Ransalu Senanayake




I am a postdoctoral scholar at the Stanford Intelligent Systems Laboratory (SISL), working with Prof. Mykel Kochenderfer. I completed my PhD in Robot Learning and Machine Learning in Prof. Fabio Ramos' group at the School of Computer Science in the University of Sydney.


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Postdoctoral scholar, Mar. 2019 - present

PhD in Computer Science, Mar. 2015 - Feb. 2019
   - University: The University of Sydney, Australia
   - Major Research Area: Nonlinear methods for modeling spatiotemporal phenomena
   
MPhil in Industrial Engineering, Aug. 2013 
   - Major Research Area: Human Factors in Human-Computer Interaction

BEng (Hons) in Electronic Engineering (First Class), Nov. 2011
   - University: Sheffield Hallam University (SHU), Sheffield, UK
   - Studied at:  Sri Lanka Institute of Information Technology, Sri Lanka






 


While advancing robots towards full autonomy, it is important to minimize deleterious effects on human and infrastructure. To achieve this, I have been developing data-efficient robotic mapping techniques that capture uncertainty in dynamic environments. By modeling the nonlinear spatiotemporal relationships, these techniques can characterize the uncertainty in long-term and short-term patterns of occupancy, speed, and directions. Since these maps represent uncertainty, they can then be used for robust decision-making.



  News

 June - I am co-organizing a workshop on safety aspects of robotics at R:SS 2019.

 April - Bayesian Hilbert maps code with demos/tutorials has been updated. 



  Peer-Reviewed Publications

 Authors
 Paper
 Conference/Journal
 Year
 Weiming Zhi, Ransalu Senanayake, Lionel Ott, and Fabio Ramos

 Spatiotemporal Directional Mapping

 IEEE Robotics and Automation Letters (RA-L)  2019
 Vitor Guizilini, Ransalu Senanayake, Fabio Ramos

 Dynamic Hilbert Maps: Real-Time Occupancy Predictions in Changing Environments

 The International Conference on Robotics and Automation (ICRA), Montreal 2019
 Weiming Zhi, Lionel Ott, Ransalu Senanayake, Fabio Ramos

 Continuous Occupancy Map Fusion with Fast Bayesian Hilbert Maps

 The International Conference on Robotics and Automation (ICRA), Montreal 2019
 A. Tompkins*, R. Senanayake*, P. Morere*, F. Ramos

 Black-box Quantiles for Kernel Learning [paper][video][code]

The 22nd International Conference on Artificial Intelligence and Statistics (AISTATS), Okinawa
 2019
  R. Senanayake*, A. Tompkins*, and F. Ramos Automorphing Kernels for Nonstationarity in Mapping Unstructured Environments [paper][video][code]

 Annual Conference on Robot Learning (CoRL), Zurich 2018
  R. Senanayake and
 F. Ramos

 Directional Grid Maps: Modeling Multimodal Angular Uncertainty in Dynamic Environments  [paper][video][code]

 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Madrid 2018
 R. Senanayake and
 F. Ramos

 Continuous Occupancy Mapping with Moving Robots  [link] [video][video][code] 32nd AAAI Conference on Artificial Intelligence (AAAI), New Orleans
 2018
 R. Senanayake and
 F. Ramos
 Bayesian Hilbert Maps for Dynamic Continuous Occupancy Mapping  [link] [video][python][code] Annual Conference on Robot Learning (CoRL), Mountain View
 2017
 R. Senanayake,
 S. O'Callaghan, and
 F. Ramos

 Learning Highly Dynamic Environments with Stochastic Variational Inference [link] [video][code] The International Conference on Robotics and Automation (ICRA), Singapore
 2017
 R. Senanayake,
 L. Ott,  
 S. O'Callaghan, and
 F. Ramos

