What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Algorithm
- Robot
Siddhartha S. Srinivasa mainly investigates Artificial intelligence, Robot, Motion planning, Robotics and Human–computer interaction.
His research on Artificial intelligence often connects related topics like Computer vision.
His work carried out in the field of Robot brings together such families of science as Motion and Trajectory.
The study incorporates disciplines such as Motion control, Probabilistic logic, Mathematical optimization, Trajectory optimization and Configuration space in addition to Motion planning.
His Robotics research includes elements of Animation, Computer graphics, Software and Dart.
The various areas that Siddhartha S. Srinivasa examines in his Human–computer interaction study include Contrast, Real-time computing and Teleoperation.
His most cited work include:
- CHOMP: Gradient optimization techniques for efficient motion planning (456 citations)
- CHOMP: Covariant Hamiltonian optimization for motion planning (386 citations)
- Planning-based prediction for pedestrians (327 citations)
What are the main themes of his work throughout his whole career to date?
Robot, Artificial intelligence, Motion planning, Human–computer interaction and Computer vision are his primary areas of study.
Siddhartha S. Srinivasa combines subjects such as Theoretical computer science and Trajectory with his study of Robot.
His studies in Artificial intelligence integrate themes in fields like Machine learning and GRASP.
Siddhartha S. Srinivasa has included themes like Algorithm, Mathematical optimization, Heuristics and Shortest path problem in his Motion planning study.
In the field of Mathematical optimization, his study on Asymptotically optimal algorithm overlaps with subjects such as Rate of convergence.
His Human–computer interaction research is multidisciplinary, incorporating elements of Simulation and Teleoperation.
He most often published in these fields:
- Robot (49.51%)
- Artificial intelligence (45.25%)
- Motion planning (22.62%)
What were the highlights of his more recent work (between 2017-2021)?
- Artificial intelligence (45.25%)
- Robot (49.51%)
- Human–computer interaction (20.00%)
In recent papers he was focusing on the following fields of study:
His primary areas of investigation include Artificial intelligence, Robot, Human–computer interaction, Object and Motion planning.
His research integrates issues of Machine learning and Computer vision in his study of Artificial intelligence.
Siddhartha S. Srinivasa performs multidisciplinary studies into Robot and Key in his work.
His work deals with themes such as Categorization, Teleoperation and Human–robot interaction, which intersect with Human–computer interaction.
His study explores the link between Object and topics such as Base that cross with problems in Track.
His research in Motion planning intersects with topics in Algorithm, Bottleneck, Enhanced Data Rates for GSM Evolution and Shortest path problem.
Between 2017 and 2021, his most popular works were:
- DART: Dynamic Animation and Robotics Toolkit (93 citations)
- Shared autonomy via hindsight optimization for teleoperation and teaming (61 citations)
- Informed Sampling for Asymptotically Optimal Path Planning (46 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Algorithm
- Programming language
His main research concerns Artificial intelligence, Human–computer interaction, Robot, Partially observable Markov decision process and Human–robot interaction.
His Artificial intelligence research includes themes of Beam search, Computer vision and Component.
His work in the fields of Computer vision, such as Object, overlaps with other areas such as Source area.
Siddhartha S. Srinivasa connects Robot with Food item in his research.
His research in Human–robot interaction focuses on subjects like Latent variable, which are connected to Human behavior.
His Robotics study incorporates themes from Planning algorithms, Animation, Computer graphics and Dart.
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