Advancing Trustworthy AI Through Research and Innovation

Welcome to my digital space! I’m Arjun Roy, a machine learning researcher with over seven years of experience at the intersection of AI innovation, robustness, and ethical systems design.

I’m currently based at the Research Institute CODE (Cyber Defence and Smart Data) at Universität der Bundeswehr München, where I work in the AIML lab on the EU Horizon projects MAMMOth and STELAR. In parallel, I’m pursuing a PhD in Machine Learning at Freie Universität Berlin, under the supervision of Prof. Dr. Eirini Ntoutsi.

Through this site, I aim to share my work and ongoing collaborations, and invite fellow researchers and practitioners to engage with ideas that contribute to transparent, scalable, and trustworthy AI.

Research Focus

My research lies at the intersection of machine learning theory, algorithm design, and practical system-level challenges. I am particularly interested in developing methods that are not only performant, but also fair, interpretable, and deployable under real-world constraints.

Areas of Work:

Fairness-aware Machine Learning & Multi-objective Optimization: Developing algorithms that balance accuracy with social and ethical constraints, ensuring responsible AI decision-making.
Robustness & Privacy in Training and Deployment: Designing models resilient to noise, adversaries, and distribution shifts, with an emphasis on data protection and compliance-aware deployment.
Multi-task, Federated, and Deep Reinforcement Learning: Exploring efficient training paradigms that scale across tasks, devices, and learning environments — with both centralized and decentralized architectures.
Multi-modal Learning & Natural Language Processing: Working with heterogeneous data sources (text, images, structured data) to build systems capable of contextual understanding and complex reasoning.

contact@arjunroy.info

Recent Activities

MTP-Arjun