Elnaz Jahani Heravi
Papers
1
Total Citations
28
H-Index
1
About
Elnaz Jahani Heravi is a researcher whose work lies at the intersection of robotics, machine learning, and intelligent systems, with a particular focus on trajectory prediction and motion planning. Her most-cited paper, "Long Term Trajectory Prediction of Moving Objects Using Gaussian Process" (2011, 28 citations), addresses a critical challenge in robotics: accurately forecasting the future paths of moving objects over extended time horizons. This work highlights the limitations of traditional techniques like MLP and ANFIS when applied to small, deterministic datasets for online training, and proposes Gaussian Process-based methods as a robust alternative. By tackling the problem of long-term prediction with sparse data, Heravi’s contributions have implications for autonomous navigation, human-robot interaction, and dynamic environment modeling. Her research demonstrates a commitment to developing intelligent, data-efficient algorithms that enhance the reliability of robotic systems in real-world scenarios. With her work cited in studies on motion prediction and control, she has established a foundation for further exploration in adaptive and probabilistic modeling, making her a notable figure in the field of robotics and artificial intelligence.
Research Focus
Key Achievements
Top Papers
- 1Long Term Trajectory Prediction of Moving Objects Using Gaussian Process28 citations · 2011