World's Best Scientists 2026 revealed!
Siddhartha S. Srinivasa

Siddhartha S. Srinivasa

D-Index & Metrics

Electronics and Electrical Engineering

D-Index
77
Citations
23581
World Ranking
607
National Ranking
272

Siddhartha S. Srinivasa publication distribution in Electronics and Electrical Engineering in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Electronics and Electrical Engineering in 2026. The highlighted bar marks where Siddhartha S. Srinivasa sits on this spectrum.

34–53 publications: 24 scientists 54–73 publications: 52 scientists 74–93 publications: 114 scientists 94–113 publications: 203 scientists 114–133 publications: 269 scientists 134–153 publications: 355 scientists 154–173 publications: 403 scientists 174–193 publications: 445 scientists 194–213 publications: 430 scientists 214–233 publications: 431 scientists 234–253 publications: 399 scientists 254–273 publications: 366 scientists 274–293 publications: 335 scientists 294–313 publications: 300 scientists 314–333 publications: 276 scientists 334–353 publications: 250 scientists 354–373 publications: 214 scientists 374–393 publications: 187 scientists 394–413 publications: 152 scientists 414–433 publications: 169 scientists 434–453 publications: 147 scientists 454–473 publications: 111 scientists 474–493 publications: 117 scientists 494–513 publications: 103 scientists 514–533 publications: 99 scientists 534–553 publications: 92 scientists 554–573 publications: 75 scientists 574–593 publications: 58 scientists 594–613 publications: 69 scientists 614–633 publications: 50 scientists 634–653 publications: 62 scientists 654–673 publications: 54 scientists 674–693 publications: 44 scientists 694–713 publications: 37 scientists 714–733 publications: 28 scientists 734–753 publications: 26 scientists 754–773 publications: 26 scientists 774–793 publications: 19 scientists 794–813 publications: 23 scientists 814–833 publications: 20 scientists 834–853 publications: 16 scientists 854–873 publications: 20 scientists 874–893 publications: 11 scientists 894–913 publications: 11 scientists 914–933 publications: 16 scientists 934–953 publications: 13 scientists 954–973 publications: 10 scientists 974–993 publications: 11 scientists 994–1,013 publications: 9 scientists 1,014–1,033 publications: 9 scientists 1,034–1,053 publications: 10 scientists 1,054–1,064 publications: 6 scientists 1,065+ publications: 99 scientists
34 publications 1,065+

This scientist: 302 publications — 58th percentile

58% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 1,065 publications or more.

Siddhartha S. Srinivasa D-index placement in Electronics and Electrical Engineering in 2026

The chart shows the D-index (discipline H-index) distribution of Electronics and Electrical Engineering scientists ranked by Research.com in 2026. The highlighted bar marks where Siddhartha S. Srinivasa sits on this spectrum.

30 D-Index: 178 scientists 31 D-Index: 257 scientists 32 D-Index: 263 scientists 33 D-Index: 262 scientists 34 D-Index: 244 scientists 35 D-Index: 236 scientists 36 D-Index: 211 scientists 37 D-Index: 220 scientists 38 D-Index: 214 scientists 39 D-Index: 214 scientists 40 D-Index: 205 scientists 41 D-Index: 187 scientists 42 D-Index: 194 scientists 43 D-Index: 201 scientists 44 D-Index: 155 scientists 45 D-Index: 189 scientists 46 D-Index: 148 scientists 47 D-Index: 160 scientists 48 D-Index: 134 scientists 49 D-Index: 130 scientists 50 D-Index: 141 scientists 51 D-Index: 156 scientists 52 D-Index: 108 scientists 53 D-Index: 130 scientists 54 D-Index: 112 scientists 55 D-Index: 97 scientists 56 D-Index: 111 scientists 57 D-Index: 102 scientists 58 D-Index: 108 scientists 59 D-Index: 120 scientists 60 D-Index: 103 scientists 61 D-Index: 93 scientists 62 D-Index: 92 scientists 63 D-Index: 74 scientists 64 D-Index: 77 scientists 65 D-Index: 73 scientists 66 D-Index: 64 scientists 67 D-Index: 69 scientists 68 D-Index: 60 scientists 69 D-Index: 39 scientists 70 D-Index: 57 scientists 71 D-Index: 59 scientists 72 D-Index: 46 scientists 73 D-Index: 49 scientists 74 D-Index: 38 scientists 75 D-Index: 35 scientists 76 D-Index: 32 scientists 77 D-Index: 35 scientists 78 D-Index: 31 scientists 79 D-Index: 22 scientists 80 D-Index: 34 scientists 81 D-Index: 31 scientists 82 D-Index: 34 scientists 83 D-Index: 23 scientists 84 D-Index: 18 scientists 85 D-Index: 30 scientists 86 D-Index: 19 scientists 87 D-Index: 19 scientists 88 D-Index: 20 scientists 89 D-Index: 8 scientists 90 D-Index: 17 scientists 91 D-Index: 7 scientists 92 D-Index: 14 scientists 93 D-Index: 9 scientists 94 D-Index: 15 scientists 95 D-Index: 10 scientists 96 D-Index: 12 scientists 97 D-Index: 10 scientists 98 D-Index: 10 scientists 99 D-Index: 12 scientists 100 D-Index: 16 scientists 101 D-Index: 5 scientists 102 D-Index: 7 scientists 103 D-Index: 7 scientists 104 D-Index: 8 scientists 105 D-Index: 9 scientists 106 D-Index: 13 scientists 107 D-Index: 4 scientists 108 D-Index: 5 scientists 109 D-Index: 10 scientists 110 D-Index: 8 scientists 111+ D-Index: 96 scientists
30 D-Index 111+

