I’m a graduate student in Computer Science and Engineering at the University of Michigan, advised by Professor Chad Jenkins. My research interests are in advanced computing topics and especially those that make connections between nondeterminstic computing, deep learning, probabilistic inference, and perception for robotics.

I’m proud to be a recipient of the Qualcomm Innovation Fellowship. I earned my BSE (2014-2018) and MSE (2019-2020) in computer science at the University of Michigan. Between degree programs, I worked on applied machine learning research at MIT Lincoln Laboratory under the direction of Dr. Jason Thornton and Dr. Pedro Torres-Carrasquillo.

This summer (2023), I look forward to working as an Applied Scientist Intern at Amazon Lab126 under the direction of Dr. Aravindhan Krishnan and Dr. Shreekant Gayaka.

Are you a University of Michigan student interested in robotics research, mobile manipulation robots, perception algorithms, or deep learning?
I’m actively looking for motivated students who are interested in collaborating on ongoing research projects. If this sounds of interest, kindly fill out this scheduling form and I will be happy to discuss potential opportunities with you.

Organizing

I’m excited to be co-organizing the workshop on Differentiable Probabilistic Robotics: Emerging Perspectives on Robot Learning as a part of the IEEE / RSJ International Conference on Intelligent Robots and Systems (IROS) to be held in Detroit, Michigan in October, 2023.

IROS 2023

Differentiable Probabilistic Robotics: Emerging Perspectives on Robot Learning

Co-Organizer

Publications

Journal Articles

DNBP: Differentiable Nonparametric Belief Propagation.
Anthony Opipari, Jana Pavlasek, Chao Chen, Shoutian Wang, Karthik Desingh, Odest Chadwicke Jenkins.
Accepted: ACM / IMS Journal of Data Science. 2023.

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Efficient Nonparametric Belief Propagation for Pose Estimation and Manipulation of Articulated Objects.
Karthik Desingh, Shiyang Lu, Anthony Opipari, Odest Chadwicke Jenkins.
Science Robotics. 2019.

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Peer-Reviewed Conference Proceedings

A Reconfigurable Hardware Library for Robot Scene Perception.
Yanqi Liu, Anthony Opipari, Odest Chadwicke Jenkins, Ruth Iris Bahar.
IEEE / ACM International Conference on Computer-Aided Design. 2022.

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ClearPose: Large-scale Transparent Object Dataset and Benchmark.
Xiaotong Chen, Huijie Zhang, Zeren Yu, Anthony Opipari, Odest Chadwicke Jenkins.
ECVA European Conference on Computer Vision. 2022.

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Hardware Acceleration of Nonparametric Belief Propagation for Efficient Robot Manipulation.
Yanqi Liu, Anthony Opipari, Theo Guerin, Ruth Iris Bahar.
ACM / SIGDA International Symposium on Field-Programmable Gate Arrays. 2022.

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Factored Pose Estimation of Articulated Objects using Efficient Nonparametric Belief Propagation.
Karthik Desingh, Shiyang Lu, Anthony Opipari, Odest Chadwicke Jenkins.
IEEE International Conference on Robotics and Automation. 2019.

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Workshop Papers

Visual Robot Pose Tracking through Counter-Hypothetical Nonparametric Belief Propagation.
Elizabeth Olson, J. Arden Knoll, Anthony Opipari, Grant Gibson, Odest Chadwicke Jenkins.
Distributed Graph Algorithms for Robotics (IEEE ICRA). 2023.

TransNet: Category-Level Transparent Object Pose Estimation.
Huijie Zhang, Anthony Opipari, Xiaotong Chen, Jiyue Zhu, Zeren Yu, Odest Chadwicke Jenkins.
7th International Workshop on Recovering 6D Object Pose (ECVA ECCV). 2022.

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NeRF-Frenemy: Co-Opting Adversarial Learning for Autonomy-Directed Co-Design.
Stanley Lewis, Bahaa Aldeeb, Anthony Opipari, Elizabeth Olson, Cameron Kisailus, Odest Chadwicke Jenkins.
Implicit Representations for Robotic Manipulation (RSS). 2022.

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Differentiable Nonparametric Belief Propagation.
Anthony Opipari, Jana Pavlasek, Chao Chen, Shoutian Wang, Karthik Desingh, Odest Chadwicke Jenkins.
Robotic Perception and Mapping: Emerging Techniques (IEEE ICRA). 2022.

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Analysis of Goal-Directed Manipulation in Clutter using Scene Graph Belief Propagation.
Karthik Desingh, Anthony Opipari, Odest Chadwicke Jenkins.
Multimodal Robot Perception (IEEE ICRA). 2018.

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Patents

Systems and Methods for Detection of Concealed Threats.
Marianne A. DeAngelus, Justin Goodwin, Neela Kaushik, Anthony Opipari, Taylor Killian.
United States Patent and Trademark Office: US-20220334243-A1. 2022.

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