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Lydia E. Kavraki

Lydia E. Kavraki

D-Index & Metrics

Computer Science

D-Index
82
Citations
38039
World Ranking
936
National Ranking
509

Research.com Recognitions

  • 2020 - Member of Academia Europaea
  • 2019 - ACM AAAI Allen Newell Award For pioneering contributions to robotic motion planning and their applications in bioinformatics and biomedicine, including the invention of randomized motion planning algorithms and probabilistic roadmaps.
  • 2017 - ACM Athena Lecturer Award For the invention of randomized motion planning algorithms in robotics and the development of robotics-inspired methods for bioinformatics and biomedicine.
  • 2012 - Fellow of the American Association for the Advancement of Science (AAAS)
  • 2012 - IEEE Fellow For contributions to robot-motion planning and computational biology
  • 2012 - Member of the National Academy of Medicine (NAM)
  • 2010 - ACM Fellow For contributions to robotic motion planning and its application to computational biology.
  • 2008 - Fellow of the Association for the Advancement of Artificial Intelligence (AAAI) For significant contributions to the field of automated motion planning and the development of widely used probabilistic search algorithms
  • 2004 - Fellow of the Indian National Academy of Engineering (INAE)
  • 2000 - ACM Grace Murray Hopper Award For her seminal work on the probabilistic roadmap approach which has caused a paradigm shift in the area of path planning, and has many applications in robotics, manufacturing, nanotechnology and computational biology.
  • 2000 - Fellow of Alfred P. Sloan Foundation

Overview

Lydia E. Kavraki is affiliated with Rice University in the United States. Their research spans multiple fields and subfields within computer science and engineering, producing a significant body of scholarly work.

The main fields of study in which they have published include:

  • Computer Science
  • Engineering

The notable subfields of study covered by their publications are:

  • Computer Vision and Pattern Recognition
  • Molecular Biology
  • Artificial Intelligence
  • Control and Systems Engineering
  • Computational Theory and Mathematics

Their research topics include:

  • Robotic Path Planning Algorithms
  • Robot Manipulation and Learning
  • AI-based Problem Solving and Planning
  • Vaccines and Immunoinformatics Approaches
  • Computational Drug Discovery Methods
  • Protein Structure and Dynamics
  • Reinforcement Learning in Robotics

Kavraki has published extensively in the following venues:

  • arXiv (Cornell University)
  • Frontiers in Immunology
  • IEEE Robotics and Automation Letters
  • 2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
  • Journal of Chemical Information and Modeling

Selected recent papers demonstrate a blend of robotics, machine learning, and bioinformatics applications:

  • Machine Learning-Guided Three-Dimensional Printing of Tissue Engineering Scaffolds, 2020, Tissue Engineering Part A
  • Sampling-Based Motion Planning: A Comparative Review, 2023, Annual Review of Control Robotics and Autonomous Systems
  • MotionBenchMaker: A Tool to Generate and Benchmark Motion Planning Datasets, 2021, IEEE Robotics and Automation Letters
  • Prediction of drug metabolites using neural machine translation, 2020, Chemical Science
  • An end-to-end deep learning framework for translating mass spectra to de-novo molecules, 2023, Communications Chemistry

Frequent co-authors collaborating with Kavraki include:

  • Zachary Kingston
  • Dinler A. Antunes
  • Constantinos Chamzas
  • Maurício Rigo
  • Anja Conev

The scientist's recognitions and honors consist of:

  • Member of Academia Europaea, 2020
  • ACM AAAI Allen Newell Award, 2019, for pioneering contributions to robotic motion planning and applications in bioinformatics and biomedicine
  • ACM Athena Lecturer Award, 2017, for invention of randomized motion planning algorithms and robotics-inspired bioinformatics methods
  • Member of the National Academy of Medicine (NAM), 2012
  • IEEE Fellow, 2012, for contributions to robot-motion planning and computational biology
  • Fellow of the American Association for the Advancement of Science (AAAS), 2012
  • ACM Fellow, 2010, for contributions to robotic motion planning applied to computational biology
  • Fellow of the Association for the Advancement of Artificial Intelligence (AAAI), 2008
  • Fellow of the Indian National Academy of Engineering (INAE), 2004
  • ACM Grace Murray Hopper Award, 2000, for seminal work on the probabilistic roadmap approach impacting path planning and multiple applied fields
  • Fellow of Alfred P. Sloan Foundation, 2000

