I am an AI systems scientist at the Palo Alto Research Center. I study human-aware AI - how to design intelligent interactive systems that model, learn, and reason about their human collaborators. I am especially interested in methods for effective and robust human-agent collaborative behavior in real-world settings. My research advances methods for complex sequential decision making and leverages insights about human behavior from cognitive science, linguistics, and economics.
I have designed collaborative agents for a variety of application domains general purpose robots, preventive healthcare, sustainable transportation, and augmented reality learning. I am particularly motivated to build intelligent collaborative technology social good and public welfare. My work is interdisciplinary and has been published at venues for research on artificial intelligence (JAIR, AAAI, IAAI), human cognition (ICCM, ACS, BICA), human-machine interaction (ACM TiiS, IEEE RO-MAN) as well as in applications (JMIR, EMBC, ACM/AAAI AIES). My research has been supported by the US government (DARPA, AFOSR, ARPA-E, NSF) and commercial entities (Xerox Corporation, Kaiser Permanente). Currently, I am the principal investigator for PARC’s efforts on DARPA SAIL-ON and DARPA GAILA.
Humans of AI summarizes my ongoing research and outlines my research agenda on incorporating explicit models of humans in design of collaborative AI systems. My research statement explains it in more detail
I am a graduate of the Soar lab led by John E. Laird that traces its legacy to foundational research on human cognition by Allen Newell and human decision making by Herbert Simon. My graduate experience set me on this wonderful journey in studying the computational underpinnings of human intelligence and building intelligent systems that support people in their goals. PARC’s legacy in leveraging cognitive psychology to design more effective technology has only made this journey more adventurous.
|Mar 10, 2022||Giving an invited talk on cognitive science and collaborative robots at Human-Interactive Robot Learning at HRI 2022.|
|Mar 3, 2022||ITL research by Aaron Mininger and John Laird in the Soar group won the best demonstration award at AAAI 2022.|
|Jun 10, 2021||Research on natural human-robot teaching led by Preeti Ramaraj accepted for oral presentation at IEEE RO-MAN 2021|
|May 14, 2021||Giving a talk on cognitive science and robotics at Talking Robotics.|
|May 6, 2021||Looking forward to talking to graduate students at UM ECSEL+.|
- IEEE RO-MANUnpacking Human Teachers’ Intentions For Natural Interactive Task Learning30th IEEE International Conference on Robot and Human Interactive Communication 2021
- ACM TiiSExploring the Role of Common Model of Cognition in Designing Adaptive Coaching Interactions for Health Behavior ChangeACM Transactions on Interactive Intelligent Systems 2021
- ACM TiiSDesigning an AI Health Coach and Studying its Utility in Promoting Regular Aerobic ExerciseACM Transactions on Interactive Intelligent Systems (TiiS) 2020
- JAIRAcceptable planning: Influencing Individual Behavior to Reduce Transportation Energy Expenditure of a CityJournal of Artificial Intelligence Research 2019
- ACSCharacterizing an Analogical Concept Memory for Architectures Implementing the Common Model of CognitionIn Proceedings of the Annual Conference on Advances in Cognitive Systems 2020
- AAAILearning Fast and Slow: Levels of Learning in General Autonomous Intelligent Agents.In Proeedings of the AAAI Conference on Artificial Intelligence 2018