I am a postdoctoral researcher in the Kavraki Lab at Rice University. I work with Professor Lydia Kavraki on combining symbolic and geometric planning. Specifically, I’m interested in improving the efficiency, robustness, and utility of robot task and motion planning (TMP), with a particular focus on making TMP under uncertainty practically useful.
Though I primarily research robot planning, I’m also interested in ML and formal methods for robotics, robotics research broadly, and programming languages. I am graciously funded by the CRA CIFellows 2021 postdoctoral fellowship.
Research
I work on combining symbolic and geometric planning, often referred to as “integrated task and motion planning”. My work explores approaches to task and motion planning that provide high performance and robustness to action failure with lightweight domain-specific assumptions. I also research approaches to improved planning effort reuse through abstract plan representation and fusions of classical planning with modern machine learning for more efficient, automatic planning and execution.
For more about my research, please see my publication and presentation list.
News
- “Dynamic Motion Planning from Perception via Accelerated Point Cloud Collision Checking” in “Agile Robotics: From Perception to Dynamic Action”, with Clayton W. Ramsey, Zak Kingston, and Lydia Kavraki
- “Stochastic Implicit Neural Signed Distance Functions for Safe Motion Planning under Sensing Uncertainty”, in “Back to the Future: Robot Learning Going Probabilistic”, with Carlos Quintero-Peña, Zak Kingston, Anastasios Kyrillidis, and Lydia Kavraki
- “Motions in Microseconds via Vectorized Sampling-Based Planning”, with Zak Kingston and Lydia Kavraki
- “Stochastic Implicit Neural Signed Distance Functions for Safe Motion Planning under Sensing Uncertainty”, with Carlos Quintero-Peña, Zak Kingston, Anastasios Kyrillidis, and Lydia Kavraki
- “Accelerating Long-Horizon Planning with Affordance-Directed Dynamic Grounding of Abstract Skills”, with Khen Elimelech, Zak Kingston, Moshe Vardi, and Lydia Kavraki
Thanks to the reviewers for their valuable feedback!
Service and Outreach
- I was a faculty chair for RSS Pioneers 2021, helping to recruit invited speakers and design the program for the workshop
- I served as a reviewer for AURO, Black in AI (2017-2020), ICRA (2016, 2019-2023), IJCAI 2021, IJRR (2022), IROS (2017, 2022, 2023), MRS 2019, RA-L (2021-2023), RSS (2019), SIMPAR (2018), T-ASE (2020), and WAFR (2018).
- I was a mentor for Black in AI, providing assistance and advice to my mentee on his Ph.D. program application process. (Fall 2019 - Spring 2020)
- I helped review extended abstracts for the Black in AI workshop. (Fall 2017, 2018, 2019, and 2020)
- I taught 7th and 8th grade girls about state machines and programming at Cornell’s Expanding your Horizons conference. (Spring 2016, 2017, and 2018)
Teaching
- TA for Foundations of Robotics, Cornell University, Professor Ross Knepper (Fall 2016 and Fall 2017)
- Head TA for Introduction to Computing Using Python, Cornell University, Professor Walker White (Fall 2015)
- TA for a multitude of undergraduate courses at UVa {Program and Data Representation, Operating Systems, Artificial Intelligence, Programming Languages} (Fall 2013 to Spring 2015)
Departmental Service
- In 2020, I served on the CS department Anti-Racism Task Force, assisting in making a statement and set of plans for improvements to departmental culture and policy around diversity and inclusion, as well as participating in the hiring process for the CS Director of the Office of Diversity, Equity, and Inclusion
- From 2016 through 2019, I organized the Cornell CS department colloquium czars
- From 2016 through 2018, I coordinated the Cornell CS PhD mentor program