Seyed Mohammad Khansari-Zadeh

Orcid: 0000-0001-9093-6977

Affiliations:
  • Stanford University, Stanford, CA, USA


According to our database1, Seyed Mohammad Khansari-Zadeh authored at least 15 papers between 2010 and 2025.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

Legend:

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PhD thesis 
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Bibliography

2025
On the Applicability of the Power Law Signature in the Cyber Security Data.
Proceedings of the 29th International Computer Conference, Computer Society of Iran, 2025

2017
Learning potential functions from human demonstrations with encapsulated dynamic and compliant behaviors.
Auton. Robots, 2017

2016
Adaptive human-inspired compliant contact primitives to perform surface-surface contact under uncertainty.
Int. J. Robotics Res., 2016

2015
Incremental motion learning with locally modulated dynamical systems.
Robotics Auton. Syst., 2015

Open-source benchmarking for learned reaching motion generation in robotics.
Paladyn J. Behav. Robotics, 2015

2014
Learning control Lyapunov function to ensure stability of dynamical system-based robot reaching motions.
Robotics Auton. Syst., 2014

Modeling robot discrete movements with state-varying stiffness and damping: A framework for integrated motion generation and impedance control.
Proceedings of the Robotics: Science and Systems X, 2014

2012
A dynamical system approach to realtime obstacle avoidance.
Auton. Robots, 2012

Learning to Play Minigolf: A Dynamical System-Based Approach.
Adv. Robotics, 2012

2011
Learning Stable Nonlinear Dynamical Systems With Gaussian Mixture Models.
IEEE Trans. Robotics, 2011

Vision-Based Navigation in Autonomous Close Proximity Operations using Neural Networks.
IEEE Trans. Aerosp. Electron. Syst., 2011

Learning Non-linear Multivariate Dynamics of Motion in Robotic Manipulators.
Int. J. Robotics Res., 2011

Learning to control planar hitting motions in a minigolf-like task.
Proceedings of the 2011 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2011

2010
Imitation learning of globally stable non-linear point-to-point robot motions using nonlinear programming.
Proceedings of the 2010 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2010

BM: An iterative algorithm to learn stable non-linear dynamical systems with Gaussian mixture models.
Proceedings of the IEEE International Conference on Robotics and Automation, 2010


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