What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Microsoft Windows
- Computer vision
His main research concerns Human–computer interaction, Computer graphics, Artificial intelligence, Gesture and Computer vision.
He has researched Human–computer interaction in several fields, including Creative visualization and Fitts's law.
As part of the same scientific family, Ravin Balakrishnan usually focuses on Computer graphics, concentrating on Visualization and intersecting with Situated and Match moving.
His study in Leverage and Visual feedback is carried out as part of his Artificial intelligence studies.
His Gesture research incorporates themes from Sketch and Tracking.
His work on Cursor, Segmentation and Pointer as part of general Computer vision study is frequently connected to Exploit, therefore bridging the gap between diverse disciplines of science and establishing a new relationship between them.
His most cited work include:
- Interactive public ambient displays: transitioning from implicit to explicit, public to personal, interaction with multiple users (543 citations)
- Multi-finger and whole hand gestural interaction techniques for multi-user tabletop displays (512 citations)
- The bubble cursor: enhancing target acquisition by dynamic resizing of the cursor's activation area (409 citations)
What are the main themes of his work throughout his whole career to date?
Ravin Balakrishnan spends much of his time researching Human–computer interaction, Artificial intelligence, Computer vision, Computer graphics and Gesture.
His studies deal with areas such as Object, Multimedia and Collaborative software as well as Human–computer interaction.
His work in Artificial intelligence addresses issues such as Input device, which are connected to fields such as Simulation.
Computer vision is closely attributed to Fitts's law in his work.
His Computer graphics research incorporates elements of Visualization and 3D interaction.
His work on Interaction technique is typically connected to Set as part of general Gesture study, connecting several disciplines of science.
He most often published in these fields:
- Human–computer interaction (37.16%)
- Artificial intelligence (34.43%)
- Computer vision (29.51%)
What were the highlights of his more recent work (between 2011-2020)?
- Human–computer interaction (37.16%)
- Artificial intelligence (34.43%)
- Gesture (16.94%)
In recent papers he was focusing on the following fields of study:
Ravin Balakrishnan focuses on Human–computer interaction, Artificial intelligence, Gesture, Computer vision and Multimedia.
His work on Virtual reality as part of general Human–computer interaction research is frequently linked to Interface, thereby connecting diverse disciplines of science.
His research on Artificial intelligence focuses in particular on Visualization.
His Gesture research is multidisciplinary, relying on both Virtual image, Fitts's law and Feature.
The various areas that Ravin Balakrishnan examines in his Computer vision study include Animation, Wearable computer and Haptic technology.
His biological study spans a wide range of topics, including Mobile interaction and Modality.
Between 2011 and 2020, his most popular works were:
- mClerk: enabling mobile crowdsourcing in developing regions (115 citations)
- Interactive Exploration of Implicit and Explicit Relations in Faceted Datasets (69 citations)
- DualKey: Miniature Screen Text Entry via Finger Identification (52 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Microsoft Windows
- Computer vision
His primary scientific interests are in Multimedia, Human–computer interaction, Wearable computer, Identification and Artificial intelligence.
His research integrates issues of Mobile interaction, Modality and CAPTCHA in his study of Multimedia.
Human–computer interaction is closely attributed to Task in his study.
The Wearable computer study combines topics in areas such as Simulation, Haptic technology and Text entry.
The concepts of his Identification study are interwoven with issues in Embedded system and Cognitive effort.
His research in the fields of Feature and Gesture overlaps with other disciplines such as Forearm and Sampling.
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