Ahmed H. Qureshi
Computer Science · Purdue University West Lafayette
Publications
108
Citations
1,113
Est. group size
~5
Recurring co-author estimate
Active years
19
Publishing since 2008
Ahmed H. Qureshi works in robotics, focusing on how robots plan motions, manipulate objects, and navigate in unknown or cluttered environments. His work combines machine learning (including reinforcement learning and diffusion-based policies) with physics-informed and formal methods to make robot behavior more reliable and efficient, spanning single- and multi-agent settings.
Publication output has grown substantially over the past decade, rising from a handful of papers per year before 2020 to around 14–21 per year in 2023-2025.
Generated by claude-sonnet-5 from public bibliographic data · Jul 20, 2026
- Formal Methods in Robot Policy Learning and Verification: A Survey on Current Techniques and Future Directions
Open MIND · 2026
- Multi-Agent Monte Carlo Tree Search for Makespan-Efficient Object Rearrangement in Cluttered Spaces
Open MIND · 2026
- Multi-Agent Monte Carlo Tree Search for Makespan-Efficient Object Rearrangement in Cluttered Spaces
arXiv (Cornell University) · 2026
- Formal Methods in Robot Policy Learning and Verification: A Survey on Current Techniques and Future Directions
arXiv (Cornell University) · 2026
- Safe Continuous-time Multi-Agent Reinforcement Learning via Epigraph Form
Open MIND · 2026
- Safe Continuous-time Multi-Agent Reinforcement Learning via Epigraph Form
arXiv (Cornell University) · 2026
- PPGuide: Steering Diffusion Policies with Performance Predictive Guidance
arXiv (Cornell University) · 2026
- PPGuide: Steering Diffusion Policies with Performance Predictive Guidance
arXiv (Cornell University) · 2026
- Graph-of-Constraints Model Predictive Control for Reactive Multi-agent Task and Motion Planning
arXiv (Cornell University) · 2026
- Graph-of-Constraints Model Predictive Control for Reactive Multi-agent Task and Motion Planning
arXiv (Cornell University) · 2026
- DeRi-IGP: Learning to Manipulate Rigid Objects Using Deformable Linear Objects via Iterative Grasp-Pull
IEEE Robotics and Automation Letters · 2025
- Physics-Informed Neural Mapping and Motion Planning in Unknown Environments
IEEE Transactions on Robotics · 2025
- Differentiable Composite Neural Signed Distance Fields for Robot Navigation in Dynamic Indoor Environments
2025
- Integrating Active Sensing and Rearrangement Planning for Efficient Object Retrieval from Unknown, Confined, Cluttered Environments
2025
- Differentiable Composite Neural Signed Distance Fields for Robot Navigation in Dynamic Indoor Environments
arXiv (Cornell University) · 2025
- arXiv (Cornell University)×52
- IEEE Robotics and Automation Letters×5
- IEEE Transactions on Robotics×4
- Open MIND×3
- Robotics and Autonomous Systems×1
- Ruiqi Ni
Computer Science · Purdue University West Lafayette
- Zachary Kingston
Computer Science · Purdue University West Lafayette
- Lantao Liu
Computer Science · Indiana University
- Weizhe Chen
Computer Science · Indiana University
- Ayanna Howard
Computer Science · The Ohio State University
This profile was generated automatically from public scholarly data (OpenAlex). Group size and activity levels are estimates derived from co-authorship patterns.
Last updated Jul 20, 2026.
Claim or correct this profile