Kirsten Van Huffel

Highly motivated to improve my skills in data analysis and machine learning within a technical role, ideally in a biotech setting (the perfect combo aligning my main interests). Currently I'm working as a project manager AI, where I have gained valuable experience in managing projects with a commercial focus. However, my genuine passion lies in hands-on implementing data analysis and AI solutions, and therefore I am seeking a technical role to fully delve into my passion.

(November 2022 - now) Project Manager AI (Trendskout): 

• Managing AI projects for over 25 customers, focused on sales AI, image recognition and automatic text processing 
• Programming: support data scientists with technical execution of projects by working out proof-of-concepts in Python and verifying final results 
• Give demonstrations to customers during sales meetings: set up AI models on demo data and explain AI strategies 
• Gained experience with forecasting, recommendation, classification approaches, clustering, regression, large language models (GPT), object detection, image classification 
• Present results to customers and take the lead in meetings

• Research unit Knowledge-based Systems (KERMIT), Department of Data Analysis and Mathematical Modelling, Faculty of Bioscience Engineering 
• Special Research Fund UGent (BOF) 
• Research: energy-based machine learning to optimize biosystems such as molecules, proteins and cells and explore their combinatorial design space 
• Gained experience with deep learning, mathematical optimization and experimental design (Python, Julia, Pytorch, Tensorflow, sklearn...) 
• Writing skills: two A1 publications in high-quality journals as a first author 
• Teaching: assisted computer practicals for the course Probabilistic Models for 2nd year students of bioengineering, guided bachelor and master thesis projects in AI and optimization

2020: Credict contract at the Faculty of Engineering and Architecture (Ghent University)

• Courses in Machine learning and Mathematical optimization 

• Degree: summa cum laude 
• Master thesis: Machine learning for more efficient metabolic engineering

• Degree: summa cum laude