Hi! I'm an Ph.D student at the University of Southern California, where I work with Jesse Thomason on language grounding and human-robot interaction. I build robots that interact with their environment and other humans, and study how humans percieve their actions.

I was a visiting scholar at Cornell with Tapo Bhattacharjee working on assistive robotics for people with mobility limitations. Previously at UT Austin, I worked on human-robot interaction with the Building-Wide Intelligence Project with Justin Hart and Peter Stone. I also completed an honors thesis with Chandrajit Bajaj.

I previously interned at Sandia National Labs with the Neural Exploration and Research Lab. Over three years, I had the pleasure of working with James Aimone, Craig Vineyard, and many others!

abrar.anwar [at] usc [dot] edu

news

Dec 2022	I will be presenting my work on Human-Robot Commensality at CoRL 2022!
July 2022	My work on social bite timing was featured on the New Scientist!
May 2022	I will be a Visiting Scholar at Cornell University with Tapo Bhattacharjee to work on robot-assisted dining in social settings
June 2021	I will be presenting our work on gaze for social navigation at ICRA 2021
May 2021	I defended my honors thesis on deep reinforcement learning for mesh refinement and finally graduated from UT Austin
May 2021	I will be working with Tapo Bhattacharjee from Cornell this summer thanks to the Google exploreCSR program
May 2021	I will be joining the University of Southern California for my PhD to work on HRI and language grounding with Jesse Thomason
Jan 2021	I attended the AAAI-21 Undergraduate Consortium, and met so many wonderful people while presenting my research on spiking weight-agnostic neural networks
Jan 2021	I will be participating in Google Research's CS Research Mentorship program

2020 and Earlier

July 2020

I (virtually) attended my first conference, ICONS, and presented a poster on spiking neural networks

research

2024
	Robot-assisted Inside-mouth Bite Transfer using Robust Mouth Perception and Physical Interaction-Aware Control Rajat Jenamani, Daniel Stabile, Ziang Liu, Abrar Anwar, Katherine Dimitropoulou, Tapomayukh Bhattacharjee We design a system to feed people with disabilities in their mouth using real-time mouth perception and tactile-informed control. HRI, 2024
2023
	Exploring Strategies for Efficient VLN Evaluation Abrar Anwar, Rohan Gupta, Elle Szabo, Jesse Thomason Evaluation in the real world is often time-consuming and expensive, so we propose a targeted contrast set-based evaluation strategy to efficiently evaluate the linguistic and visual capabilities of an end-to-end VLN policy. CoRL Language and Robotics Workshop. (Oral presentation), 2023 paper
	Comparative Reasoning for Multi-View Language Grounding Abrar Anwar, Chancharik Mitra, Rodolfo Corona, Dan Klein, Trevor Darrell, Jesse Thomason We present the MAGiC model which selects an object referent based on language meant to distinguish between two similar objects by reasoning over both objects from multiple vantage points. In review, 2023
2022
	Human-Robot Commensality: Bite Timing Prediction for Robot-Assisted Feeding in Groups Jan Ondras, Abrar Anwar, Tong Wu, Fanjun Bu, Malte Jung, Jorge Jose Ortiz, Tapomayukh Bhattacharjee We develop data-driven models to predict when a robot should feed during social dining scenarios. We build a dataset of human-human commensality, develop novel models to learn social dynamics of when to feed, and conduct a human-robot commensality study. CoRL, 2022 paper* arxiv
2021
	Deep Reinforcement Learning for Optimal Refinement of Cross-Sectional Mesh Sequence Finite Elements Abrar Anwar Developed the first deep reinforcement learning framework for mesh refinement and refined “good” quality surface reconstructions of cross-sectional contours using soft-actor critic Honors Thesis, 2021
	Watch Where You're Going! Gaze and Head Orientation as Predictors for Social Robot Navigation Blake Holman, Abrar Anwar, Akash Singh, Mauricio Tec, Justin Hart, Peter Stone We leverage virtual reality to collect gaze and position data to create a predictive model and a mixed effects model to show gaze orientation precedes other features ICRA, 2021 paper video
2020
	Evolving Spiking Circuit Motifs using Weight Agnostic Neural Networks. Abrar Anwar, Craig Vineyard, William Severa, Srideep Musuvathy, Suma Cardwell An evolutionary, weight agnostic method is used to generate spiking neural networks used for classification, control, and various other tasks AAAI-21 Undergraduate Consortium , 2021 Computer Science Research Institute Summer Proceedings, 2020 International Conference on Neuromorphic Systems (poster), 2020 paper tech report poster
2019
	BrainSLAM: Robust autonomous navigation in sensor-deprived contexts Felix Wang, James B. Aimone, Abrar Anwar, Srideep Musuvathy. We explore using brain-inspired approaches to navigation and localization in a noisy, data-sparse environment for a hypersonic glide vehicle. Rotation invariant feature representations are used to increase accuracy and reduce map storage Sandia National Labs Technical Report, 2019 tech report

Design and source code from Jon Barron's website

news

research

2024

2023

2022

2021

2020

2019