DBIS

During my last 5 years of tenure at Fraunhofer FIT, I have been assigned to a number of responsibilities including: i) applied ML research to develop efficient ML methods and data+knowledge-driven analytical solutions to complex problems using SotA ML algorithms, ii) improving interpretability and adversarial robustness of the models before deploying them for production, and iii) writing grant proposals to acquire funding out of AI calls. I did my PhD in Explainable AI at RWTH Aachen University under the supervision of Prof. Dr. Stefan Decker with dissertation titled "Interpreting Black-Box Machine Learning Models with Decision Rules and Knowledge Graph Reasoning" with distinction (Summa Cum Laude). During my PhD, I published several scientific articles in major/top conferences and journals. Besides, I received the best paper (NLP) award at a top data science conference. As the recognition, I won the prestigious ICT Young Researcher Award 2020 for my significant contributions to ICT-related research. Overall, I've several years of experience in data science roles, covering predictive modelling, data analytics, deployment, and R&D skills and hands-on experience of using ML frameworks, MLOPs frameworks, and dealing with large-scale datasets, followed by building robust ML models with a view to scaling from the beginning. I apply ML, NLP and semantic web technologies on daily basis in order to develop data and knowledge-driven analytical solutions.