Ingmar Nopens

About Ingmar Nopens

Ingmar Nopens, With an exceptional h-index of 57 and a recent h-index of 40 (since 2020), a distinguished researcher at Universiteit Gent, specializes in the field of Model-based process optimisation.

His recent articles reflect a diverse array of research interests and contributions to the field:

Prediction of Activated Sludge Settling Characteristics from Microscopy Images with Deep Convolutional Neural Networks and Transfer Learning

Analysis of the effect of formulation properties and process parameters on granule formation in twin-screw wet granulation

A framework for the in silico assessment of the robustness of an MPC in a CDC line in function of process variability

Cracking the code: Spatial heterogeneity as the missing piece for modeling granular fluidized bed drying

A full‐scale operational digital twin for a water resource recovery facility—A case study of Eindhoven Water Resource Recovery Facility

An innovative model-based protocol for minimisation of greenhouse gas (GHG) emissions in WRRFs

A Colourful Way to Unravel the Important Fluidization-Related Granule Size Effect on Semi-Continuous Drying

High biomass yields of Chlorella protinosa with efficient nitrogen removal from secondary effluent in a membrane photobioreactor

Ingmar Nopens Information

University

Position

BIOMATH -

Citations(all)

12353

Citations(since 2020)

6494

Cited By

8726

hIndex(all)

57

hIndex(since 2020)

40

i10Index(all)

218

i10Index(since 2020)

173

Email

University Profile Page

Google Scholar

Ingmar Nopens Skills & Research Interests

Model-based process optimisation

Top articles of Ingmar Nopens

Prediction of Activated Sludge Settling Characteristics from Microscopy Images with Deep Convolutional Neural Networks and Transfer Learning

arXiv preprint arXiv:2402.09367

2024/2/14

Sina Borzooei
Sina Borzooei

H-Index: 6

Ingmar Nopens
Ingmar Nopens

H-Index: 40

Analysis of the effect of formulation properties and process parameters on granule formation in twin-screw wet granulation

International Journal of Pharmaceutics

2024/1/25

Michael Ghijs
Michael Ghijs

H-Index: 4

Ingmar Nopens
Ingmar Nopens

H-Index: 40

A framework for the in silico assessment of the robustness of an MPC in a CDC line in function of process variability

International Journal of Pharmaceutics

2024/4/24

Daan Van Hauwermeiren
Daan Van Hauwermeiren

H-Index: 6

Ingmar Nopens
Ingmar Nopens

H-Index: 40

Cracking the code: Spatial heterogeneity as the missing piece for modeling granular fluidized bed drying

International Journal of Pharmaceutics

2024/4/21

Michael Ghijs
Michael Ghijs

H-Index: 4

Ingmar Nopens
Ingmar Nopens

H-Index: 40

A full‐scale operational digital twin for a water resource recovery facility—A case study of Eindhoven Water Resource Recovery Facility

Water Environment Research

2024/3

Sina Borzooei
Sina Borzooei

H-Index: 6

Ingmar Nopens
Ingmar Nopens

H-Index: 40

An innovative model-based protocol for minimisation of greenhouse gas (GHG) emissions in WRRFs

Chemical Engineering Journal

2024/3/1

A Colourful Way to Unravel the Important Fluidization-Related Granule Size Effect on Semi-Continuous Drying

AAPS PharmSciTech

2023/12/29

Michael Ghijs
Michael Ghijs

H-Index: 4

Ingmar Nopens
Ingmar Nopens

H-Index: 40

High biomass yields of Chlorella protinosa with efficient nitrogen removal from secondary effluent in a membrane photobioreactor

Journal of Environmental Sciences

2023/11/22

Capturing unmodelled phenomena: A hybrid approach for the prediction of the transport through ceramic membranes in organic solvent nanofiltration

Journal of Membrane Science

2023/11/15

Ingmar Nopens
Ingmar Nopens

H-Index: 40

Validation of model-based design of experiments for continuous wet granulation and drying

International Journal of Pharmaceutics

2023/11/5

Mechanistic modeling of semicontinuous fluidized bed drying of pharmaceutical granules by incorporating single particle and bulk drying kinetics

International Journal of Pharmaceutics

2023/11/5

Exploring the effect of raw material properties on continuous twin-screw wet granulation manufacturability

International Journal of Pharmaceutics

2023/10/15

A hybrid modelling approach for reverse osmosis processes including fouling

Desalination

2023/10/15

Quantifying the hydrodynamic stress for bioprocesses

Biotechnology Progress

2023/9

Evaluation of the influence of material properties and process parameters on granule porosity in twin-screw wet granulation

International Journal of Pharmaceutics

2023/6/25

Ingmar Nopens
Ingmar Nopens

H-Index: 40

Partial least squares regression to calculate population balance model parameters from material properties in continuous twin-screw wet granulation

International Journal of Pharmaceutics

2023/6/10

Mobility and the spatial spread of sars-cov-2 in Belgium

Mathematical Biosciences

2023/6/1

Linking material properties to 1D-PBM parameters towards a generic model for twin-screw wet granulation

Chemical Engineering Research and Design

2023/5/1

Analysis of the influence of process and formulation properties on the drying behavior of pharmaceutical granules in a semi-continuous fluid bed drying system

Powders

2023/4/4

Towards a multiscale rheological model of fresh cement paste: A population balance approach

Chemical Engineering Research and Design

2023/4/1

Ingmar Nopens
Ingmar Nopens

H-Index: 40

See List of Professors in Ingmar Nopens University(Universiteit Gent)