Shaoting Peng

I am a second-year master student majoring in Robotics at GRASP Lab of University of Pennsylvania, co-advised by Prof. Nadia Figueroa and Prof. Ruzena Bajcsy. My research interests currently lie in learning and perception-based robust, efficient and generalizable human-robot interaction (HRI).

Prior graduate study, I received my bachelor degree in Computer Science and Technology from ShanghaiTech University in 2022 advised by Prof. Xuming He. During my undergraduate, I worked as a research intern at OpenDriveLab under the supervision of Prof. Hongyang Li

Email / CV / linkedin / Github

News

[April, 2024] I'll start my PhD at University of Illinois Urbana-Champaign (UIUC) Electrical and Computer Engineering (ECE) department from fall 2024, advised by Prof. Katie Driggs-Campbell!

[February, 2024] Two papers accepted to ICRA 2024! More details can be found below.

Research Projects

	Object Permanence Filter for Robust Tracking with Interactive Robots Shaoting Peng, Margaret X. Wang, Julie A. Shah, Nadia Figueroa ICRA 2024 Project page / Video / Arxiv Proposed a set of assumptions and rules to computationally embed ``object permanence'' into a particle filter scheme to form the 6-DoF object permanence filter (OPF) for occlusion-aware robust perception.
	On the Feasibility of EEG-based Motor Intention Detection for Real-Time Robot Assistive Control Ho Jin Choi, Satyajeet Das, Shaoting Peng, Ruzena Bajcsy, Nadia Figueroa ICRA 2024* Project page / Video / Arxiv Investigated the feasibility of using electroencephalogram (EEG) to achieve binary motor intention classification for robot assistive control in real-time.
	Camera-Lidar Fusion-based Pointcloud Segmentation in Auto-driving Research project at OpenDriveLab, Shanghai AI Lab Explored effective methods for pointcloud segmentation based on camera-Lidar fusion. The RGB image from camera was segmented using DeepLabV3+ to get the segmentation score for each pixel, then projected on lidar pointcloud followed by lidar segmentation. An average mIOU (mean Intersection over Union) of 69.8% across 19 classes on KITTI odometry dataset is achieved, demonstrating a 6% improvement over the baseline model, Cylinder3D.
	Cross-modal Weakly-supervised Segmentation for Myocardial Infarction Research project at PLUS Lab, ShanghaiTech University Explored a weakly-supervised pipeline to register two myocardial image modalities, which are T2 weighted imaging (T2W) with edema regions and phase-sensitive inversion recovery (PSIR) with infarction regions. Participated in RANSAC flow-based registration, nnUNet-based segmentation, and post-processing to reduce the segmentation uncertainty. The recorded Sørensen–Dice coefficient of 0.68 provides evidence of a correlation between myocardial necrosis and edema regions.

Education

University of Pennsylvania

Master of Science in Robotics
September 2022 - Now

Working as a graduate researcher at Figueroa Robotics Lab

ShanghaiTech University

Bachelor of Engineering in Computer Science and Technology
September 2018 - June 2022

Worked as a undergraduate research assistant at PLUS lab

Worked as a teaching assistant in Prof. Sören Schwertfeger's CS110: Computer Architecture in Spring 2021.

Worked as a teaching assistant in Prof. Lifeng Yang's CS110: Computer Architecture in Spring 2021.

Magna Cum Laude (top 10%)

University of California, Berkeley

Exchange Student
July 2019 - August 2019

Miscellanea

I love photographing, here can find some of them.

I like playing acoustic guitar, my favorite guitarists are Kotaro Oshio and Masaaki Kishibe.

I like doing sports, especially working out, swimming, playing badminton and tennis.

I'm a cat person, and my MBTI is ISTP

I believe in the conservation of luck.

This template is a modification to Jon Barron's website.