FAU MoD Lecture: A data-driven approach to closed-loop control of wound state progression to drive healing outcomes

Date: Mon. May 4, 2026
Event: FAU MoD Lecture
Organized by: FAU MoD, the Research Center for Mathematics of Data at Friedrich-Alexander-Universität Erlangen-Nürnberg (Germany)

FAU MoD Lecture: A data-driven approach to closed-loop control of wound state progression to drive healing outcomes
Speaker: Prof. Dr. Marcella M. Gomez
Affiliation: University of California, Santa Cruz (USA)

Abstract. The advancement of technology in bioelectronic sensors and actuators provides a platform for automating custom treatment strategies through feedback control. If we consider the response of an individual to a treatment regimen as a dynamical system, we can deploy adaptive strategies with real-time learning to optimize prescribed treatments. Here, we discuss work in wound healing. We argue that timing of treatments is as critical to consider as the choice of drug or therapy. Due to system size and complexity, data-driven methods need to be explored to develop multi-dimensional quantifiable indicators tracking systemic changes. Open challenges we address include developing data-driven models suitable for relatively small datasets that are temporally sparse and noisy. Thus, there is a need to develop methods that work with small training datasets and that can be updated in real-time with incoming data. This allows the model to be fine-tuned to the individual of study. In this work I discuss our approach to enhancing bioelectronic devices with deep learning to help facilitate real-time sensing and actuation for automated decisions in treatment to accelerate wound closure.

OUR SPEAKER

Marcella M. Gomez is an associate professor at UC Santa Cruz in the department of Applied Mathematics and Associate Dean for Diversity, Equity, and Inclusion for Baskin Engineering. She received her PhD from Caltech in 2015 and a B.S. from UC Berkeley in 2009; both degrees in Mechanical Engineering. Her research interests are in the broad field of bio-control leveraging methods in machine learning and control theory. Applications range from controlling single-cell response to driving complex systems such as wound healing.

AUDIENCE

This is a hybrid event (On-site/online) open to: Public, Students, Postdocs, Professors, Faculty, Alumni and the scientific community all around the world.

WHEN

Mon. May 4, 2026 at 11:30H (Berlin time)

WHERE

On-site / Online

[On-site] Friedrich-Alexander-Universität Erlangen-Nürnberg.

[Online] https://www.fau.tv/clip/id/59621

 

This event @LinkedIn

 
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