This scientist: 77 D-Index — 91st percentile

91% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 111 D-Index or more.

Overview

Siddhartha S. Srinivasa is affiliated with the University of Washington in the United States. Their research primarily spans the fields of Computer Science and Engineering, with significant focus on subfields such as Computer Vision and Pattern Recognition, Artificial Intelligence, and Control and Systems Engineering. Additional areas of interest include Biomedical Engineering and Aerospace Engineering.

The scientist's work covers diverse topics within robotics and related disciplines. These topics include:

  • Robot Manipulation and Learning
  • Robotic Path Planning Algorithms
  • Reinforcement Learning in Robotics
  • Robotics and Sensor-Based Localization
  • Anomaly Detection Techniques and Applications
  • Modular Robots and Swarm Intelligence
  • Soft Robotics and Applications

Their recent papers illustrate a focus on human-robot collaboration, robotic navigation, and policy optimization for manipulation tasks. Notable recent publications include:

  • "Trust-Aware Decision Making for Human-Robot Collaboration" (2020), published in ACM Transactions on Human-Robot Interaction
  • "HARMONIC: A multimodal dataset of assistive human-robot collaboration" (2021), published in The International Journal of Robotics Research
  • "Git Re-Basin: Merging Models modulo Permutation Symmetries" (2022), published on arXiv (Cornell University)
  • "Winding Through: Crowd Navigation via Topological Invariance" (2022), published in IEEE Robotics and Automation Letters
  • "Benchmarking Structured Policies and Policy Optimization for Real-World Dexterous Object Manipulation" (2021), published on arXiv (Cornell University)

The scientist collaborates frequently with several researchers, including Christoforos Mavrogiannis, Sanjiban Choudhury, Tapomayukh Bhattacharjee, Ethan Kroll Gordon, and Brian Hou, indicating ongoing partnerships in areas related to human-robot interaction and robotic control.

Publications by Siddhartha S. Srinivasa appear extensively across multiple venues, with a particularly strong presence in:

  • arXiv (Cornell University)
  • The International Journal of Robotics Research
  • IEEE Robotics and Automation Letters
  • 2022 International Conference on Robotics and Automation (ICRA)
  • 2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

Best Publications

  • CHOMP: Gradient optimization techniques for efficient motion planning

    Nathan Ratliff;Matt Zucker;J. Andrew Bagnell;Siddhartha Srinivasa

  • Informed RRT*: Optimal Sampling-based Path Planning Focused via Direct Sampling of an Admissible Ellipsoidal Heuristic

    Jonathan D. Gammell;Siddhartha S. Srinivasa;Timothy D. Barfoot

  • CHOMP: Covariant Hamiltonian optimization for motion planning

    Matt Zucker;Nathan Ratliff;Anca D. Dragan;Mihail Pivtoraiko

  • The YCB object and Model set: Towards common benchmarks for manipulation research

    Berk Calli;Arjun Singh;Aaron Walsman;Siddhartha Srinivasa

  • Planning-based prediction for pedestrians

    Brian D. Ziebart;Nathan Ratliff;Garratt Gallagher;Christoph Mertz

  • Batch Informed Trees (BIT*): Sampling-based optimal planning via the heuristically guided search of implicit random geometric graphs

