What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Operating system
- The Internet
Thad Starner spends much of his time researching Wearable computer, Artificial intelligence, Human–computer interaction, Computer vision and Gesture.
Thad Starner interconnects Context, Interface, Augmented reality and Gesture recognition in the investigation of issues within Wearable computer.
His Artificial intelligence research is multidisciplinary, incorporating elements of Speech recognition and Line.
The concepts of his Human–computer interaction study are interwoven with issues in Wireless, User interface, Locust and Mobile computing.
His research integrates issues of Computer graphics, Mobile device and Task in his study of Computer vision.
His Gesture study combines topics from a wide range of disciplines, such as Event, Input device, Magnet and Pattern recognition.
His most cited work include:
- Energy scavenging for mobile and wireless electronics (2211 citations)
- Real-time American sign language recognition using desk and wearable computer based video (1070 citations)
- Using GPS to learn significant locations and predict movement across multiple users (954 citations)
What are the main themes of his work throughout his whole career to date?
His primary areas of investigation include Wearable computer, Artificial intelligence, Human–computer interaction, Computer vision and Gesture.
As a member of one scientific family, Thad Starner mostly works in the field of Wearable computer, focusing on Mobile computing and, on occasion, Mobile phone.
His work carried out in the field of Artificial intelligence brings together such families of science as Natural language processing, Speech recognition, American Sign Language, Accelerometer and Pattern recognition.
His research integrates issues of Context, User interface, Smartwatch, Mobile device and Haptic technology in his study of Human–computer interaction.
As part of his studies on Computer vision, Thad Starner frequently links adjacent subjects like Computer graphics.
His Gesture study focuses on Gesture recognition in particular.
He most often published in these fields:
- Wearable computer (40.58%)
- Artificial intelligence (27.23%)
- Human–computer interaction (26.44%)
What were the highlights of his more recent work (between 2015-2021)?
- Wearable computer (40.58%)
- Human–computer interaction (26.44%)
- Gesture (16.49%)
In recent papers he was focusing on the following fields of study:
His main research concerns Wearable computer, Human–computer interaction, Gesture, Artificial intelligence and Computer vision.
His Wearable computer research focuses on subjects like Movement, which are linked to Speech interface and Head.
His Human–computer interaction study incorporates themes from Interface, Kinesthetic learning, Smartwatch, Focus and Haptic technology.
The various areas that Thad Starner examines in his Gesture study include User experience design, Speech recognition, Computer hardware and E-textiles.
His Artificial intelligence research is multidisciplinary, incorporating perspectives in Signal and User studies.
He usually deals with Computer vision and limits it to topics linked to Reading and Optical head-mounted display.
Between 2015 and 2021, his most popular works were:
- EarBit: Using Wearable Sensors to Detect Eating Episodes in Unconstrained Environments (72 citations)
- TapSkin: Recognizing On-Skin Input for Smartwatches (36 citations)
- Smooth eye movement interaction using EOG glasses (26 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Operating system
- The Internet
Wearable computer, Human–computer interaction, Artificial intelligence, Computer vision and Gesture are his primary areas of study.
In his works, Thad Starner undertakes multidisciplinary study on Wearable computer and Order picking.
Thad Starner has included themes like Interface, Smartwatch, Mobile interfaces and Haptic technology in his Human–computer interaction study.
His work on Eye tracking and Finger movement as part of his general Artificial intelligence study is frequently connected to Thumb and Nose, thereby bridging the divide between different branches of science.
His Computer vision research is multidisciplinary, relying on both Eyewear and Nose bridge.
Thad Starner interconnects Speech recognition and User studies in the investigation of issues within Gesture.
This overview was generated by a machine learning system which analysed the scientist’s
body of work. If you have any feedback, you can
contact us
here.
