Jiaji (Robin) Zhou
The Robotics Institute
School of Computer Science
Carnegie Mellon University
Email: jiajiz [at] cs [dot] cmu [dot] edu


Startup: XYZ Robotics (stay tuned)

My CMU RI Seminar Talk on ICRA 2016 BEST PAPER

Some internship work at TRI: Book Pulling (IEEE Spectrum)

Planar Manipulation Software Toolbox

IROS Workshop on Contact-rich Interaction

Brief Bio

I recently graduated with a PhD from The Robotics Institute of CMU School of Computer Science. I was co-advised by Drew Bagnell and Matt Mason.

I interned at TRI Manipulation Group , GoogleX Self-driving Car team (now Waymo) and Turi.

I received my Master of Robotics in Dec. 2013 from CMU and B.S. in Computer Science in June. 2012 from Chien-Shiung Wu Honors College, Southeast University.

Research Interests

My most recent work focuses on 3D perception in the context of robotic manipulation. My thesis addresses several aspects of contact-rich robotic manipulation including mechanics modeling, planning, control and perception.

Current Research Projects

Pushing revisited: Differential flatness, trajectory planning and stabilization [Preprint]
Jiaji Zhou, Matthew T. Mason
ISRR 2017
A Probabilistic Planning Framework for Planar Grasping Under Uncertainty [PDF]
Jiaji Zhou, Robert Paolini, Aaron M. Johnson, J. Andrew Bagnell, Matthew T. Mason
IROS (RA-Letter) 2017
A fast stochastic contact model for planar pushing and grasping: Theory and experimental validation, [PDF][IJRR]
Jiaji Zhou, J. Andrew Bagnell, Matthew T. Mason
RSS 2017
IJRR 2018
A Convex Polynomial Force-Motion Model for Planar Sliding: Identification and Application [PDF][IJRR]
Jiaji Zhou, Robert Paolini, J. Andrew Bagnell, Matthew T. Mason
ICRA 2016 Best Conference Paper
IJRR 2018

Past Research Projects

My master's research projects explored provable techniques for near-optimal algorithms for list prediction, with applications in document summarization, spatially fine-grained object detection, manipulator trajectory library selection.

Visual Chunking: A List Prediction Framework for Region-based Object Detection [PDF]
Nick Rhinehart, Jiaji Zhou, Martial Hebert, J. Andrew (Drew) Bagnell
ICRA 2015
Learning Policies for Contextual Submodular Prediction [PDF]
Stephane Ross, Jiaji Zhou, Yisong Yue, Debadeepta Dey, J. Andrew (Drew) Bagnell
ICML 2013
[Code based upon Vowpal Wabbit]
Knapsack Constrained Contextual Submodular List Prediction with Application to Multi-document Summarization [PDF]
Jiaji Zhou, Stephane Ross, Yisong Yue, Debadeepta Dey, J. Andrew (Drew) Bagnell
ICML 2013 Workshop on Inferning: Interactions between Inference and Learning

Technical Reports and Fun Math

Clustering via Determinantal Point Processes , Paul Vernaza, Jiaji Zhou, Kris Kitani, J. Andrew (Drew) Bagnell

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