    Jonathan D. Gammell;Siddhartha S. Srinivasa;Timothy D. Barfoot

  • Benchmarking in Manipulation Research: Using the Yale-CMU-Berkeley Object and Model Set

    Berk Calli;Aaron Walsman;Arjun Singh;Siddhartha Srinivasa

  • Legibility and predictability of robot motion

    Anca D. Dragan;Kenton C.T. Lee;Siddhartha S. Srinivasa

  • Brief paper: Decentralized estimation and control of graph connectivity for mobile sensor networks

    P. Yang;R. A. Freeman;G. J. Gordon;K. M. Lynch

  • The MOPED framework: Object recognition and pose estimation for manipulation

    Alvaro Collet;Manuel Martinez;Siddhartha S Srinivasa

  • Task Space Regions: A framework for pose-constrained manipulation planning

    Dmitry Berenson;Siddhartha Srinivasa;James Kuffner

  • A policy-blending formalism for shared control

    Anca D Dragan;Siddhartha S Srinivasa

  • HERB: a home exploring robotic butler

    Siddhartha S. Srinivasa;Dave Ferguson;Casey J. Helfrich;Dmitry Berenson

  • Manipulation planning on constraint manifolds

    Dmitry Berenson;Siddhartha S. Srinivasa;Dave Ferguson;James J. Kuffner

  • Yale-CMU-Berkeley dataset for robotic manipulation research:

    Berk Çalli;Arjun Singh;James Bruce;Aaron Walsman

  • Object recognition and full pose registration from a single image for robotic manipulation

    Alvaro Collet;Dmitry Berenson;Siddhartha S. Srinivasa;Dave Ferguson

  • Extrinsic dexterity: In-hand manipulation with external forces

    Nikhil Chavan Dafle;Alberto Rodriguez;Robert Paolini;Bowei Tang

  • Effects of Robot Motion on Human-Robot Collaboration

    Anca D. Dragan;Shira Bauman;Jodi Forlizzi;Siddhartha S. Srinivasa

  • Toward seamless human-robot handovers

    Kyle Strabala;Min Kyung Lee;Anca Dragan;Jodi Forlizzi

  • Benchmarking in Manipulation Research: The YCB Object and Model Set and Benchmarking Protocols.

    Berk Çalli;Aaron Walsman;Arjun Singh;Siddhartha S. Srinivasa

Frequent Co-Authors

Matthew T. Mason
Matthew T. Mason Carnegie Mellon University
Anca D. Dragan
Anca D. Dragan University of California, Berkeley
J. Andrew Bagnell
J. Andrew Bagnell Carnegie Mellon University
Nancy S. Pollard
Nancy S. Pollard Carnegie Mellon University
Timothy D. Barfoot
Timothy D. Barfoot University of Toronto
Jodi Forlizzi
Jodi Forlizzi Carnegie Mellon University
James J. Kuffner
James J. Kuffner Toyota Motor Corporation (United States)
David Hsu
David Hsu National University of Singapore
Martial Hebert
Martial Hebert Carnegie Mellon University
Geoffrey J. Gordon
Geoffrey J. Gordon Carnegie Mellon University

If you think any of the details on this page are incorrect, let us know.

Report an issue

We appreciate your kind effort to assist us to improve this page, it would be helpful providing us with as much detail as possible in the text box below:

Related Online Degrees & Career Pathways

For students pursuing Electronics and Electrical Engineering, exploring complementary fields can open new career avenues. Many professionals enhance their skills by earning a bachelor degree in project management, which equips them with essential leadership and organizational capabilities for managing complex engineering projects.

Working adults often face time constraints when advancing their education. Fortunately, there are several degree programs for working adults designed to offer flexibility and convenience without compromising quality. These programs help learners balance professional responsibilities and academic pursuits.

Another valuable discipline gaining popularity is instructional design, which focuses on creating effective educational experiences. Engineers interested in training and development may find instructional design programs beneficial for transitioning into roles that involve technical education and curriculum development.

Moreover, competency based masters degrees offer tailored learning paths based on skill mastery rather than time spent in class. This approach is ideal for professionals seeking to demonstrate expertise in specific areas quickly and efficiently, further customizing their educational journey.

Best Scientists Citing Siddhartha S. Srinivasa

Trending Scientists

Recently Published Articles