Pratik Prabhanjan Brahma
Papers
1
Total Citations
3
H-Index
1
About
Pratik Prabhanjan Brahma is a researcher whose work sits at the critical intersection of autonomous driving, robotics, and probabilistic machine learning. His primary research focus is on trajectory and behavior prediction for traffic agents—a fundamental challenge for safe and reliable autonomous navigation. Brahma’s major contribution lies in rigorously analyzing the "variety loss" phenomenon within the context of probabilistic trajectory prediction. By framing future sequence generation as a probabilistic problem, he has explored how generative models can be effectively applied to anticipate the diverse, uncertain behaviors of vehicles and pedestrians. His 2019 paper on this topic, which has garnered 3 citations, provides a foundational lens for understanding the limitations and potential of these models in real-world planning systems. This work is particularly notable for its direct relevance to robot planning and autonomous driving stacks, where predicting multiple plausible futures is essential for safety. Brahma’s research helps bridge the gap between theoretical generative modeling and practical, safety-critical applications, offering valuable insights for students and engineers working on the next generation of intelligent transportation systems.
Research Focus
Key Achievements
Top Papers
- 1