2019 - ACM Fellow For contributions to automated planning and human-aware AI systems and leadership within the field
2017 - Fellow of the American Association for the Advancement of Science (AAAS)
Subbarao Kambhampati spends much of his time researching Artificial intelligence, Heuristics, Planner, Plan and Mathematical optimization. Subbarao Kambhampati works on Artificial intelligence which deals in particular with Robot. His Heuristics research incorporates elements of Quality, Data mining, Graphplan and Reachability.
His biological study spans a wide range of topics, including Generalized algorithm, Distance measures and Operations research. Subbarao Kambhampati has researched Plan in several fields, including Domain, Domain model, Task, Structure and Set. His work in the fields of Mathematical optimization, such as Heuristic and Integer programming, overlaps with other areas such as Forward chaining.
His primary areas of investigation include Artificial intelligence, Plan, Planner, Machine learning and Mathematical optimization. His work carried out in the field of Artificial intelligence brings together such families of science as Domain, Action and Set. Human–computer interaction and Task is closely connected to Robot in his research, which is encompassed under the umbrella topic of Plan.
His Planner research integrates issues from Theoretical computer science, Software engineering and Empirical research. Heuristic, Heuristics and Integer programming are the core of his Mathematical optimization study. His studies examine the connections between Heuristics and genetics, as well as such issues in Graphplan, with regards to Constraint satisfaction problem.
His primary areas of study are Task, Plan, Artificial intelligence, Human–computer interaction and Robot. The Task study combines topics in areas such as Variety, Counterfactual thinking, Cognitive science and Process management. His study in Plan is interdisciplinary in nature, drawing from both Adversarial system, Legibility, Operations research and Domain.
His studies in Artificial intelligence integrate themes in fields like Machine learning and Action. His research investigates the link between Human–computer interaction and topics such as Behavior-based robotics that cross with problems in Interpretability. His Robot research is multidisciplinary, incorporating perspectives in Task analysis and Set.
His main research concerns Data science, Set, Cloud computing, Task and Point. His research in Set intersects with topics in Action, Natural language processing, Scripting language, Variety and Internet privacy. His study in Cloud computing is interdisciplinary in nature, drawing from both Computer security, Network security, Scalability and Stackelberg competition.
The various areas that Subbarao Kambhampati examines in his Stackelberg competition study include Artificial neural network, Intrusion detection system, Artificial intelligence and Network interface. The concepts of his Task study are interwoven with issues in Scheme, Robot, Cognitive science and Order. Subbarao Kambhampati combines subjects such as Cognitive psychology and Empirical research with his study of Robot.
This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.
What We Instagram: A First Analysis of Instagram Photo Content and User Types
Yuheng Hu;Lydia Manikonda;Subbarao Kambhampati.
international conference on weblogs and social media (2014)
Multiresolution path planning for mobile robots
S. Kambhampati;L. Davis.
international conference on robotics and automation (1986)
A validation-structure-based theory of plan modification and reuse
Subbarao Kambhampati;James A. Hendler.
Artificial Intelligence (1992)
Sapa: a multi-objective metric temporal planner
Minh B. Do;Subbarao Kambhampati.
Journal of Artificial Intelligence Research (2003)
Planning as refinement search: a unified framework for evaluating design tradeoffs in partial-order planning
Subbarao Kambhampati;Craig A. Knoblock;Qiang Yang.
Artificial Intelligence (1995)
Integration of biological sources: current systems and challenges ahead
Thomas Hernandez;Subbarao Kambhampati.
international conference on management of data (2004)
Planning as constraint satisfaction: solving the planning graph by compiling it into CSP
Minh Binh Do;Subbarao Kambhampati.
Artificial Intelligence (2001)
Reviving partial order planning
XuanLong Nguyen;Subbarao Kambhampati.
international joint conference on artificial intelligence (2001)
Planning and scheduling
Thomas L. Dean;Subbarao Kambhampati.
The Computer Science and Engineering Handbook (1997)
When is temporal planning really temporal
William Cushing;Subbarao Kambhampati;Daniel S. Weld.
international joint conference on artificial intelligence (2007)
If you think any of the details on this page are incorrect, let us know.
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: