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Researcher · Massachusetts Institute of Technology · United States

Jonathan P. How

Jonathan P. How publishes mostly in Aerospace Engineering, Control and Systems Engineering and Artificial Intelligence, on topics such as Robotic Path Planning Algorithms, Robotics and Sensor-Based Localization and Reinforcement Learning in Robotics.

ORCID 0000-0001-8576-1930 OpenAlex
World rank
#15,573
of 7,710,434 ranked researchers
Rank in United States
#5,541
of 1,627,098
Works
944
Citations
33k
Citations per work
35.0
h-index
85
i10-index 436Top 0.1% in Aerospace Engineering
Jonathan P. How

What does Jonathan P. How research?

Jonathan P. How's work is mostly in Engineering (39%), Computer Science (34%).

Physical Sciences: 697 works · 73.8% of their workEngineering: 372 works · 39.4% of their workAerospace Engineering: 179 works · 19.0% of their workControl and Systems Engineering: 163 works · 17.3% of their workAutomotive Engineering: 29 works · 3.1% of their workComputer Science: 325 works · 34.4% of their workArtificial Intelligence: 154 works · 16.3% of their workComputer Vision and Pattern Recognition: 101 works · 10.7% of their workComputer Networks and Communications: 70 works · 7.4% of their workEverything else: 247 works · 26.2% of their workTHEIR WORKJonathan P. How944works
Physical Sciences74%

Their six largest subfields, inside their fields and domains; the grey slice is everything else they publish. The interactive view splits every one of their works down to single topics.

The fields and subfields, with their numbers
    1. Engineering37239.4%
    2. Computer Science32534.4%
  2. Everything else24726.2%
  1. 1Aerospace Engineering19% of their works
  2. 2Control and Systems Engineering17% of their works
  3. 3Artificial Intelligence16% of their works
  4. 4Computer Vision and Pattern Recognition11% of their works
  5. 5Computer Networks and Communications7% of their works
  6. 6Automotive Engineering3% of their works

Research topics

Which keywords describe Jonathan P. How's research?

The keywords of their largest research topics: Multi-Agent Systems, Autonomous Vehicles, Collision Avoidance, Robotics, Optimal Motion Planning, Sampling-Based Algorithms, Deep Learning and Sensor Fusion.

Size is their works in the topics tagged with each word, from their 8 largest topics. Each links to the topic it comes from most.

All 22 words, with their numbers
  1. Multi-Agent Systems3993 topics
  2. Autonomous Vehicles2622 topics
  3. Collision Avoidance2622 topics
  4. Robotics2542 topics
  5. Optimal Motion Planning1921 topic
  6. Sampling-Based Algorithms1921 topic
  7. Deep Learning1882 topics
  8. Sensor Fusion1402 topics
  9. 3D Mapping1361 topic
  10. SLAM1361 topic
  11. Neural Networks1181 topic
  12. Reinforcement Learning1181 topic
  13. Model Predictive Control1091 topic
  14. Optimization1091 topic
  15. Consensus891 topic
  16. Cooperative Control891 topic
  17. Spacecraft Formation Flying801 topic
  18. Trajectory Optimization801 topic
  19. Driver Assistance Systems701 topic
  20. Nonlinear Estimation701 topic
  21. Particle Filters701 topic
  22. Trajectory Prediction701 topic

Where does Jonathan P. How work?

Jonathan P. How's main affiliation in the publication record is Massachusetts Institute of Technology, United States.

How many publications and citations does Jonathan P. How have?

OpenAlex counts 944 works and 33,066 citations for Jonathan P. How, an h-index of 85, ranking #15,573 of 7,710,434 researchers worldwide on the quality score.

Ranked on field-normalised excellence (50%), output (30%) and citations (20%). Counts come from OpenAlex author records, which occasionally merge different people who share a name or split one person into several.

Papers, co-authors, who cited this work and researchers on the nearest topics have tabs of their own, above. Is this your page? Claim it with your ORCID iD, or request a correction or removal.

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