The chart shows the distribution of publications by all Research.com ranked scientists in the field of Computer Science in 2026. The highlighted bar marks where Sridha Sridharan sits on this spectrum.
This scientist: 693 publications — 98th percentile
98% of scientists in this discipline score the same or lower.
The last bar groups every scientist with 991 publications or more.
The chart shows the D-index (discipline H-index) distribution of Computer Science scientists ranked by Research.com in 2026. The highlighted bar marks where Sridha Sridharan sits on this spectrum.
This scientist: 73 D-Index — 89th percentile
89% of scientists in this discipline score the same or lower.
The last bar groups every scientist with 131 D-Index or more.
Sridha Sridharan is affiliated with the Queensland University of Technology in Australia and specializes primarily in the field of Computer Science. Their publication record includes a strong focus on subfields such as Computer Vision and Pattern Recognition, Artificial Intelligence, Aerospace Engineering, Cognitive Neuroscience, and Signal Processing.
The scientist's research topics center on areas including Video Surveillance and Tracking Methods, Advanced Neural Network Applications, Human Pose and Action Recognition, Domain Adaptation and Few-Shot Learning, Advanced Image and Video Retrieval Techniques, Face Recognition and Analysis, and Robotics and Sensor-Based Localization.
Recent papers illustrate a focus on biomedical and healthcare applications involving deep learning and EEG signal analysis. Notable works include:
Sridharan collaborates frequently with researchers such as Clinton Fookes, Simon Denman, Tharindu Fernando, Peyman Moghadam, and Kien Nguyen. These coauthors appear consistently across their extensive body of work.
Their publications have appeared in venues with a strong emphasis on both open-access and peer-reviewed platforms. The most frequent venues are:
The research spans many interdisciplinary applications, combining advanced machine learning techniques with practical implementations in medical diagnosis, robotics, and cognitive science. Their work on deep learning applied to EEG signals and biomedical data reflects an interest in health informatics and neural data interpretation.
Overall, Sridha Sridharan contributes to a wide range of subjects within computer science, with a notable focus on neural networks, vision-related pattern recognition, and sensor-data-driven approaches.
Jason W. Pelecanos;Sridha Sridharan
Tharindu Fernando;Simon Denman;Sridha Sridharan;Clinton Fookes
Kien Nguyen;Clinton Fookes;Arun Ross;Sridha Sridharan
David Ryan;Simon Denman;Clinton Fookes;Sridha Sridharan
P Lucey;J F Cohn;I Matthews;S Lucey
A. Busch;W.W. Boles;S. Sridharan
Tharindu Fernando;Harshala Gammulle;Simon Denman;Sridha Sridharan
Ahilan Kanagasundaram;Robbie Vogt;David Dean;Sridha Sridharan
Harshala Gammulle;Simon Denman;Sridha Sridharan;Clinton Fookes
Alina Bialkowski;Patrick Lucey;Peter Carr;Yisong Yue
David B. Dean;Sridha Sridharan;Robert J. Vogt;Michael W. Mason
Robbie Vogt;Sridha Sridharan
Kien Nguyen;Clinton Fookes;Raghavender Jillela;Sridha Sridharan
Sabesan Sivapalan;Daniel Chen;Simon Denman;Sridha Sridharan
S. Vidas;R. Lakemond;S. Denman;C. Fookes
Alina Bialkowski;Simon Denman;Sridha Sridharan;Clinton Fookes
David Ryan;Simon Denman;Sridha Sridharan;Clinton Fookes
D. Butler;S. Sridharan;V.M.Jr. Bove
Theekshana Dissanayake;Tharindu Fernando;Simon Denman;Sridha Sridharan
Tharindu Fernando;Houman Ghaemmaghami;Simon Denman;Sridha Sridharan
Sien. W. Chew;Patrick Lucey;Simon Lucey;Jason Saragih
K. Messer;J. Kittler;M. Sadeghi;M. Hamouz
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