Call For Papers

Scope and Topics

Among the five human senses, we most heavily rely on sound and vision in our everyday lives. Advances in computer vision have profoundly impacted our daily lives and greatly bridged the gap between human and machine intelligence. However, without exploiting the rich information about the activities, events, and environment around us embedded in audio, it is not possible to fully unleash the potential of machine intelligence. Though many physical characteristics of acoustics have been explored, it has been rarely explored with the lens of pervasive sensing modality in mobile and intelligent systems. Audio presents numerous opportunities, including – (1) reduced power consumption and computational requirements; (2) higher omnidirectional coverage; (3) more susceptibility to physical obstruction; (4) cheaper and smaller sensors; and (5) better privacy preservation. Acoustic intelligence will enable low-power, low-cost, real-time, hands-free, and more interactive communication between machines, humans, and the environment. This workshop aims to push the boundaries of machine intelligence by exploring the sensing, communication, system implementation, algorithm design, and applications of intelligent acoustic systems.

IASA welcomes contributions in all aspects of acoustic sensing, systems, and applications, including – mobile and wearable sensing or communication utilizing sound, vibration, ultrasound, and infrasound, algorithms in acoustic intelligence, security, and privacy utilizing acoustics, and data or deployment experiences.

Topics of interest include, but not limited to:
  • Acoustic mobile applications and embedded systems
  • Novel acoustic sensors
  • Innovative acoustic sensing wearables, devices, and platforms
  • Novel software architectures for audio processing
  • Authentication and verification with audio
  • Privacy preservation of continuous listening devices
  • New acoustic features for information extraction
  • Audio augmented reality, AR/VR/Immersive reality applications of acoustic
  • Audio synthesis
  • Sound localization, denoising, and separation
  • Resource-efficient machine learning and artificial intelligence using acoustic signals
  • Multi-modal sensing and learning where acoustic modality enhances or gets enhanced by other sensing modalities
  • Audio + X; where X = edge computing, localization, battery-less, deep learning, robotics, etc
  • Multi-task learning leveraging wearables with microphones
  • Acoustic passive sensing support for vehicular and mobile robotic systems
  • Acoustic sensing in miniaturized aerial devices
  • Communication with audible sounds, ultra-sounds, infra-sound, and vibration
  • Quality-aware audio data collection with earables and wearables
  • Health and wellbeing applications utilizing acoustic signals
  • Emerging applications in earables based on audio signals

In addition to the research papers, we also invite “Challenge Papers” that present revolutionary new ideas that challenge existing assumptions prevalent among acoustic signal processing, machine learning, and the mobile systems community in general. These “challenge papers” should provide stimulating ideas that may open up exciting avenues and/or influence the direction of future intelligent acoustic research. An exhaustive evaluation of the proposed ideas is not necessary for this category; instead, insight and in-depth understanding of the issues are expected.

Submission Guideline

We invite original research papers that have not been previously published and are not currently under review for publication elsewhere. Submitted papers should be no longer than six pages for research papers and four pages for challenge papers (including references and appendices). Your submission must use a 10pt font (or larger) and be correctly formatted for printing on Letter-sized (8.5" by 11") paper. Paper text blocks must follow ACM guidelines: double-column, with each column 9.25" by 3.33", 0.33" space between columns and single-spaced. The title of challenge papers must bear a "Challenge:" prefix.

Papers are to be submitted at: TBD Papers are to be submitted at

All accepted papers will be published as part of the ACM proceedings.

Important Dates
  • Paper submission: March 13, 2023, AoE
  • Notification of Acceptance: March 24, 2023, AoE
  • Camera Ready Deadline: TBD
  • Workshop Date: May 9, 2023
  • Location: San Antonio, Texas, USA

Workshop committees

General co-Chairs

Xiaofan (Fred) Jiang (Columbia University)
Shahriar Nirjon (University of North Carolina, Chapel Hill)
Nirupam Roy (University of Maryland, College Park)

TPC co-Chairs

Mi Zhang (Ohio State University)
Shijia Pan (University of California, Merced)
Jagmohan Chauhan (University of Southampton)

Steering Committee

Publicity Chair

Social Media Chair

Sponsorship Chair

Web Chair

  • Nakul Garg (University of Maryland, College Park)

