“Generations in Dialogue: Bridging Perspectives in AI.”
“Generations in Dialogue: Bridging Perspectives in AI” features thought-provoking discussions between AI experts, practitioners, and enthusiasts from different age groups and backgrounds. Each episode will delve into how generational experiences shape views on AI, exploring the challenges, opportunities, and ethical considerations that come with the advancement of this transformative technology.
AAAI is thrilled to announce the creation of a new podcast series, “Generations in Dialogue: Bridging Perspectives in AI.” Through this series, we aim to represent diverse perspectives across generations, fostering rich conversations about the ever changing landscape of AI. “Generations in Dialogue” aims to feature unique outlooks from AI experts, practitioners, enthusiasts of all backgrounds. Each episode will cover topics ranging from the history of AI, emerging topics, to exploring the future ethical implications of its newest technologies. We welcome you to join us in this exciting journey. Whether you are an AI professional, researcher, or student, we hope this platform will be invaluable in discovering unique perspectives of AI with a global audience, bridging existing generational gaps in the understanding of AI and expanding your network beyond your local communities. If you have a compelling story, unique insight, or an innovative idea, we want to hear from you! Please submit your application to participate by this form, and be a part of shaping the future of AI through intergenerational dialogue!
About the Host:
Ella Lan, a member of the AAAI Student Committee, is the host of “Generations in Dialogue: Bridging Perspectives in AI.” She is passionate about bringing together voices across career stages to explore the evolving landscape of artificial intelligence. Ella is a student at Stanford University tentatively studying Computer Science and Psychology, and she enjoys creating spaces where technical innovation intersects with ethical reflection, human values, and societal impact. Her interests span education, healthcare, and AI ethics, with a focus on building inclusive, interdisciplinary conversations that shape the future of responsible AI.
Episode 1: Multi-Agent Systems and Human-AI Interaction with Professor Manuela Veloso
Also available on YouTube
About Professor Manuela Veloso:
Manuela Veloso is a renowned computer scientist and a pioneer in artificial intelligence, with influential work in multi-agent systems, robotics, and human-AI collaboration. She is currently the Head of AI Research at JPMorgan Chase, where she leads efforts to integrate AI into financial services. Previously, she was the Herbert A. Simon University Professor at Carnegie Mellon University and Head of its Machine Learning Department. Her research spans autonomous robotics, planning, machine learning, and AI systems that collaborate seamlessly with humans. A Fellow of the AAAI, IEEE, and AAAS, Prof. Veloso has received numerous awards for her contributions to AI and remains a leading voice in advancing responsible and interactive AI systems.
Episode 2: Human-Centric AI and Collaborative AI Systems with Professor Andreea Bobu
Also available on YouTube
About Professor Andreea Bobu:
Andreea Bobu is an Assistant Professor at MIT and leads the Collaborative Learning and Autonomy Research (CLEAR) Lab, where she develops autonomous agents that learn to act for, with, and around people. Her research focuses on aligning robot behavior with human expectations by studying how agents can acquire the right supervision—whether from direct human input or priors—build shared task representations with users, and address misalignment from differing human models. Drawing from deep learning, inverse reinforcement learning, and Bayesian inference, her work is grounded in experiments with systems like assistive robot arms and large language models. Prof. Bobu earned her Ph.D. in EECS from UC Berkeley with Anca Dragan, was a Research Scientist at the AI Institute, and previously interned at NVIDIA’s Robotics Lab. She holds a B.S. in Computer Science from MIT.
Episode 3: Embodied AI, Robotics, Perception, and Action with Professor Roberto Martin-Martin
Also available on YouTube
About Professor Roberto Martin-Martin:
Roberto Martín-Martín is an Assistant Professor of Computer Science at the University of Texas at Austin, where his research integrates robotics, computer vision, and machine learning to build autonomous agents capable of perceiving, learning, and acting in the real world. His work spans low-level tasks like pick-and-place and navigation to complex activities such as cooking and mobile manipulation, often drawing inspiration from human cognition and integrating insights from psychology and cognitive science. He previously worked as an AI Researcher at Salesforce AI and as a Postdoctoral Scholar at the Stanford Vision and Learning Lab with Silvio Savarese and Fei-Fei Li, leading projects in visuomotor learning, mobile manipulation, and human-robot interaction. He earned his Ph.D. and M.S. from Technische Universität Berlin under Oliver Brock and a B.S. from Universidad Politécnica de Madrid. His work has been recognized with best paper awards at RSS and ICRA, and he serves as Chair of the IEEE/RAS Technical Committee on Mobile Manipulation.
Episode 4: Human-Robot Interactions and Social Robotics with Professor Marynel Vasquez
Also available on YouTube
About Professor Marynel Vasquez:
Marynel Vázquez is a computer scientist and roboticist whose research focuses on Human-Robot Interaction (HRI), particularly in multi-party settings. She studies social group dynamics—such as spatial behavior and social influence—in HRI, and develops perception and decision-making algorithms that enable autonomous, socially aware robot behavior. A central theme in her work is modeling interactions as graphs, allowing robots to reason about individuals, relationships, and groups simultaneously. Her interdisciplinary approach combines computer science, behavioral science, and design, and she enjoys building new robotic systems and research infrastructure to bring theoretical ideas into real-world practice.