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Posts by Collection
portfolio
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publications
Computer Vision for Recognition of Materials and Vessels in Chemistry Lab Settings and the Vector-LabPics Data Set
Published in ACS Central Science, 2020
Recommended citation: Eppel, Sagi, Haoping Xu, Mor Bismuth, and Alan Aspuru-Guzik. “Computer Vision for Recognition of Materials and Vessels in Chemistry Lab Settings and the Vector-LabPics Data Set.” ACS Central Science 6, no. 10 https://pubs.acs.org/doi/full/10.1021/acscentsci.0c00460
Computer vision for liquid samples in hospitals and medical labs using hierarchical image segmentation and relations prediction
Published in arXiv, 2021
Recommended citation: Eppel, Sagi, Haoping Xu, and Alan Aspuru-Guzik. “Computer Vision for Liquid Samples in Hospitals and Medical Labs Using Hierarchical Image Segmentation and Relations Prediction.” arXiv, May 4, 2021. https://arxiv.org/abs/2105.01456
Predicting 3D shapes, masks, and properties of materials, liquids, and objects inside transparent containers, using the TransProteus CGI dataset
Published in Digital Discovery, 2021
Recommended citation: Eppel, Sagi, Haoping Xu, Yi Ru Wang, and Alan Aspuru-Guzik. “Predicting 3D Shapes, Masks, and Properties of Materials inside Transparent Containers, Using the TransProteus CGI Dataset.” Digital Discovery 1, no. 1 https://pubs.rsc.org/en/content/articlelanding/2022/dd/d1dd00014d
Seeing Glass: Joint Point Cloud and Depth Completion for Transparent Objects
Published in Conference on Robot Learning (CoRL) 2021, 2021
Recommended citation: Xu, Haoping, Yi Ru Wang, Sagi Eppel, Alàn Aspuru-Guzik, Florian Shkurti, and Animesh Garg. “Seeing Glass: Joint Point Cloud and Depth Completion for Transparent Objects.” in proceedings of Conference on Robot Learning (CoRL) 2021 https://arxiv.org/abs/2110.00087
Conformer Search Using SE3-Transformers and Imitation Learning
Published in NeurIPS 2022 Workshop AI4Mat, 2022
Recommended citation: Thiede, Luca, Santiago Miret, Krzysztof Sadowski, Haoping Xu, Mariano Phielipp, and Alan Aspuru-Guzik. “Conformer Search Using SE3-Transformers and Imitation Learning" in NeurIPS 2022 Workshop AI4Mat https://openreview.net/forum?id=b832-LQhwYP
An adaptive robotics framework for chemistry lab automation
Published in arXiv, 2022
Recommended citation: Yoshikawa, Naruki, Andrew Zou Li, Kourosh Darvish, Yuchi Zhao, Haoping Xu, Artur Kuramshin, Alán Aspuru-Guzik, Animesh Garg, and Florian Shkurti. “Chemistry Lab Automation via Constrained Task and Motion Planning.” arXiv https://arxiv.org/abs/2212.09672
MVTrans: Multi-View Perception of Transparent Objects
Published in 2023 IEEE International Conference on Robotics and Automation (ICRA), 2023
Recommended citation: Wang, Yi Ru, Yuchi Zhao, Haoping Xu, Sagi Eppel, Alán Aspuru-Guzik, Florian Shkurti, and Animesh Garg. “MVTrans: Multi-View Perception of Transparent Objects.” In 2023 IEEE International Conference on Robotics and Automation (ICRA), 3771–78, 2023. https://ieeexplore.ieee.org/abstract/document/10161089
talks
Automated Chemistry Lab via Perception-based Robot
Published:
Led by Professor Samantha-Jo Caetano in the past years, the ISSC (Integrated Statistical Student Community) Summer Speaker Series has provided an opportunity for graduate students to share their research and grad school experience with undergraduate students. This year, to facilitate cross-faculty student connection and increase engagement, UTMIST (University of Toronto Machine Intelligence Student Team) will be collaborating with ISSC and Prof. Caetano to deliver a monthly, virtual speaker series from May to August. The details and expectations are listed below.
teaching
CSC420: Introduction to Image Understanding
Undergraduate course, University of Toronto, Computer Science, 2019
Teaching Assistant
CSC 412/2506 Probabilistic Machine Learning
Undergraduate course, University of Toronto, Computer Science, 2020
Teaching Assistant
CSC311 - Introduction to Machine Learning
Undergraduate course, University of Toronto, Computer Science, 2020
Teaching Assistant
CSC317: Computer Graphics
Undergraduate course, University of Toronto, Computer Science, 2021
Teaching Assistant
CSC 412/2506 Probabilistic Machine Learning
Undergraduate course, University of Toronto, Computer Science, 2021
Teaching Assistant
CSC420: Introduction to Image Understanding
Undergraduate course, University of Toronto, Computer Science, 2021
Teaching Assistant
CSC 412/2506 Probabilistic Machine Learning
Undergraduate course, University of Toronto, Computer Science, 2022
Teaching Assistant
CSC420: Introduction to Image Understanding
Undergraduate course, University of Toronto, Computer Science, 2022
Teaching Assistant
CSC 412/2506 Probabilistic Machine Learning
Undergraduate course, University of Toronto, Computer Science, 2023
Teaching Assistant