What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Neuroscience
- Computer vision
Mandayam A. Srinivasan mainly focuses on Haptic technology, Artificial intelligence, Computer vision, Human–computer interaction and Biomedical engineering.
His study looks at the relationship between Haptic technology and topics such as Computer graphics, which overlap with Taxonomy and Metaverse.
His Artificial intelligence study frequently draws connections between related disciplines such as Robust control.
The various areas that he examines in his Computer vision study include Robotics and Tactile sensor.
His study looks at the relationship between Human–computer interaction and fields such as Multimedia, as well as how they intersect with chemical problems.
His Biomedical engineering study incorporates themes from Mechanoreceptor, Compressibility, Neuroscience and Sensory receptor.
His most cited work include:
- Real-time prediction of hand trajectory by ensembles of cortical neurons in primates (1230 citations)
- Haptics in virtual environments: Taxonomy, research status, and challenges (459 citations)
- Human factors for the design of force-reflecting haptic interfaces (369 citations)
What are the main themes of his work throughout his whole career to date?
His scientific interests lie mostly in Haptic technology, Artificial intelligence, Computer vision, Human–computer interaction and Simulation.
His research in Haptic technology tackles topics such as Computer graphics which are related to areas like Teleoperation.
Mandayam A. Srinivasan has included themes like Illusion, Planar and Neuroprosthetics in his Artificial intelligence study.
In the field of Computer vision, his study on Stylus overlaps with subjects such as Texture.
The study incorporates disciplines such as Haptic communication and Set in addition to Human–computer interaction.
His Simulation research incorporates themes from Soft tissue and Nonlinear system.
He most often published in these fields:
- Haptic technology (40.12%)
- Artificial intelligence (27.91%)
- Computer vision (22.09%)
What were the highlights of his more recent work (between 2013-2021)?
- Artificial intelligence (27.91%)
- Biological system (7.56%)
- Computer vision (22.09%)
In recent papers he was focusing on the following fields of study:
His primary areas of investigation include Artificial intelligence, Biological system, Computer vision, Tactile sensor and Caenorhabditis elegans.
His study in the field of Image resolution and Magnification is also linked to topics like West africa and Sub saharan.
His Computer vision study combines topics in areas such as Deep learning, Visual servoing and Blood film.
His Tactile sensor study combines topics from a wide range of disciplines, such as Robotics and Electrical engineering.
He focuses mostly in the field of Cognitive neuroscience of visual object recognition, narrowing it down to topics relating to Eye movement and, in certain cases, Haptic technology.
His research integrates issues of Rehabilitation, Human–computer interaction and Fixation in his study of Haptic technology.
Between 2013 and 2021, his most popular works were:
- Localization and Manipulation of Small Parts Using GelSight Tactile Sensing (117 citations)
- Measurement of shear and slip with a GelSight tactile sensor (98 citations)
- Shape-independent hardness estimation using deep learning and a GelSight tactile sensor (41 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Neuroscience
- Electrical engineering
Mandayam A. Srinivasan focuses on Computer vision, Artificial intelligence, Tactile sensor, Robot and Slip.
His Computer vision study integrates concerns from other disciplines, such as Grippers, Robotics and Visual servoing.
His Robotics research includes themes of Matching, Tracking, Feature and Robust control.
His Robot hand study, which is part of a larger body of work in Robot, is frequently linked to Torsional load, GRASP and Shear force, bridging the gap between disciplines.
Many of his Slip research pursuits overlap with Contact force, Deep learning, Silicone and Cognitive neuroscience of visual object recognition.
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