Interview with Amar Halilovic: Explainable AI for robotics

In this interview collection, we’re assembly a few of the AAAI/SIGAI Doctoral Consortium individuals to seek out out extra about their analysis. The Doctoral Consortium gives a possibility for a bunch of PhD college students to debate and discover their analysis pursuits and profession targets in an interdisciplinary workshop along with a panel of established researchers. In this newest interview, we hear from Amar Halilovic, a PhD scholar at Ulm University.

Tell us a bit about your PhD – the place are you finding out, and what’s the matter of your analysis?

I’m at the moment a PhD scholar at Ulm University in Germany, the place I give attention to explainable AI for robotics. My analysis investigates how robots can generate explanations of their actions in a method that aligns with human preferences and expectations, significantly in navigation duties.

Could you give us an summary of the analysis you’ve carried out up to now throughout your PhD?

So far, I’ve developed a framework for environmental explanations of robotic actions and selections, particularly when issues go improper. I’ve explored black-box and generative approaches for the era of textual and visible explanations. Furthermore, I’ve been engaged on planning of various clarification attributes, reminiscent of timing, illustration, period, and so forth. Lately, I’ve been engaged on strategies for dynamically choosing the right clarification technique relying on the context and consumer preferences.

Is there a side of your analysis that has been significantly fascinating?

Yes, I discover it fascinating how individuals interpret robotic habits in a different way relying on the urgency or failure context. It’s been particularly rewarding to review how clarification expectations shift in numerous conditions and the way we will tailor clarification timing and content material accordingly.

What are your plans for constructing in your analysis up to now through the PhD – what features will you be investigating subsequent?

Next, I’ll be extending the framework to include real-time adaptation, enabling robots to be taught from consumer suggestions and modify their explanations on the fly. I’m additionally planning extra consumer research to validate the effectiveness of those explanations in real-world human-robot interplay settings.

Amar together with his poster on the AAAI/SIGAI Doctoral Consortium at AAAI 2025.

What made you wish to research AI, and, specifically, explainable robotic navigation?

I’ve at all times been within the intersection of people and machines. During my research, I noticed that making AI programs comprehensible isn’t only a technical problem—it’s key to belief and usefulness. Robot navigation struck me as a very compelling space as a result of selections are spatial and visible, making explanations each difficult and impactful.

What recommendation would you give to somebody considering of doing a PhD within the area?

Pick a subject that genuinely excites you—you’ll be residing with it for a number of years! Also, construct a assist community of mentors and friends. It’s simple to get misplaced within the technical work, however collaboration and suggestions are very important.

Could you inform us an fascinating (non-AI associated) truth about you?

I’ve lived and studied in 4 totally different nations.

About Amar

Amar is a PhD scholar on the Institute of Artificial Intelligence of Ulm University in Germany. His analysis focuses on Explainable Artificial Intelligence (XAI) in Human-Robot Interaction (HRI), significantly how robots can generate context-sensitive explanations for navigation selections. He combines symbolic planning and machine studying to construct explainable robotic programs that adapt to human preferences and totally different contexts. Before beginning his PhD, he studied Electrical Engineering on the University of Sarajevo in Sarajevo, Bosnia and Herzegovina, and Computer Science at Mälardalen University in Västerås, Sweden. Outside academia, Amar enjoys travelling, images, and exploring connections between expertise and society.