QLS Seminar - Wednesday, 15 July at 14h00 - Physics-Informed Machine Learning for Biological Systems

[Quantitative Life Sciences]

Dear All,

Today, Wed. 15 July at 14h00, Prof.  Mohammad Kohandel (U. of Waterloo, 
Canada) will give a seminar titled:

*"Physics-Informed Machine Learning for Biological Systems"*

Physics-informed machine learning (PIML) is emerging as a powerful 
framework for modeling complex biological systems by integrating 
mechanistic knowledge with experimental data. Unlike purely data-driven 
approaches, PIML incorporates differential equations describing 
biological processes while enabling unknown mechanisms to be learned 
directly from sparse, noisy, and partially observed measurements. This 
capability is particularly valuable in biology, where mechanistic models 
are often incomplete and experimental data are limited. In this talk, I 
will present recent advances from our group in developing interpretable 
physics-informed learning methods for biomedical applications. I will 
introduce Universal Physics-Informed Neural Networks (UPINNs), which 
extend conventional PINNs by simultaneously estimating unknown 
parameters and discovering previously unknown biological functions from 
data. I will demonstrate applications in quantitative systems 
pharmacology, drug development, and cancer biology, and discuss how 
these approaches can accelerate mechanistic discovery, improve 
predictive modeling, and support the development of next-generation 
biological digital twins.

Indico: https://indico.ictp.it/event/11403/

The seminar will take place in the *L. Stasi seminar room, 1st floor, 
Leonardo building* (Strada Costiera, 11).

You are all most welcome to attend!

Best regards,

Erica

Erica Sarnataro
Group Secretary
Quantitative Life Sciences
The Abdus Salam International Centre for Theoretical Physics (ICTP)
Trieste,  Italy
Tel. +39-040-22404623 (NEW PHONE NUMBER)
www.ictp.it/research/qls.aspx
e-mail:qls at ictp.it