Aaron D’Souza

866 citations
14 papers · 597 · h-index 10

Impact in

    • Robot Manipulation and Learning
    • Fault Detection and Control Systems
    • Control Systems and Identification
    • Robotic Mechanisms and Dynamics
    • Gaussian Processes and Bayesian Inference
    • Reinforcement Learning in Robotics

Papers in

Aaron D’Souza

13 papers receiving 559 citations

Peers

Aaron D’Souza
Comparison fields: 5 of 80
  • Control and Systems Engineering 298
  • Artificial Intelligence 262
  • Cognitive Neuroscience 105
  • Computer Vision and Pattern Recognition 100
  • Statistics, Probability and Uncertainty 22
Replace Jo-Anne Ting with:
Jo-Anne Ting United States
Li Xie China
K. Ramkumar India
J.M. Izquierdo Spain
Wonkeun Youn South Korea
Régis Lengelle France
H. Daniel Patiño Argentina
Francesco Gianfelici Italy
C. Doncarli France
Bruce A. Whitehead United States
Aaron D’Souza relative to Jo-Anne Ting United States Jo-Anne Ting's profile →
Citations per field
00.5×1.5×1.9×
Jo-Anne Ting · 1×
Citations per year

Countries citing papers authored by Aaron D’Souza

Since Specialization
Citations

This map shows the geographic impact of Aaron D’Souza's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Aaron D’Souza with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Aaron D’Souza more than expected).

Fields of papers citing papers by Aaron D’Souza

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Aaron D’Souza. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Aaron D’Souza. The network helps show where Aaron D’Souza may publish in the future.

Co-authors

The 17 scholars most cited alongside Aaron D’Souza, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Aaron D’Souza Line = papers co-authored together Aaron D’Souza links everyone, so they are left out of the graph.

All Works

14 of 14 papers shown
#Work
1 2005374
2 200259
3 200726
4 200826
5 201024
6 200418
7 200917
8
LWPR: A Scalable Method for Incremental Online Learning in High Dimensions
200515
9 200813
10
Predicting EMG Data from M1 Neurons with Variational Bayesian Least Squares
200510
11 20069
12
Real-time statistical learning for robotics and human augmentation
20013
13
Towards tractable parameter-free statistical learning
20043
14 20250

About Aaron D’Souza

Aaron D’Souza is a scholar working on Artificial Intelligence, Control and Systems Engineering, Signal Processing, Computational Mechanics and Cognitive Neuroscience, having authored 14 papers that have together received 597 indexed citations. Recurring topics across this work include Gaussian Processes and Bayesian Inference (7 papers), Fault Detection and Control Systems (3 papers), Control Systems and Identification (3 papers), Sparse and Compressive Sensing Techniques (3 papers), EEG and Brain-Computer Interfaces (2 papers), Robot Manipulation and Learning (2 papers), Blind Source Separation Techniques (2 papers) and Neural dynamics and brain function (2 papers). The work is most often cited by research in Control and Systems Engineering (298 citations), Artificial Intelligence (262 citations), Cognitive Neuroscience (105 citations), Computer Vision and Pattern Recognition (100 citations) and Statistics, Probability and Uncertainty (22 citations). Aaron D’Souza has collaborated with scholars based in United States, United Kingdom and Japan. Frequent co-authors include Stefan Schaal, Sethu Vijayakumar, Jo-Anne Ting, Jörg Conradt, Tomohiro Shibata, Donna S. Hoffman, Toshinori Yoshioka, Lauren E. Sergio, Shinji Kakei and Kenji Yamamoto. Their work appears in journals such as Neural Networks, Neural Computation, Autonomous Robots, Infoscience (Ecole Polytechnique Fédérale de Lausanne) and ERA.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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