Best Publications

  • Probabilistic roadmaps for path planning in high-dimensional configuration spaces

    L.E. Kavraki;P. Svestka;J.-C. Latombe;M.H. Overmars

  • The Open Motion Planning Library

    I. A. Sucan;M. Moll;L. E. Kavraki

  • Path planning using lazy PRM

    R. Bohlin;L.E. Kavraki

  • Practical robust localization over large-scale 802.11 wireless networks

    Andreas Haeberlen;Eliot Flannery;Andrew M. Ladd;Algis Rudys

  • Robotics-based location sensing using wireless Ethernet

    Andrew M. Ladd;Kostas E. Bekris;Algis Rudys;Lydia E. Kavraki

  • Robotics-based location sensing using wireless ethernet

    Andrew M. Ladd;Kostas E. Bekris;Algis Rudys;Guillaume Marceau

  • Randomized preprocessing of configuration for fast path planning

    L. Kavraki;J.-C. Latombe

  • On finding narrow passages with probabilistic roadmap planners

    David Hsu;Lydia E. Kavraki;Jean-Claude Latombe;Rajeev Motwani

  • Analysis of probabilistic roadmaps for path planning

    L.E. Kavraki;M.N. Kolountzakis;J.-C. Latombe

  • A random sampling scheme for path planning

    Jér ocirc Barraquand;Lydia Kavraki;Jean-Claude Latombe;Rajeev Motwani

  • Randomized Query Processing in Robot Path Planning

    Lydia E. Kavraki;Jean-Claude Latombe;Rajeev Motwani;Prabhakar Raghavan

  • Low-dimensional, free-energy landscapes of protein-folding reactions by nonlinear dimensionality reduction

    Payel Das;Mark Moll;Hernán Stamati;Lydia E. Kavraki

  • On the feasibility of using wireless ethernet for indoor localization

    A.M. Ladd;K.E. Bekris;A.P. Rudys;D.S. Wallach

  • Sampling-based motion planning with temporal goals

    Amit Bhatia;Lydia E. Kavraki;Moshe Y. Vardi

  • An Accurate, Sensitive, and Scalable Method to Identify Functional Sites in Protein Structures

    Hui Yao;David M. Kristensen;David M. Kristensen;Ivana Mihalek;Mathew E. Sowa

  • Randomized path planning for linkages with closed kinematic chains

    J.H. Yakey;S.M. LaValle;L.E. Kavraki

  • Path planning for deformable linear objects

    M. Moll;L.E. Kavraki

  • Kinodynamic Motion Planning by Interior-Exterior Cell Exploration

    Ioan Alexandru Sucan;Lydia E. Kavraki

  • Sampling-based roadmap of trees for parallel motion planning

    E. Plaku;K.E. Bekris;B.Y. Chen;A.M. Ladd

  • A two level fuzzy PRM for manipulation planning

    C.L. Nielsen;L.E. Kavraki

  • Principles of Robot Motion: Theory, Algorithms, and Implementation ERRATA!!!! 1

    Howie Choset;Kevin Lynch;Seth Hutchinson;George Kantor

Frequent Co-Authors

Kostas E. Bekris
Kostas E. Bekris Rutgers, The State University of New Jersey
Jean-Claude Latombe
Jean-Claude Latombe Stanford University
Moshe Y. Vardi
Moshe Y. Vardi Rice University
Olivier Lichtarge
Olivier Lichtarge Baylor College of Medicine
Marek Kimmel
Marek Kimmel Rice University
Swarat Chaudhuri
Swarat Chaudhuri The University of Texas at Austin
Rajeev Motwani
Rajeev Motwani Stanford University
Wolfram Burgard
Wolfram Burgard University of Technology Nuremberg
Sebastian Thrun
Sebastian Thrun Stanford University
Kevin M. Lynch
Kevin M. Lynch Northwestern University

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