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Antony Irudayaraj

dblp:187/9678 · also Antony Albert Raj Irudayaraj · DBLP profile ↗
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7ranked-venue papers
2as first author
4since 2021 · last 2025
0000-0003-2015-523XORCID · corroborated

Domains — the database's venue-derived domains; a paper can count in several

Human-computer interaction and ubiquitous computing · 7 · 2 first-author · 4 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Human-computer interaction and pervasive computing
6 papers
Wearable and physiological sensing · 43% Interaction techniques and input · 29% Haptics and multimodal interaction · 21%
Computer networks
1 paper
Physical-layer communications · 100%

Topics — the 11 heaviest of 13, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Interaction techniques and input
gesture input
0.822024
Single-handed Folding Interactions with a Modified Clamshell Flip Phone · CHI 2024
Haptic Learning of Semaphoric Finger Gestures · UIST 2016
Haptics and multimodal interaction
wearable haptic device
0.522017
HapticClench: Investigating Squeeze Sensations using Memory Alloys · UIST 2017
Haptic Learning of Semaphoric Finger Gestures · UIST 2016
Haptics and multimodal interaction
haptic feedback
0.312017
HapticClench: Investigating Squeeze Sensations using Memory Alloys · UIST 2017
Haptics and multimodal interaction › haptic actuator
shape memory alloy actuator
0.312017
HapticClench: Investigating Squeeze Sensations using Memory Alloys · UIST 2017
Interaction techniques and input › input sensing
gesture sensing
0.312025
SparseEMG: Computational Design of Sparse EMG Layouts for Sensing Gestures · UIST 2025
Physical-layer communications › optical wireless communication
visible light communication
0.312025
LightLink: Enhancing Smartwatch Sensing and Actuation Through Visible Light Communication · UIST 2025
Learning and educational technologies › embodied learning
haptic learning
0.212016
Haptic Learning of Semaphoric Finger Gestures · UIST 2016
Interaction techniques and input
mobile interaction
0.212024
Single-handed Folding Interactions with a Modified Clamshell Flip Phone · CHI 2024
Interaction techniques and input › mobile interaction
one-handed interaction
0.212024
Single-handed Folding Interactions with a Modified Clamshell Flip Phone · CHI 2024
Ubiquitous computing and smart environments › interruption management
notification presentation
0.112021
PocketView: Through-Fabric Information Displays · UIST 2021
Wearable and physiological sensing › smart wearable
wrist-worn device
0.112017
HapticClench: Investigating Squeeze Sensations using Memory Alloys · UIST 2017

