Priya Sundaresan

I am a 2nd year PhD student at Stanford University, advised by Professor Dorsa Sadigh in the Stanford Intelligent and Interactive Autonomous Systems Group (ILIAD) and Jeannette Bohg in the Interactive Perception and Robot Learning Lab. I am interested in robot manipulation through multimodal perception, and I am funded by the National Science Foundation Graduate Fellowship.

Before Stanford, I completed my B.S. and M.S. at UC Berkeley, where I worked with Professor Ken Goldberg in the AUTOLAB within Berkeley AI Research (BAIR).

priyasun@stanford.edu / CV / Github / Google Scholar / Twitter

Research

	In-Mouth Robotic Bite Transfer with Visual and Haptic Sensing Lorenzo Shaikewitz, Yilin Wu, Suneel Belkhale, Jennifer Grannen, Priya Sundaresan, Dorsa Sadigh International Conference on Robotics and Automation (ICRA), 2023.* Website / PDF
	Learning Visuo-Haptic Skewering Strategies for Robot-Assisted Feeding Priya Sundaresan, Suneel Belkhale, Dorsa Sadigh Conference on Robot Learning (CoRL), 2022. Oral Presentation Website / PDF
	DiffCloud: Real-to-Sim from Point Clouds with Differentiable Simulation and Rendering of Deformable Objects Priya Sundaresan, Rika Antonova, Jeannette Bohg International Conference on Intelligent Robots and Systems (IROS), 2022. Website / PDF
	A Bayesian Treatment of Real-to-Sim for Deformable Object Manipulation Rika Antonova, Jingyun Yang, Priya Sundaresan, Dieter Fox, Fabio Ramos, Jeannette Bohg IEEE Robotics and Automation Letters (RA-L), 2022. PDF
	Disentangling Dense Multi-Cable Knots Vainavi Viswanath, Jennifer Grannen, Priya Sundaresan, Brijen Thananjeyan, Ashwin Balakrishna, Ellen Novoseller, Jeffrey Ichnowski, Michael Laskey, Joseph E. Gonzalez, Ken Goldberg International Conference on Intelligent Robots and Systems (IROS), 2021.* Website / PDF
	Untangling Dense Non-Planar Knots by Learning Manipulation Features and Recovery Policies Priya Sundaresan, Jennifer Grannen, Brijen Thananjeyan, Ashwin Balakrishna, Jeffrey Ichnowski, Ellen Novoseller, Minho Hwang, Michael Laskey, Joseph E. Gonzalez, Ken Goldberg Robotics: Science and Systems (RSS), 2021. Website / PDF
	Learning Dense Visual Correspondences in Simulation to Smooth and Fold Real Fabrics Aditya Ganapathi, Priya Sundaresan, Brijen Thananjeyan, Ashwin Balakrishna, Daniel Seita, Jennifer Grannen, Minho Hwang, Ryan Hoque, Joseph E. Gonzalez, Nawid Jamali, Katsu Yamane, Soshi Iba, Ken Goldberg International Conference on Robotics and Automation (ICRA), 2021. Website / PDF
	MMGSD: Multi-Modal Gaussian Shape Descriptors for Correspondence Matching in 1D and 2D Deformable Objects. Priya Sundaresan, Aditya Ganapathi, Brijen Thananjeyan, Ashwin Balakrishna, Daniel Seita, Ryan Hoque, Joseph Gonzalez, Ken Goldberg International Conference on Intelligent Robots and Systems (IROS), Workshop on Robotic Manipulation of Deformable Objects, 2020. PDF
	Untangling Dense Knots by Learning Task-Relevant Keypoints Jennifer Grannen, Priya Sundaresan, Brijen Thananjeyan, Jeffrey Ichnowski, Ashwin Balakrishna, Minho Hwang, Vainavi Viswanath, Michael Laskey, Joseph E. Gonzalez, Ken Goldberg Conference on Robot Learning (CoRL), 2020. Oral Presentation Website / PDF
	Learning Rope Manipulation Policies Using Dense Object Descriptors Trained on Synthetic Depth Data. Priya Sundaresan, Jennifer Grannen, Brijen Thananjeyan, Ashwin Balakrishna, Michael Laskey, Kevin Stone, Joseph E. Gonzalez, Ken Goldberg. International Conference on Robotics and Automation (ICRA), 2020. Website / PDF
	Automated Extraction of Surgical Needles from Tissue Phantoms Priya Sundaresan, Brijen Thananjeyan, Johnathan Chiu, Danyal Fer, Ken Goldberg Conference on Automation Science and Engineering (CASE), 2019. PDF

For Fun

Doge Dodge
This is a silly little game I made which is heavily inspired by the Chrome T-Rex game that pops up when there's bad connectivity (s/o to UC Berkeley's wifi!), as well as my favorite game of all time, Crossy Road!!
Credits: tile art and sound effects, doge art, cactus art, background art, rock art, spike art.

Shoutout to Jon Barron for the awesome website template <3.