About

I'm working on realtime visual-inertial localization and motion tracking algorithms on mobile devices at Google. I got my Ph.D. degree in Computer Science at Colorado School of Mines (Mines) in May 2018 (started from August 2015), under the supervision of Professor Hao Zhang. Before going to Mines, I received a Ph.D. degree in Control Science and Engineering from City University of Hong Kong (CityU) in 2014, under the supervision of Professor Gang (Gary) Feng. I received the B.Eng. degree in Automation from University of Science and Technology of China (USTC) in 2009.

Research

My research is focused on Artificial Intelligence (AI) in robotics, with the objective of integrating the strengths of humans and autonomous robots cooperate together in time-critical and safety-critical applications, e.g. autonomous driving. I use various machine learning and computer vision methods in my research projects.

Awards

• Best paper finalist of RSS'16
• AAAI Student Scholarship
• Computer Science Graduate Student Research Award
• Best oral presentation at C-MAPP
• PerterHo Scholarship at City University of Hong Kong
• Outstanding Student Scholarship at University of Science and Technology of China

Field Work

I always enjoy filed work with our robots from system evaluation, to data collection for various machine learning based applictions. Onsite testing and trouble shooting lead my way to a better understanding of machine learning methods for real-world robotic systems.

Figure: Field work for experiments of visual SLAM as well as human-robot teaming in the underground mine

Selected Publications

Journal

1. Brian Reily, Peng Gao, Fei Han, Hua Wang, Hao Zhang, "Real-time recognition of team behaviors by multisensory graph-embedded robot learning," The International Journal of Robotics Research (IJRR), to appear, 2021. [bibtex]
2. Fei Han, Saad Elbeleidy, Hua Wang, Cang Ye, and Hao Zhang, "Learning of Holism-Landmark Graph Embedding for Place Recognition in Long-Term Autonomy," IEEE Robotics and Automation Letters (RA-L), vol. 3, no. 4, pp. 3669-3676, 2018. [bibtex] [The contents of this paper were also selected by IROS'18 Program Committee for presentation at the Conference]
3. Fei Han, Hua Wang, Guoquan Huang, and Hao Zhang, "Sequence-Based Sparse Optimization Methods for Long-Term Loop Closure Detection in Visual SLAM," Autonomous Robots (AuRo), vol. 42, no. 7, pp. 1323-1335, 2018. [bibtex]
4. Fei Han, Xue Yang, Yiming Deng, Mark Rentschler, Dejun Yang, and Hao Zhang, "SRAL: Shared Representative Appearance Learning for Long-Term Visual Place Recognition," IEEE Robotics and Automation Letters (RA-L), vol. 2, no. 2, pp. 1172-1179, April 2017 [bibtex] [project] [code]
5. Fei Han, Brian Reily, William Hoff, and Hao Zhang, "Space-Time Representation of People Based on 3D Skeletal Data: A Review," Computer Vision and Image Understanding (CVIU), vol. 158, pp. 85-105, May 2017. [bibtex]
6. Brian Reily*, Fei Han*, Lynne Parker, and Hao Zhang, "Skeleton-Based Bio-Inspired Human Activity Prediction For Real-Time Human-Robot Interaction," Autonomous Robots (AuRo), vol. 42, no. 6, pp. 1281-1298, 2018. * Equal contribution [bibtex]

Highly Selective Conference

1. Hao Zhang, Fei Han, and Hua Wang, "Robust multimodal sequence-based loop closure detection via structured sparsity," in Robotics: Science and Systems (RSS), 2016, (Acceptance Rate: 20.6%, Best Paper Finalist). [bibtex] [slides] [poster]

