Hardik Parwana

University of Michigan–Ann Arbor

Papers

5

Total Citations

62

H-Index

2

About

Hardik Parwana is a rising researcher at the forefront of safe control synthesis for autonomous and robotic systems. His work centers on developing rigorous, practical methods to guarantee safety in complex, nonlinear dynamical systems—a critical challenge for deploying robots in the real world. Parwana’s most significant contribution is his pioneering work on Control Barrier Functions (CBFs), where his highly cited tutorial paper (43 citations) systematically addresses practical hurdles like time-varying constraints and input limits, bridging the gap between theory and application. He has also introduced a constructive method for designing safe multirate controllers for differentially-flat systems, enabling safety guarantees even when control loops operate at different frequencies. More recently, Parwana has ventured into continuum robotics, proposing a novel Neural Configuration Signed Distance Function (N-CSDF) to model robot shapes with high accuracy. His work on integrating Model Predictive Path Integral control with reach-avoid tasks and CBFs further showcases his commitment to robust, safety-critical autonomy. With a growing citation impact and a focus on both foundational theory and deployable algorithms, Parwana is shaping the future of safe, autonomous systems.

Research Focus

Key Achievements

2
H-Index
5
Papers
62
Total Citations
12
Avg Citations/Paper
🏆 Most Cited Paper
Advances in the Theory of Control Barrier Functions: Addressing practical challenges in safe control synthesis for autonomous and robotic systems
43 citations · 2024
📈 Most Prolific Year: 2024 (2 Papers)
🤝 Key Collaborators: 15
🏛 Institutions: University of Michigan–Ann Arbor

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 12 days ago