基本信息
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Career Trajectory
Bio
I am interested in the intersection of control theory, sequential decision making, and machine learning, with applications in robotics.
My research goal is to develop algorithms and systems that enable physical robots to operate intelligently, safely, and efficiently, with provable guarantees. Currently, my research trajectory consists of two general approaches:
1. My research aims to develop MDP and POMDP algorithms that tackle realistic assumptions and frameworks - such as having continuous observation and action spaces - which combine provable theoretical convergence guarantees as well as computational efficiency.
2. My research attempts to interface controls and planning techniques with computer vision and machine learning, which enables agents to navigate in unknown environments or in the presence of other agents with unknown intentions.
My research goal is to develop algorithms and systems that enable physical robots to operate intelligently, safely, and efficiently, with provable guarantees. Currently, my research trajectory consists of two general approaches:
1. My research aims to develop MDP and POMDP algorithms that tackle realistic assumptions and frameworks - such as having continuous observation and action spaces - which combine provable theoretical convergence guarantees as well as computational efficiency.
2. My research attempts to interface controls and planning techniques with computer vision and machine learning, which enables agents to navigate in unknown environments or in the presence of other agents with unknown intentions.
Research Interests
Papers共 17 篇Author StatisticsCo-AuthorSimilar Experts
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crossref(2024)
biorxiv(2024)
JOURNAL OF ARTIFICIAL INTELLIGENCE RESEARCH (2023): 1591-1636
2023 62ND IEEE CONFERENCE ON DECISION AND CONTROL, CDC (2023): 6596-6603
L4DCpp.469-482, (2022)
CoRR (2022)
Ecology lettersno. 4 (2022): 516-528
crossref(2022)
arXiv (Cornell University) (2021): 2489-2496
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