Diversity, Equity & Inclusion
Building Explainable, Inclusive, and Human-Centered AI.
Artificial Intelligence is not only a technological revolution but also a social one. As a researcher working at the intersection of Explainable AI (XAI), Multi-Agent Systems (MAS), and Digital Twin Systems, I believe that the future of intelligent systems must be transparent, inclusive, and human-aligned.
I view diversity in research not as a numerical goal but as a source of creativity and robustness. In multi-agent decision-making—just like in human collaboration—systems perform best when different perspectives, skills, and values interact fairly and transparently.
My Commitment
I am dedicated to fostering an academic and professional environment where all individuals— regardless of background, gender, ethnicity, ability, or experience—can learn, collaborate, and lead. Inclusion means not only ensuring representation but also designing AI that reflects plural human values and supports equitable decision-making in real-world systems.
In Technology & Society
Digital twin and AI-driven systems are increasingly shaping policy, environment, and everyday life. It is crucial that these systems be designed with fairness, inclusivity, and human understanding at their core. I advocate for the principle that “transparency in AI is not only about interpretability—it’s about empathy.”