Conference & Workshop

1. Fei Han, Sriram Siva, and Hao Zhang, "Scalable representation learning for long-term augmented reality-based information delivery in collaborative human-robot perception," in International Conference on Virtual, Augmented and Mixed Reality (VAMR), 2019. [bibtex]
2. Kai Liu, Hua Wang, Fei Han, and Hao Zhang, "Visual Place Recognition via Robust l2-norm Distance Based Holism And Landmark Integration," in AAAI Conference on Artificial Intelligence (AAAI), 2019. [bibtex]
3. Fei Han, Hua Wang, and Hao Zhang, "Learning of Integrated Holism-Landmark Representations for Long-Term Loop Closure Detection," in AAAI Conference on Artificial Intelligence (AAAI), 2018. [bibtex]
4. Fei Han and Hao Zhang, "Team Intent Understanding through Latent Representation Learning for Underground Search and Rescue," in Workshop of IEEE International Conference on Robotics and Automation (ICRA), 2018. [bibtex]
5. Fei Han, Xue Yang, Yu Zhang, and Hao Zhang, "Sequence-based Multimodal Apprenticeship Learning For Robot Perception and Decision Making," in IEEE International Conference on Robotics and Automation (ICRA), 2017. [bibtex]
6. Fei Han, Xue Yang, Christopher Reardon, Yu Zhang, and Hao Zhang, "Simultaneous Feature and Body-Part Learning for Real-Time Robot Awareness of Human Behaviors," in IEEE International Conference on Robotics and Automation (ICRA), 2017. [bibtex] [project] [code]
7. Fei Han, Christopher Reardon, Lynne Parker, and Hao Zhang, "Minimum Uncertainty Latent Variable Models for Robot Recognition of Sequential Human Activities," in IEEE International Conference on Robotics and Automation (ICRA), 2017. [bibtex]
8. Fei Han, Christopher Reardon, Cang Ye, and Hao Zhang, "Robot Understanding of Human Intents in Gesture-based Interaction," in Workshop of IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2017. [bibtex]
9. Fei Han, Jiayi Liu, William Hoff, and Hao Zhang, "Poster: Planning-based Workflow Modeling for AR-enabled Automated Task Guidance," in IEEE International Symposium on Mixed and Augmented Reality (ISMAR), 2017. [bibtex]
10. Christopher Reardon, Fei Han, Hao Zhang, and Jonathan Fink, "Optimizing Autonomous Surveillance Route Solutions from Minimal Human-Robot Interaction," in IEEE International Symposium on Safety, Security, and Rescue Robotics (SSRR), 2017. [bibtex]
11. Fei Han, Xue Yang, Yiming Deng, Mark Rentschler, Dejun Yang, and Hao Zhang, "Life-Long Place Recognition by Shared Representative Appearance Learning," in Robotics: Science and Systems (RSS) Workshop of Visual Place Recognition: What is it Good For?, 2016. [bibtex] [project] [slides] [poster] [code]
12. Fei Han, Christopher Dreyer, Thomas Jones, Rob Kelso, James Thomas, and Hao Zhang, "Data-Driven Fault Detection via Sparse Multisensory Learning," in AIAA Annual Technical Symposium (ATS), 2016. [bibtex]
13. Xue Yang, Fei Han, Hua Wang, and Hao Zhang, " Enforcing template representability and temporal consistency for adaptive sparse tracking," in International Joint Conference on Artificial Intelligence (IJCAI), 2016. [bibtex]
14. Hao Zhang, Christopher Reardon, Fei Han, and Lynne E. Parker "SRAC: Self-Reflective Risk-Aware Artificial Cognitive Models for Robot Response to Human Activities," in IEEE International Conference on Robotics and Automation (ICRA), 2016. [bibtex]

Reviewer

Journal

• IEEE Transactions on Fuzzy Systems
• Fuzzy Sets and Systems
• Neurocomputing
• IET Control Theory & Applications

Conference

• AAAI Conference on Artificial Intelligence (AAAI), 2016-
• International Conference on Robotics and Automation (ICRA), 2016, 2018
• IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2016
• IEEE International Conference on Humanoid Robots (Humanoids), 2015-2016

Teaching