Yantian was born in Nanjing, China. While Yantian started learning piano at three years old (and eventually obtained his 10-Level Piano Certificate), Yantian is committed to Robotics (which is one of Yantian’s childhood dreams). Yantian’s robotics journey truly set out when he was an undergrad, worked with Prof. Xudong Ma and Prof. Kun Qian at the Institute of Intelligent Robotics and Intelligent Control, Southeast University. After that, Yantian went to Arizona State University and had a delighted Ph.D. life with his advisor Prof. Subbarao Kambhampati (Rao) (as clearly seen from the title of Yantian’s Ph.D. Thesis). Recently, Yantian becomes a Postdoctoral Associate, working with Prof. Yiannis Aloimonos and Dr. Cornelia Fermüller in the Perception & Robotics Group, at the University of Maryland, College Park.

Research Interest:

Yantian is interested in Cognitive Robot Learning – how different levels of cognitive functions like perception, acting, planning, and metacognition, can be tightly coupled to achieve human-level intelligence for robots.

Teaching:

2023 Spring: ENPM808Z Cognitive Robotics

Please feel free to contact Yantian via ytzha at umd dot edu or LinkedIn.

News!

04/2022: I am a recipient of the Maryland Robotics Center Postdoctoral Fellowship at the Institute for Systems Research (ISR), University of Maryland, 2022-2023.

06/30/2021: Our paper Contrastively Learning Visual Attention as Affordance Cues from Demonstrations for Robotic Grasping is accecped by IROS 2021. Thanks to my collaborators!

04/30/2021: I am awarded the CIDSE Doctoral Fellowship by ASU.

03/2020 - 08/2020: Worked as a robotics research intern at ABB, Raleigh advised by Dr. Jianjun Wang.

Publications

NatSGD: A Dataset with Speech, Gestures, and Demonstrations for Robot Learning in Natural Human-Robot Interaction
Snehesh Shrestha, Yantian Zha, Ge Gao, Cornelia Fermuller, and Yiannis Aloimonos
AAAI-23 Workshop on User-Centric Artificial Intelligence for Assistance in At-Home Tasks.
Media: [Demo Video]

Learning from Ambiguous Demonstrations with Self-Explanation Guided Reinforcement Learning
Yantian Zha, Lin Guan, Subbarao Kambhampati
AAAI-22 Workshop on Reinforcement Learning in Games 2022.
Media: [Demo Video] [Poster]

Symbols as a Lingua Franca for Bridging Human-AI Chasm for Explainable and Advisable AI Systems
Subbarao Kambhampati, Sarath Sreedharan, Mudit Verma, Yantian Zha, Lin Guan
AAAI Blue Sky Paper (Senior Member Presentation Track) 2022.

Contrastively Learning Visual Attention as Affordance Cues from Demonstrations for Robotic Grasping
Yantian Zha, Siddhant Bhambri, and Lin Guan
The IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) 2021.
Media: [Project] [IROS_Talk] [Slides]

Plan-Recognition-Driven Attention Modeling for Visual Recognition
Yantian Zha, Yikang Li, Tianshu Yu, Subbarao Kambhampati and Baoxin Li
AAAI 2019 Workshop on Plan, Activity, and Intent Recognition (PAIR).

Recognizing plans by learning embeddings from observed action distributions
Yantian Zha, Yikang Li, Sriram Gopalakrishnan, Baoxin Li, and Subbarao Kambhampati
In Proceedings of International Conference on Autonomous Agents and Multiagent Systems (AAMAS) 2018.
Media: [Full Paper] [Code] [Slides] [Poster]

Discovering Underlying Plans Based on Shallow Models
Hankz Hankui Zhuo, Yantian Zha, Subbarao Kambhampati, and Xin Tian
In Proceedings of ACM Transactions on Intelligent Systems and Technology (ACM-TIST) 2019.
Media: [Code]

Explicability as Minimizing Distance from Expected Behavior
Anagha Kulkarni, Yantian Zha, Tathagata Chakraborti, Satya Gautam Vadlamudi, Yu Zhang and Subbarao Kambhampati
In Proceedings of International Conference on Autonomous Agents and Multiagent Systems (AAMAS) 2019.
Media: [Full Paper] [Demo Video]