M.I.L.E. Workshop | RO-MAN 2026

About the Workshop

Human–robot interaction has traditionally focused on settings where humans and robots share a common goal and operate under the assumption of cooperation. While this paradigm has enabled major progress in assistive robotics, collaborative manipulation, and shared autonomy, it often abstracts away from the complexity of real-world interaction.

In natural environments, alignment between humans and robots is frequently incomplete, uncertain, or dynamically changing. Humans may not fully trust, understand, or adapt to robotic behavior, and robots may misinterpret human intent, fail to predict subtle behavioral cues, or operate under conflicting objectives. These forms of partial alignment introduce rich but underexplored challenges for perception, planning, and learning.

The M.I.L.E. workshop (Misaligned Interaction and Learning Engagement Strategies) aims to bring together researchers working at the intersection of robotics, machine learning, cognitive modeling, and human factors to study these challenges in a unified way. We are particularly interested in how misalignment emerges, how it can be detected and modeled online, and how adaptive systems can respond to it in a principled manner.

Topics of interest include, but are not limited to: intention inference under uncertainty, human-aware planning in non-cooperative settings, learning from ambiguous or conflicting feedback, modeling human engagement and disengagement, multi-agent miscoordination, and safety in partially aligned systems.

Beyond technical advances, M.I.L.E. also emphasizes conceptual and interdisciplinary perspectives on interaction, including cognitive science, social psychology, and theories of cooperation and conflict in human–robot teams.

By fostering discussion across these communities, the workshop aims to establish a shared foundation for studying misalignment not as an edge case, but as a fundamental property of real-world human–robot interaction.

Invited Speakers

The workshop features internationally recognized researchers in HRI, adaptive autonomy, intention modeling, and human-aware decision-making.

Hiroshi Ishiguro

Hiroshi Ishiguro is a preeminent robotics researcher and Director of the Intelligent Robotics Laboratory at Osaka University, Japan. His work focuses on android science, human–robot interaction, and the broader implications of artificial intelligence. He is widely known for pioneering lifelike androids, including Geminoid robots such as a robotic replica of himself, which have reshaped how researchers think about the boundaries between humans and machines. Through his research and public engagement, he continues to explore questions of human identity and the future relationship between humans and robots.

Yukie Nagai

Yukie Nagai is a Project Professor at the University of Tokyo’s International Research Center for Neurointelligence, where she leads the Cognitive Developmental Robotics Lab. Her research focuses on cognitive developmental robotics and computational neuroscience, with an emphasis on understanding the mechanisms underlying social cognitive development and supporting developmental disorders. She has contributed to major JST CREST projects and has received international recognition for her work in robotics and AI.

Friederike Eyssel

Friederike Eyssel is Professor of Psychology and head of the “Applied Social Psychology and Gender Research” group at the Center for Cognitive Interaction Technology (CITEC), Bielefeld University. Her research focuses on social robotics, trust, acceptance of emerging technologies, and attitude change, combining basic and applied social psychological perspectives. She has contributed to several EU- and nationally funded projects and is co-author of key textbooks in human–robot interaction and social robotics. She also serves in editorial roles for leading robotics and HRI journals and has received multiple awards for her research, teaching, and contributions to gender equality in science.

Tatsuya Nomura

Tatsuya Nomura is an Associate Professor in the Department of Media Informatics at Ryukoku University, Japan, and a researcher in the Advanced Technology and Research Intelligent Robotics and Communication Laboratories. His research focuses on human–robot interaction and intelligent robotics, with an emphasis on psychological and cognitive aspects of human responses to robots. Prior to his academic career, he worked in industrial research at Sharp Corporation. He is a member of several academic societies, including IEEE, the Japanese Psychological Association, and the Japanese Cognitive Science Society.

Heramb Nemlekar

Heramb Nemlekar is an Assistant Professor in the Department of Mechanical Engineering at California State University, Northridge (CSUN), where he leads the Collaborative & Autonomous Robotics Research (CARE) Lab. His research focuses on human–robot interaction and robot learning from human feedback, with applications in assistive robotics, healthcare, and manufacturing. He develops learning-based methods and interaction interfaces that enable intuitive collaboration between humans and robotic systems.

Sarah Gillet

Sarah Gillet develops autonomous social robots that aim to meaningfully enhance and enrich human–human interaction. Her research combines real-world user studies with computational and learning-based approaches to design systems that are not only technically robust, but also deeply grounded in human social needs and experiences.

Hashini Senaratne

Hashini Senaratne is a Research Scientist in the Robotics and Autonomous Systems program at CSIRO, Australia. Her work focuses on human-centered robotics and AI, with an emphasis on natural, safe, and explainable human–robot interaction. She develops multimodal and adaptive systems that support effective collaboration in human–robot teams, including interfaces that help maintain human situational awareness during shared tasks. She received her PhD in Human-Centered Computing and Artificial Intelligence from Monash University, where her research explored multimodal detection of anxiety patterns to inform intelligent assistive technologies.

Tentative Program

Full-day schedule designed to maximize interaction, discussion, and feedback.

09:00 – 09:30 · Opening Session
- Welcome and introduction
- Overview of misalignment and adaptation challenges
- Framing key scientific questions
09:30 – 11:00 · Block 1: Invited Talks & Papers
- Invited speakers present state-of-the-art approaches
- Oral presentations of selected accepted papers
11:00 – 12:00 · Poster & Spotlight Session (Part 1)
- 2–3 minute spotlight presentations per paper
- Poster session with interactive discussion
12:00 – 12:30 · Coffee Break
12:30 – 14:00 · Block 2: Invited Talks & Papers
- Continuation of invited talks and presentations
- Oral presentations of selected papers
14:00 – 15:30 · Lunch Break
15:30 – 16:30 · Poster & Spotlight Session (Part 2)
- Second round of spotlight presentations
- Extended poster interaction session
16:30 – 17:00 · Coffee Break
17:00 – 18:00 · Plenary Discussion
- Open research challenges
- Benchmarks and evaluation metrics
- Future collaboration opportunities
18:00 – 18:15 · Closing Session
- Final remarks and conclusions