Technical Program Committee


Local Time: Central Daylight Time(UTC-5)

9:00 am - 10:00 am Keynote 1: Pei Zhang (University of Michigan, Ann Arbor)

Title: Listening to Structures: Leveraging Building Vibrations to Understand People

Abstract: This talk introduces sensing people using structural vibrations. Occupants and Environments induces vibrations on structures. These induced vibrations range from large vibrations like foot-steps to small vibrations like heartbeats. Measuring these vibrations should allow us to learn information about these persons. However, building vibration is also a mixture of these signals convoluted with the building response that makes this problem especially challenging and often impossible. This talk introduces a combination of techniques that incorporate physical models and hardware characteristics to enable learning in from highly convoluted signal to enable learning with “small data”. We 1) improve sensed data through actuation of the sensing system, 2) incorporate physical characteristics to guide learning, and 3) combine and transfer data from other domains using the physical understanding. This talk illustrates these approaches through our work on Structures-as-Sensors, where a building acts as the physical elements of the sensor; and the structural response is interpreted to obtain information about the occupants. I will present our results through a range of applications through a range of real-world deployments from pristine hospitals and not-so-pristine pig farms.

Bio: Pei Zhang is an Associate Professor in Department of Electrical Engineering and Computer Science at the University of Michigan, Ann Arbor. He received his bachelor's degree from California Institute of Technology in 2002, and his Ph.D. degree in Electrical Engineering from Princeton University in 2008. His early work ZebraNet is considered one of the seminal works in sensor networks, for which he received the SenSys Test-of-Time Award in 2017. His recent work focuses on Cyber-Physical systems that utilizes the physical properties of vehicles and structures to discover surrounding physical information. His work combines machine learning-based data models, physics-based models, as well as heuristic models to improve learning using a small amount of labeled sensor data. His work is applied to the field of medicine, farming, smart retail, and is part of multiple startups. His work has been featured in popular media including CNN, CBS, NBC, Science Channel, Discovery Channel, Scientific American, etc. In addition, he has received various best paper awards, the NSF CAREER award (2012), SenSys Test of Time Award (2017), Google faculty award (2013, 2016), and was a member of the Department of Defense Computer Science Studies Panel.
10:30 am - 12:00 pm Session 1: Robust Acoustic Sensing
1. A Cognitive Scaling Mixer for Concurrent Ultrasound Sensing and Music Playback in Smart Devices
Yin Li (Cornell Tech), Rajalakshmi Nandakumar (Cornell Tech)

2. CaNRun: Non-Contact, Acoustic-based Cadence Estimation on Treadmills using Smartphones
Ziyi Xuan (Columbia University), Ming Liu (Columbia University), Jingping Nie (Columbia University), Minghui Zhao (Columbia University), Stephen Xia (Columbia University), Xiaofan Jiang (Columbia University)

3. Spatial Audio Empowered Smart speakers with Xblock - A Pose-Adaptive Crosstalk Cancellation Algorithm for Free-moving Users
Frank Liu (Arizona State University), Anish Narsipur (Arizona State University), Andrew Kemeklis (Arizona State University), Lucy Song (Arizona State University), Robert LiKamWa (Arizona State University)

1:30 pm - 3:30 pm Session 2: Augmentation Acoustic
1. [Invited Paper] Augmenting Vibration-Based Customer-Product Interaction Recognition with Sparse Load Sensing
Yue Zhang (University of California Merced), Shiwei Fang (University of Massachusetts Amherst), Carlos Ruiz (Aifi Inc.), Zhizhang Hu (University of California Merced), Shubham Rohal (University of California Merced), Shijia Pan (University of California Merced)

2. [Invited Paper] Structure Assisted Spectrum Sensing for Low-power Acoustic Event Detection
Nakul Garg (University of Maryland, College Park, Harshvardhan Takawale (University of Maryland, College Park), Yang Bai (University of Maryland College Park), Irtaza Shahid (University of Maryland, College Park), Nirupam Roy (University of Maryland, College Park)


Xiaofan (Fred) Jiang

Columbia University

Xiaofan (Fred) Jiang

Columbia University
Shahriar Nirjon

University of North Carolina

Shahriar Nirjon

University of North Carolina
Nirupam Roy

UMD College Park

Nirupam Roy

UMD College Park