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José Pinto

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Universidade Nova de Lisboa

Portugal

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HYBSimilar Deep hybrid modelling and optimisation of Chinese Hamster Ovary (CHO) cultivations for biosimilars production

Open Date: 2026-01-01

Close Date:

Articles (9)

Year:

2025

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2025

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2025

Year:

2025

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2024

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2023

Year:

2023

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2023

Year:

2023

Collaborators (4)

Jakob Kjøbsted Huusom

Technical University of Denmark

DENMARK

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Filomena Freitas

Principal Researcher

Universidade de Aveiro

PORTUGAL

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Rui Oliveira

Full Professor

Faculdade de Ciências da Universidade de Lisboa

PORTUGAL

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Xiaodong Liang

Associate Professor

Technical University of Denmark

DENMARK

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José Pinto

Research Interests

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Recent Grants

Articles (9)

Incorporating first-principles information into hybrid modeling structures

Bioprocess model-predictive control with physics-informed neural networks

A Physics-Informed Neural Network (PINN) framework for generic bioreactor modelling

HYBpy: A web-based framework for hybrid modeling of biological systems

Deep hybrid modeling of a HEK293 process: Combining long short‐term memory networks with first principles equations

Hybrid Deep Modeling of a GS115 (Mut+) <i>Pichia pastoris</i> Culture with State–Space Reduction

A General Hybrid Modeling Framework for Systems Biology Applications: Combining Mechanistic Knowledge with Deep Neural Networks under the SBML Standard

SBML2HYB: a Python interface for SBML compatible hybrid modeling

Hybrid deep modeling of a CHO-K1 fed-batch process: combining first-principles with deep neural networks

Collaborators (4)

Jakob Kjøbsted Huusom

Filomena Freitas

Rui Oliveira

Xiaodong Liang

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