Curriculum
Vitae

Bram De Jaegher

Bioscience engineer


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Keywords: mathematical modelling, process control, computational fluid dynamics, machine learning, optimisation, open-source, bioprocess technology, problem solving, programming, windsurfing, electronics tinkering

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about

9000 Gent

Belgium

bram.de.jaegher@gmail.com

LinkedIn

Github

Driving license: B

languages

Dutch: native language

English: C2 (CEFR)

French: B1 (CEFR)

additional skills

Computational
fluid dynamics

Mathematical modelling

Machine learning

Control theory

LaTeX

programming

Working knowledge

Julia

Linux/Bash

OpenFOAM

MATLAB/Simulink

Python 2/3

Basic knowledge

HTML/CSS

C++

Exposure to

R

Javascript

C#

about

9000 Gent

Belgium

bram.de.jaegher@gmail.com

LinkedIn

Github

Driving license: B

languages

Dutch: native language

English: C2 (CEFR)

French: B1 (CEFR)

additional skills

Mathematical modelling

Computational fluid
  dynamics  

Machine learning

Control theory

LaTeX

programming

Working knowledge

Julia

Python 2/3

OpenFOAM (CFD)

MATLAB/Simulink

Basic knowledge

HTML/CSS

C++

Exposure to

Javascript

C#

R

education

2014-2016

M.Sc. summa cum laude

Bioscience engineering

Chemistry and bioprocess technology

Ghent University

Chemistry and biochemistry

  • Analytical inorganic chemistry: instrumental techniques
  • Bio-organic chemistry
  • Chemical modification of renewable resources
  • Chemical structure determination
  • Colloid and surface chemistry
  • Industrial biotechnology
  • Industrial fermentation processes and downstream processing
  • Instrumental organic analysis

Mathematical modelling

  • Modelling and simulation 2: partial differential equations in practice
  • Predictive models

Process control and technology

  • Bio-process control
  • Clean technology
  • Computer control of industrial processes (Faculty of engineering and architecture)
  • Process control
  • Process engineering II
  • Sustainable energy and rational use of energy

Other

  • Discussion techniques and applied group dynamics
  • Introduction to management
  • Quality management and risk analysis
  • Thermochemical conversion of biomass

2011-2014

B.Sc. cum laude

Bioscience engineering

Chemistry and food technology

Ghent University

Chemistry, biochemistry and physics

  • Biocatalysis and enzyme technology
  • Biochemistry and molecular biology
  • Chemistry 1: inorganic - structure
  • Chemistry 2: inorganic - reactivity
  • Chemistry 3: organic - structure
  • Chemistry 4: organic - reactivity
  • Chemical analytical methods
  • Food chemistry
  • Polymers
  • Physics 1: Mechanics, vibrations and waves
  • Physics 2: electricity and magnetism
  • Physics 3: thermodynamics
  • Physics 4: physical transport phenomena

Mathematics

  • Mathematics 1: algebra and analytical geometry
  • Mathematics 2: differential and integral calculus
  • Mathematics 3: differential equations
  • Mathematics 4: probabilistic models
  • Statistical data processing

Modelling, process control and technology

  • Modelling and simulation of biosystems
  • Process engineering
  • Process technology
  • Reaction kinetics and reactor design

Life sciences and others

  • Biotechnological processes for environmental sanitation
  • Botany 1: morphology, anatomy and diversity
  • Botany 2: physiology
  • Earth sciences
  • Ecology
  • Economics
  • Food Microbiology and Food Preservation
  • Microbiology
  • Scientific computing
  • Sustainable systems
  • Zoology 1: invertebrates
  • Zoology 2: vertebrates

2005-2011

GCSE in Math and Sciences

4.2/5 GPA

Royal Atheneum Knokke-Heist

experience

01/2017 - Now

PhD candidate

The development of fouling resistant electrodialysis for the treatment of bio-based process streams

BIOMATH/VITO/PaInT

Ghent University

Keywords: electrochemical process modelling, computational fluid dynamics, Machine learning, OpenFOAM, Julia, Python, C++

Description

The main goal of this research project is developing a mathematical model for a electrodialysis installation and optimise its performance. Different modelling paradigms are used an the novelty of this research is the combination of machine learning models and physics-based models. I'm currently writing the PhD dissertation so in the mean time please enjoy these presentations on the topic.


