Personen

About

As an AI Research Scientist at the University of Applied Sciences Kempten under the guidence of Tobias Windisch, my work centers on two primary domains: conducting cutting-edge AI research and developing innovative solutions to address industrial challenges by leveraging a range of statistical and AI methodologies in collaboration with Robert Bosch GmbH. 

My ongoing research explores complex causal relationships within high-dimensional manufacturing data, mostly images. Leveraging active causal learning techniques, I uncover latent factors influencing quality criteria indirectly measurable by optical systems. By integrating functional data analysis, I discern causal relationships from multimodal data for industrial process optimization. I am working on designing predictive models to forecast optimal process parameters based on desired quality outcomes, addressing the challenge of few-shot learning. 

In my master's thesis, conducted under the supervision of  Sebastian Trimpe, I developed optimized machine learning algorithms for unsupervised anomaly detection in image datasets for Robert Bosch GmbH. These algorithms feature dynamic adjustments based on dataset properties, enhancing adaptability and performance. By leveraging AutoML, I automated the pipeline, significantly reducing human intervention in identifying scrap parts.  

Research Interests 

• Computer Vision 

• Causal Inference 

• Statistical Analysis 

• Anomaly Detection 

Education 

• M.Sc. in Data Science, RWTH Aachen, Germany

  • Thesis: Anomaly Detection in Industrial Image Datasets with AutoML

• Masters in Business Administration, Bahria University, Pakistan 

• B.Sc. in Computer Science,  National University of Computer and Emerging Sciences, Pakistan 

Let’s Connect 

• LinkedIn 

• Github