August 1-2, 2022
Audio Across Domains
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2022 Unconference

A cross-disciplinary meeting of audio data scientists from all corners.

This cross-disciplinary in-person meeting will give professionals from all audio-related fields the opportunity to connect, share ideas, and develop collaborations. This first AudioXD meeting is a collaborative effort of the Kitzes Lab at the University of Pittsburgh, the Academic Data Science Alliance (ADSA), and the Berkeley Institute for Data Science (BIDS), with financial support generously provided by ADSA and the Gordon and Betty Moore Foundation. The event will be hosted in Pittsburgh, PA at the University of Pittsburgh and will be completely in person. Please fill out the short participation form if you are interested in attending.

Lightning talks

Participants will give lightening talks highlighting their expertise and challenges from their disciplines.

Develop partnerships

We'll focus on getting to know each other and developing connections across many fields.

Launch projects

We will build in time for participants to put their brains together and kickstart new cross-disciplinary ideas.

The stated goals of our cross-domain meeting are to:
  1. Create new interpersonal connections between attendees, and
  2. Identify common research themes, needs, and pain points that could form the basis for new research collaborations
To achieve these goals, our time will be split between rapid-fire knowledge sharing, unstructured networking, and small-group ideation sessions.

study sound? we want you to join us

The target audience for our AudioXD meeting is data scientists, including those in methods disciplines (e.g., statistics, computer science, electrical engineering) and application domains (e.g., music, biology, environmental science, engineering, linguistics, psychology, history, sociology, journalism, law) who conduct research using audio data.

Session organizers

Justin Kitzes
Ecology & Conservation with Bioacoustics
University of Pittsburgh
Brian McFee
MIR & Machine Learning with Music
New York University
Sam Lapp
Bioacoustics with Machine Learning
University of Pittsburgh


Here's a preliminary outline of the three days.

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