Scientific consulting

Two-phase computational fluid dynamics of a water tower to analyse the residence time of drinking water (PIDPA).

Large-eddy simulation to compute shear stresses in a tubular membrane filter with a ribbed interior (Pentair).

09-12/2016

Research assistant

Mathematical modelling of filtercake formation
and fungal growth

BIOMATH/KERMIT

Ghent University

Keywords: model validation and calibration, actuators, hydraulics, electronics, LabVIEW, data-acquisition

Project description

During this research project, a microfiltration installation was developed for the calibration and validation of a spatio-temporal model of filtercake formation (MSc thesis). A data-acquisition and process control system was developed and the respective actuators and sensors were installed. Computational fluid dynamics (CFD) simulations of the system were validated by means of several tracer tests and the agent-based model of the dispersed particles can be validated through profilometric measurements of the formed filtercake.

Video: an example of the performed tracer tests, validating the laminar flow within the system.


08-09/2014

Research internship

Computer vision techniques for polymer
recognition on atomic-force microscopy images

University of São Paulo

Keywords: Texture analysis, machine learning, Gabor filters, Fourier analysis, visual descriptors, atomic-force microscopy

Project description

Applied computer vision research, an assessment of the applicability of several filters and visual descriptors for the classification of atomic-force microscopy images of polymers.

A Poly(p-phenylene vinylene) solution was spincoated on glass plates. These plates were exposed to different surface treatments, e.g. UV radiation, high temperatures, solvent treatments, etc. Atomic-force microscopy images of the polymer surfaces were obtained and and a dataset of visual descriptors was constructed by means of local binary patterns, gray-level co-occurence matrices, Gabor filters and Fourier analysis. Supervised learning algorithms were used to construct a mathematical model able to predict the surface treatment based on these visual descriptors.

Left to right: atomic-force microscopy images of the polymers exposed to a strong base, UV radiation and untreated.


scriptions

2016

Master thesis

Spatio-temporal modelling of filtercake formation in filtration processes

Ghent University
2014

Bachelor thesis

Innovative applications of artificial intelligence in the food industry

Ghent University

voluntary work

2009-2014

Leader youth movement

102e FOS De Albatros

Knokke-Heist

projects

2016

Open Webslides

Open-source platform for interactive presentation slides

UGent innoversity challenge winning project

Ghent University

Description

Open Webslides are a platform to create course material that promotes co-creation and makes full use of modern web technologies to promote an (inter)active and accessible learning environment. At the core of the Open Webslides project is the new format of course slides. These webslides differ from current slide solutions in a variety of ways.

Webslides, as the name suggests, are slides made with web technology, namely HTML, CSS and Javascript. Essentially, this means that every slide in itself is a website and as such, is able to do everything a website can. You can seamlessly embed YouTube videos, flipped classroom tools, dynamic graphics, etc. The possibilities are virtually endless.

The fact that every slide is a website in itself, allows you to link to specific slides from other online platforms. This allows you to make your course material more accessible and visibible.


2016

Dewpal: biocatalysed atmospheric condensation

iGEM: International Genetically Engineered Machine Competition

MIT, Boston

Keywords: 3D CAD, microprocessors, Python, biotechnology

Description

The aim of our project is to design an optimized 3D shape for condensing water, using a fusion protein of INP and streptavidin to increase our water collection.

The shape is designed to be modular (so it can be scaled up easily) and stackable (so many units can be transported and stored easily and cheaply), and is 3D-printed in a PLA-filament containing biotin. To increase the condensation capabilities of our water collector, we attach a fusion protein of INP (Ice Nucleation Protein) with streptavidin to the biotin. INP is a protein of certain bacteria that improves the nucleation of ice at higher temperatures than normal. As condensation also involves nucleation, INP can be used to increase condensation, and hence water collection.


And various others...