ADWAIT SHARMA
HCI Researcher
I like to design and recognize hand gestures for always-available input
ABOUT
I am a Lecturer (Assistant Professor) in the Department of Computer Science at the University of Bath.
My research focuses on enabling interaction with computers in challenging situations. Specifically, while users' hands are encumbered holding everyday objects. This always-available input has a wide range of applications, from controlling mobile devices when on the move to controlling systems in healthcare contexts. To build an entire stack of such novel input experiences, my work employs:
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interaction design by understanding user preferences,
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creation and empirical analysis of large-scale datasets,
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machine learning models for real-time recognition.
I recently received my Ph.D. from the Human-Computer Interaction group at the Max Planck Institute for Informatics and Saarland University, advised by Prof. Jürgen Steimle. I completed my masters at the Media Interaction Lab, advised by Prof. Michael Haller.
I have also worked at Meta Reality Labs with Stephanie Santosa and Prof. Tovi Grossman. Previously, I worked with Prof. Daniel Ashbrook at the University of Copenhagen and with Prof. Ellen Yi-Luen Do at the National University of Singapore. I have also been fortunate to work with the Parkinson's Research Group at the UBC Hospital in Vancouver, and contributed to Open-source communities (Mozilla and Python).
NOTABLE PUBLICATIONS
Note about publication venues: In my area of research, ACM CHI and UIST are the top-most and highly impactful venues (Google Scholar and Microsoft Academic both rank CHI as the #1 venue). The review process in these venues is multi-stage and very selective for each publication, involving 4-6 international subject-matter experts.
SparseIMU:
Computational Design of Sparse IMU Layouts for Sensing Fine-Grained Finger Microgestures
Accepted at ACM TOCHI
Adwait Sharma, Christina Salchow-Hömmen, Vimal S. Mollyn, Aditya S. Nittala, Michael A. Hedderich, Marion Koelle, Thomas Seel, Jürgen Steimle
Computational design tool to solve a multi-factorial problem of recognizing always-available input with minimal sensors.
Email me for preprint
SoloFinger:
Robust Microgestures while Grasping Everyday Objects
In Proc. of ACM CHI
Adwait Sharma, Michael A. Hedderich, Divyanshu Bhardwaj, Bruno Fruchard, Jess McIntosh, Aditya S. Nittala, Dietrich Klakow, Daniel Ashbrook, Jürgen Steimle
Easy and rapid-to-perform gestures, which are resilient to false activations.
Grasping Microgestures:
Eliciting Single-hand Microgestures for Handheld Objects
In Proc. of ACM CHI
Adwait Sharma, Joan Sol Roo, Jürgen Steimle
Analysis of over 2,400 user-generated microgestures while holding an everyday object.
SmartSleeve:
Real-time Sensing of Surface and Deformation Gestures on Flexible, Interactive Textiles, using a Hybrid Gesture Detection Pipeline
In Proc. of ACM UIST
Patrick Parzer, Adwait Sharma, Anita Vogl, Jürgen Steimle, Alex Olwal, Michael Haller