What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Control theory
- Statistics
S. Shankar Sastry focuses on Control theory, Artificial intelligence, Control system, Control engineering and Hybrid system.
His studies in Control theory integrate themes in fields like Robot and Nonholonomic system.
His Artificial intelligence study integrates concerns from other disciplines, such as Computer vision and Pattern recognition.
His Control system research incorporates elements of Computer security, Linear system and Linear-quadratic-Gaussian control, Optimal control.
His work carried out in the field of Hybrid system brings together such families of science as Dynamical systems theory, Algorithm, Reachability, Uniqueness and Applied mathematics.
His Nonlinear system study combines topics from a wide range of disciplines, such as Remotely operated underwater vehicle and Robustness.
His most cited work include:
- Robust Face Recognition via Sparse Representation (7978 citations)
- A Mathematical Introduction to Robotic Manipulation (4965 citations)
- Adaptive Control: Stability, Convergence and Robustness (2045 citations)
What are the main themes of his work throughout his whole career to date?
S. Shankar Sastry mainly focuses on Control theory, Artificial intelligence, Hybrid system, Control engineering and Mathematical optimization.
Control theory is represented through his Nonlinear system, Control theory, Control system, Optimal control and Adaptive control research.
His Artificial intelligence research integrates issues from Computer vision and Pattern recognition.
His studies deal with areas such as Dynamical systems theory, State space, Reachability and Topology as well as Hybrid system.
His Control engineering research is multidisciplinary, relying on both Control and Mobile robot.
His research integrates issues of Function and Algorithm in his study of Mathematical optimization.
He most often published in these fields:
- Control theory (29.71%)
- Artificial intelligence (17.26%)
- Hybrid system (15.81%)
What were the highlights of his more recent work (between 2013-2021)?
- Mathematical optimization (12.56%)
- Artificial intelligence (17.26%)
- Control theory (29.71%)
In recent papers he was focusing on the following fields of study:
His scientific interests lie mostly in Mathematical optimization, Artificial intelligence, Control theory, Nash equilibrium and Robot.
The concepts of his Artificial intelligence study are interwoven with issues in Machine learning and Computer vision.
His Control theory research focuses on Reinforcement learning and how it relates to Feedback linearization.
His Robot research includes elements of Function and Human–computer interaction.
His Optimal control research includes themes of Control system and Trajectory.
S. Shankar Sastry has included themes like Control engineering and Dynamical systems theory in his Hybrid system study.
Between 2013 and 2021, his most popular works were:
- Generalized Principal Component Analysis (209 citations)
- Planning for Autonomous Cars that Leverage Effects on Human Actions (200 citations)
- Principal Component Analysis (184 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Statistics
- Quantum mechanics
S. Shankar Sastry spends much of his time researching Artificial intelligence, Mathematical optimization, Nash equilibrium, Human–computer interaction and Game theory.
His biological study spans a wide range of topics, including Machine learning and Pattern recognition.
The Mathematical optimization study combines topics in areas such as Function, Control theory and Vehicle dynamics.
Within one scientific family, S. Shankar Sastry focuses on topics pertaining to Electric power system under Control theory, and may sometimes address concerns connected to Control engineering, Model predictive control and Hybrid system.
His research in Human–computer interaction intersects with topics in Automation, Robot and Autonomous system.
His Nonlinear control study is related to the wider topic of Control theory.
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