Methods — techniques the papers use, named apart from their topics

visible light communication · 1.7sensor and actuator add-ons · 1.7user study · 0.8prototype evaluation · 0.8light transmission through fabric · 0.5LED matrix displays · 0.5shape memory alloy actuation · 0.3psychophysical evaluation · 0.3two-day user study · 0.2multimodal stimuli coupling · 0.2
YearPublicationVenuePosition
2025 LightLink: Enhancing Smartwatch Sensing and Actuation Through Visible Light Communication
abstract
Figure 1: LightLink enables adding different sensor and actuator add-ons to a smartwatch: (a) shows a person blowing into a bezel mounted alcohol sensor for on-demand breath alcohol level measurement; (b) four button user interface attached to the watch strap for eyes-free interaction; (c) Tilt switch sensor band attached to the forearm to track reps count in exercises; (d) Vibration band attached to the forearm to deliver haptic patterns; (e) LED display add-on attached to the watch strap for quicker and easier viewing of notifications/navigation instructions.
Antony Irudayaraj, Aditya Shekhar Nittala
UIST1
2025 SparseEMG: Computational Design of Sparse EMG Layouts for Sensing Gestures
Antony Irudayaraj, Ishita Chandra, Adwait Sharma, Aditya Shekhar Nittala
UIST2
2024 Single-handed Folding Interactions with a Modified Clamshell Flip Phone
abstract
We explore and evaluate single-handed folding interactions suitable for “modified clamshell flip phones” with a full screen touch display that folds in half along the short dimension. Three categories of interactions are identified: only-fold, touch-enhanced fold, and fold-enhanced touch; in which gestures are created using fold direction, fold magnitude, and touch position. A prototype evaluation device is built to resemble clamshell flip phones, but with a modified hinge and spring system to enable folding in both directions. A study investigates performance and preference for 30 fold gestures to discover which are most promising. To demonstrate how folding interactions could be incorporated into flip phone interfaces, applications such as map browsing, text editing, and menu shortcuts are described.
Yen-Ting Yeh 0001, Antony Irudayaraj, Daniel Vogel 0001
CHI2
2021 PocketView: Through-Fabric Information Displays
abstract
People often have to remove their phone from an inaccessible location like a pocket to view things like notifications and directions. We explore the idea of viewing such information through the fabric of a pocket using low resolution bright LED matrix displays. A survey confirms viewing information on inaccessible phones is desirable, and establishes types of pockets in garments worn by respondents and what objects are typically put in pockets. A technical evaluation validates that LED light can shine through many common garment fabrics. Based on these results, functional hardware prototypes are constructed to demonstrate different form factors of through-fabric display devices, such as a phone, wallet, a key fob, a pen, and earbud headphone case. A simple interaction vocabulary for viewing key information on these devices is described, and the social and technical aspects of the approach are discussed.
Antony Irudayaraj, Rishav Agarwal, Nikhita Joshi, Aakar Gupta, Omid Abari, Daniel Vogel 0001
UIST1
2020 Expanding Side Touch Input on Mobile Phones: Finger Reachability and Two-Dimensional Taps and Flicks using the Index and Thumb
abstract
We investigate the performance of one-handed touch input on the side of a mobile phone. A first experiment examines grip change and subjective preference when reaching for side targets using different fingers. Results show all locations can be reached with at least one finger, but the thumb and index are most preferred and require less grip change for positions along the sides. Two following experiments examine taps and flicks using the thumb and index finger in a new two-dimensional input space. A side-touch sensor is simulated with a combination of capacitive sensing and motion tracking to distinguish touches on the lower, middle, or upper edges. When tapping, index and thumb speeds are similar with thumb more accurate and comfortable, and the lower edge is most reliable with the middle edge most comfortable. When flicking with the thumb, the upper edge is fast and rated highly.
Yen-Ting Yeh 0001, Quentin Roy, Antony Irudayaraj, Daniel Vogel 0001
Proc. ACM Hum. Comput. Interact.3
2017 HapticClench: Investigating Squeeze Sensations using Memory Alloys
abstract
Squeezing sensations are one of the most common and intimate forms of human contact. In this paper, we investigate HapticClench, a device that generates squeezing sensations using shape memory alloys. We define squeezing feedback in terms of it perceptual properties and conduct a psychophysical evaluation of HapticClench. HapticClench is capable of generating up to four levels of distinguishable load and works well in distracted scenarios. HapticClench has a high spatial acuity and can generate spatial patterns on the wrist that the user can accurately recognize. We also demonstrate the use of HapticClench for communicating gradual progress of an activity, and for generating squeezing sensations using rings and loose bracelets.
Aakar Gupta, Antony Irudayaraj, Ravin Balakrishnan
UIST2
2016 Haptic Learning of Semaphoric Finger Gestures
abstract
Haptic learning of gesture shortcuts has never been explored. In this paper, we investigate haptic learning of a freehand semaphoric finger tap gesture shortcut set using haptic rings. We conduct a two-day study of 30 participants where we couple haptic stimuli with visual and audio stimuli, and compare their learning performance with wholly visual learning. The results indicate that with <30 minutes of learning, haptic learning of finger tap semaphoric gestures is comparable to visual learning and maintains its recall on the second day.
Aakar Gupta, Antony Irudayaraj, Vimal Chandran, Goutham Palaniappan, Khai N. Truong, Ravin Balakrishnan
UIST2