transformation theory and an algorithm to maximize parallelism

    M.E. Wolf;M.S. Lam

  • Tracking down software bugs using automatic anomaly detection

    Sudheendra Hangal;Monica S. Lam

  • Efficient, context-sensitive pointer analysis for C programs

    Robert P. Wilson;Monica S. Lam

  • Finding security vulnerabilities in java applications with static analysis

    V. Benjamin Livshits;Monica S. Lam

  • Maximizing multiprocessor performance with the SUIF compiler

    M.W. Hall;J.M. Anderson;J.M. Anderson;S.P. Amarasinghe;S.P. Amarasinghe;B.R. Murphy;B.R. Murphy

  • 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

  • SUIF: an infrastructure for research on parallelizing and optimizing compilers

    Robert P. Wilson;Robert S. French;Christopher S. Wilson;Saman P. Amarasinghe

  • Cloning-based context-sensitive pointer alias analysis using binary decision diagrams

    John Whaley;Monica S. Lam

  • Optimizing the migration of virtual computers

    Constantine P. Sapuntzakis;Ramesh Chandra;Ben Pfaff;Jim Chow

  • Finding application errors and security flaws using PQL: a program query language

    Michael Martin;Benjamin Livshits;Monica S. Lam

  • Global optimizations for parallelism and locality on scalable parallel machines

    Jennifer M. Anderson;Monica S. Lam

  • Compilers: Principles, Techniques, and Tools (2nd Edition)

    Alfred V. Aho;Monica S. Lam;Ravi Sethi;Jeffrey D. Ullman

  • Limits of control flow on parallelism

    Monica S. Lam;Robert P. Wilson

  • A practical dynamic buffer overflow detector

    Olatunji Ruwase;Monica S. Lam

  • iWarp: an integrated solution to high-speed parallel computing

    S. Borkar;R. Cohn;G. Cox;S. Gleason

  • Efficient, context-sensitive pointer analysis for c programs

    Monica S. Lam;Robert Paul Wilson

  • Maximizing Multiprocessor Performance with the SUIF Compiler.

    Mary W. Hall;Jennifer-Ann M. Anderson;Saman P. Amarasinghe;Brian R. Murphy

Frequent Co-Authors

Mary Hall
Mary Hall University of Utah
John L. Hennessy
John L. Hennessy Stanford University
H. T. Kung
H. T. Kung Harvard University
Jason Nieh
Jason Nieh Columbia University
Benjamin Livshits
Benjamin Livshits Imperial College London
Mendel Rosenblum
Mendel Rosenblum Stanford University
Mark Horowitz
Mark Horowitz Stanford University

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