Dr Anna Xambo Sedo

Anna Xambo Sedo
BA, MA, MSc, PhD, AFHEA

Senior Lecturer in Sound and Music Computing

School of Electronic Engineering and Computer Science
Queen Mary University of London
eecs.qmul.ac.uk/~axambo
Centre for Multimodal AI
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Research

HCI, sound and music computing, NIME, live coding, web audio, diversity in music AI

Interests

Topics: Interactive sound and music systems, Human-Computer Interaction, Diversity in computing

Dr Anna Xambó Sedó (she/her) is a researcher and an experimental electronic music producer. Her research and practice concern human-computer interaction (HCI), sound and music computing (SMC), new interfaces for musical expression (NIME), live coding, and web audio looking at designing and evaluating networked algorithmic spaces that support collaboration, participation, non-hierarchical structures and do-it-yourself (DIY) practices for SMC. She is currently the Principal Investigator (PI) of the UK Research and Innovation's (UKRI) Arts and Humanities Research Council funded project “Sensing the Forest: Let the Forest Speak using the Internet of Things, Acoustic Ecology and Creative AI" (2023-2025). She has also worked as the PI for the UKRI Engineering and Physical Sciences Research Council's Human Data Interaction Network Plus funded project “MIRLCAuto: A Virtual Agent for Music Information Retrieval in Live Coding” (2020-2021).

She is open to discussing other projects related to creative AI, with particular interest in generative audio of non- mainstream music genres, algorithmic sound-based music systems, and citizen science/DIY projects that aim to improve societal aspects of unprivileged communities through the use of sound-based music and acoustic ecology systems.

Since 2016, she has co-founded and taken leading roles in several organisations for promoting and improving the representation of women in music technology: Women in Music Tech (2016-17, Georgia Tech); WoNoMute (2018-2019, NTNU/UiO); WiNIME (2019-2022, NIME); and EECS Women in Higher Education Network (2024-, QMUL).