 Spatio-Temporal Hilbert Maps for Continuous Occupancy Representation in Dynamic Environments [link] [video] 30th Annual Conference on Neural Information Processing Systems (NIPS), Barcelona  2016
 R. Senanayake,
 S. O'Callaghan, and
 F. Ramos
 Predicting Spatio‐Temporal Propagation of Seasonal Influenza using Variational Gaussian Process Regression [link] [video] 30th AAAI Conference on Artificial Intelligence (AAAI), Phoenix  2016
 R. Senanayake and
 R. Goonetilleke
 Pointing device performance in steering tasks [link] Perceptual and Motor Skills  2016
 A. Ravendran,
 R. de Silva, and
 R. Senanayake

 Moment Invariant Features for Automatic Identification of Critical Malaria Parasites [link] 10th IEEE International Conference on Industrial and Information Systems, Peradeniya  2015 
 R. Senanayake and
 R. Goonetilleke
 Targeted-Tracking With Pointing Devices [link] IEEE Transactions on Human-Machine Systems  2015
 R. Senanayake,
 E. Hoffmann, and
 R. Goonetilleke
 A Model for Combined Targeting Tracking Tasks in Computer Applications [link] Experimental Brain Research  2013
 R. Senanayake and
 R. Goonetilleke
 Superiority of Freehand Pointing [link] 57th Annual Meeting of the Human Factors and Ergonomic Society (HFES), San Diego  2013
 R. Senanayake and
 R. Goonetilleke
 Setting that Mouse for Tracking Tasks [link]  15th International Conference on Human-Computer Interaction (HCII), Las Vegas  2013
 A. de Silva,
 M, Wijesundara, and
 R. Senanayake
 Computer Controlled Digital Microscope with Photomicrograph Enhancement Proceedings of the IEEE International Conference on Information and Communication Technology, Bandung  2013
 R. Senanayake and
 S. Kumarawadu
 A Robust Vision-based Hand Gesture Recognition System for Appliance Control in Smart Homes [video] [video]

 IEEE International Conference on Signal Processing, Communications and Computing, Hong Kong  2012
       
 
Workshops

 
    
Ransalu Senanayake, Maneekwan Toyungyernsub, Mingyu Wang,Mykel Kochenderfer, and Mac Schwager

 Directional Primitives Workshop on Scene and Situation Understanding for Autonomous Driving at the Robotics: Science and Systems (R:SS), Germany

 2019
 Tomas Vintr, et al.

 Spatio-temporal Representation of Time-varying Pedestrian Flows

 Workshop on Long-term Human Motion Prediction  International Conference on Robotics and Automation (ICRA), Montreal

 2019
 A. Tompkins, R. Senanayake, F. Ramos
 Gray-box probabilistic occupancy mapping
 Workshop on Machine Learning for Intelligent Transportation Systems at the 32nd Annual Conference on Neural Information Processing Systems (NIPS), Montreal

 2018
 R. Senanayake and  F. Ramos

 Probabilistic Dynamic Maps for Path Planning
 Robotics: Science and Systems (RSS) Pioneers, Pittsburgh
 2018
 R. Senanayake,
 T. Ganegedara, and
 F. Ramos
 Deep Occupancy Maps: a continuous occupancy mapping technique for dynamic environments [link] [video] Workshop on Machine Learning for Intelligent Transportation Systems at the 31st Annual Conference on Neural Information Processing Systems (NIPS), Long Beach 2017
 R. Senanayake and
 F. Ramos
 Bayesian Hilbert Maps for Continuous Occupancy Mapping in Dynamic Environments [link] [video] Workshop on Machine Learning for Autonomous Vehicles at the 34th International Conference on Machine Learning (ICML), Sydney 2017
 R. Senanayake, 
 S. O'Callaghan, and
 F. Ramos
 Mapping Occupancy of Dynamic Environments using Big Data Gaussian Process Classification [link] [video] Workshop on Machine Learning for Intelligent Transportation Systems at the 30th Annual Conference on Neural Information Processing Systems (NIPS), Barcelona 2016

*Joint leading authors